I’ve been having some version of the same conversation for months now with other senior comms people in my life. The job and its ultimate purpose are vastly changed but still recognizable in its aims and mechanics. But the place where any of it actually lives has gotten... strange. Reach is getting weird.1

It was along those lines that I joked this week with a friend in the content industry that pretty soon all content will be either 10-second TikToks or three-hour podcasts. But I was only half joking.

More and more, the cultural firehose runs on clips, and the discourse layer runs in two-to-three-hour conversations. Everything in between is collapsing. The problem in comms is the part that’s collapsing fastest is exactly the part comms has spent 50 years optimizing for.

The middle is hollowing

In 2018, 54% of Americans said they turned to their preferred news organization first when something was breaking. By March 2026, Pew had that number at 36%. Eighteen points of distribution gone from the institution that used to be breaking news, in seven years.

The U.S. magazine industry is on track for $39.3 billion in 2026 revenue, down at a compound 2.2% rate since 2021. Publishers themselves are now telling Reuters Institute they’re scaling back service journalism, general news, and evergreen reporting, the entire mid-length feature-and-explainer category that magazines were built around.

Daily news access among 18-to-24-year-olds is down 15 percentage points since 2017. Their use of Facebook as a news source has collapsed from 47% in 2014 to 16% in 2025. The share who say they are very or extremely interested in news at all has fallen 25 points in twelve years.

Meanwhile both ends of the distribution are stronger than they’ve ever been. Forty-five percent of Americans listen to or watch podcasts every week, an all-time high. On Buzzsprout’s platform, one of the largest podcast hosts, 33% of episodes run over 40 minutes and 13% over an hour as of April 2026. Goalhanger, the production company behind The Rest Is Politics, now sees 40% of its YouTube views come via connected television. A longform format colonizing the living-room TV slot that used to belong to network news.

The shortform side is louder. The average TikTok user watches 92 videos a day at a 35-second-per-video rhythm; the algorithm’s sweet spot for reach is 21 to 34 seconds. Seventy-three percent of 18-to-24-year-olds get news from short video every week.

The dollars confirm the shape. U.S. podcast ad revenue grew 17.6% in 2025 to $2.86 billion, per the IAB and PwC, and is projected to grow another 9.6% in 2026 to roughly $3.1 billion. The money isn’t distributing evenly. Spotify alone paid more than $100 million to a handful of top podcasters — Rogan, Alex Cooper, Theo Von — in a single quarter of 2025. At the other end of the market, the top 10 podcast advertisers ran combined buys of $132.8 million in Q1 2026, with several deploying their budgets across more than a thousand shows in a programmatic-style reach play on the long tail. The institutional mid-tier show (think network-branded weekly, no individual creator’s name attached) captures neither the top-creator deal nor the long-tail reach buy. The capital flowing into podcasting in 2026 is already shaped like a barbell.

The data is clean: the ends are growing, the middle is collapsing, and grind-it-out daily news is the hardest-hit segment of the middle.

It isn’t really about length

Here’s the tell that the length framing is wrong: middle-length content is thriving — but only when it’s owned by an individual.

Independent newsletter writers in the mid-length range are reaching audiences institutional outlets can no longer touch. Casey Newton at Platformer. Ben Thompson at Stratechery. Lenny Rachitsky for product. Heather Cox Richardson for politics. Different platforms, different verticals, same shape. YouTube essays in the 30-to-60-minute range are a working business model. LinkedIn long-form lands ideas every day, but only the posts signed by a human readers already trust.

What’s collapsing isn’t mid-length. It’s institutional mid-length. The weekly magazine. The trade-pub feature. The Forbes profile. The WSJ business-section piece. The press release. Every format whose distribution depended on the institution’s brand carrying the byline.

The real axis is the trust contract.

Shortform works because there is no trust contract. You bail in eight seconds if you don’t like it. The cost of being wrong is zero. The platform delivers you a stranger and you spend half a minute deciding whether they’re worth a follow.

Longform works because the trust contract is already paid. You don’t listen to a three-hour Dwarkesh interview unless you’ve already decided he’s worth three hours. The contract is signed before you press play.

The middle used to be held up by institutional trust as the distribution mechanism. A New York Times feature was an 800-word article you read because the Times selected it for you. The brand was the contract. That contract has frayed for most institutions and broken for many. Without it, mid-length content has no entry mechanism: too long for the algorithmic feed, too short to earn parasocial commitment, anchored to an outlet you no longer have a trusted relationship with in the same way, if at all.

Creators in the middle bring an individual trust contract that travels with them. Institutions in the middle had a brand contract that is collapsing in real time. A third of U.S. consumers now report a stronger personal connection to social media creators than to TV personalities or actors, per Deloitte’s 2026 Digital Media Trends. The barbell distribution is what it looks like when the institutional middle disappears and only the creator-shaped survivors remain.

Culture and discourse split

The other thing my tossed-off joke gets right: the two ends play different roles.

Shortform dominates culture. Memes, references, vibes, the shared atmospheric layer of what the people in your life are aware of. If a CEO gets dragged on TikTok this week, your aunt will know about it on Sunday. Shortform shapes the topic.

Longform shapes discourse. The Rogan-Dwarkesh-Lex axis (whatever you think of any of them) is where ideas get tested at length among the people whose opinions move other opinions. A senator listens to All-In on the treadmill. A founder hears a frame on Acquired and repeats it in their board meeting. Three hours of careful conversation moves the frame; thirty seconds of that same conversation move the meme.

The middle used to do both, though. A great Atlantic feature shaped discourse on a topic and generated cocktail-party references for six months. Magazine longreads were the format that bridged the two functions. That function has split. Shortform owns the cocktail party. Longform owns the boardroom. The middle owns neither.

Barbell markets in everything

The content barbell isn’t an outlier. It’s the same pattern playing out in market after American market.

Retail bifurcated into luxury and dollar-store, and the middle — Macy’s, JCPenney, Sears, Bed Bath & Beyond — is a graveyard. Hollywood mostly stopped making the $15-to-$65-million mid-budget film: that range fell from 36% of all theatrical releases in the late 1990s to roughly 5% by the late 2010s. Investment management has consolidated into mega-passive index funds at one end and alternatives at the other; from 2016 through 2025, passive funds pulled in $6.4 trillion of net new money while actively managed funds bled $2.4 trillion. Mid-tier banking had its 2023 — Silicon Valley Bank, Signature, First Republic — while the megabanks and the neobanks grew on either side around it.

MIT economist David Autor has been documenting the same hollowing in the American labor market for two decades: high-skill and low-skill work both expanding while middle-skill routine jobs shrink.

The pattern is recognizable enough now that you should expect it before you observe it: when the mechanics of distribution change in a market, the institutional middle is the first thing to vanish. Content is just the latest entry on a list that’s been getting longer.

How comms must adapt

Walk me into any senior comms team’s quarterly board deck right now and you’ll see placements that look exactly like what we celebrated as wins a decade ago. The placements look the same. The denominator has moved.

The dying asset class in comms is institutional middle-length placement. The trade-pub byline. The press release picked up in three industry outlets, the Forbes contributor post, the 800-word regional op-ed, the mid-tier magazine profile.

These are the formats every comms team is still measuring, optimizing for, and reporting on because the agency tools that exist were built when these placements were the whole game. Cision and Muck Rack still count them. The Earned Media Value calculator still spits out numbers. Your agency’s monthly report still leads with them.

The dashboards are flattering you. The reach in those outlets has already left. The trust has already left. The number in your earned-media-value column is being measured against a denominator nobody is paying attention to anymore.

The barbell strategy for comms is to give up the middle, or only play in it as far as it enhances the other ends of the barbell.

Compete for cultural attention at the short end. Thirty-second clips designed to travel as native content, not as repurposed press footage. Your CEO into the formats and rhythms of TikTok and Reels and Shorts, or creators with their own audiences who can carry your story there. The metric is not impressions; it’s whether your client’s customers’ kids reference it at dinner.

Compete for discourse at the long end. Your principals into the long podcasts and the trusted newsletters where the discourse-shaping cohort actually pays attention. Not the trade-pub roundtable. The Stratechery interview. The Dwarkesh sit-down, if the principal can survive it.

Each of these requires giving up something the comms industry has institutionalized. The short end requires letting go of message control. Clips travel because creators add their own framing, and most companies can’t tolerate that. The long end requires putting an executive in a chair for two hours of unfiltered conversation, which terrifies general counsels and corporate communicators trained on talking points.

The middle was where comms could control the message while maximizing trust. The barbell ends require letting go.

Brian Armstrong sent Coinbase staff an email Tuesday telling them the company was cutting roughly 14% of headcount, partly because AI efficiencies had changed what the company needed to do. He is not the first CEO to make that call this year. He will not be the last.

There is a paragraph that shows up in nearly every one of these messages. Some version of: AI is changing the way we work. It is usually followed by a couple of examples: a team shipping faster, a function consolidating, a pilot that surprised everyone. The examples are real; they’re not inventing these things.

But almost every time, there is one piece of evidence missing. The CEO never tells you what AI has changed about their own job, their own habits and ways of working. That’s the reason this genre of CEO communications tends to hit as hollow. It presents as a classic “do as I say, not as I do” situation: these are great tools, for you.

The audience that matters most here is the remaining employees — the people who just watched colleagues clear their desks under the banner of AI efficiency, and are now being told to internalize the new pace. They are not stupid. They are doing exactly the math you would expect them to do: if this is so important that we just lost a seventh of the company, what is it changing about you?

When the answer is silence (or worse, abstraction) the message lands hollow. You are asking them to absorb a transformation you have not visibly absorbed yourself. That is the oldest authenticity gap in management. Putting AI on the marquee does not make it new.

That is where most CEO AI comms sits right now. The set is dressed, the cast is hitting marks, but you can tell the kitchen has never been used.1 The audiences always can, though.

So I went looking for the opposite.

I spent parts of this week trying to find the substantive first-person accounts of tech CEOs2 walking through how AI has actually changed their own week. The exercise was instructive, mostly because of what it returned.

The most-shared CEO AI memo of the last year, Tobi Lütke’s “reflexive AI usage” mandate at Shopify, tells the team that AI fluency is now a performance criterion and that no headcount request will be approved unless the requester proves the work cannot be done with a model first. It is muscular and unambiguous. It is also entirely about what other people must do. Lütke does not describe what he himself does, anywhere in the document.

The most-quoted CEO AI claim of last year — Marc Benioff announcing on the Logan Bartlett Show that AI now does “30% to 50%” of engineering, coding, and support work at Salesforce — is precisely the kind of macro number a layoff letter can be hung on. It contains no account of which 30% to 50% of Benioff’s time has changed.

The closest thing I found to an actual first-person workflow account was Jensen Huang last July on Fareed Zakaria GPS talking about querying multiple AIs in parallel and having them critique each other’s answers, like asking three doctors for opinions. He’s also said he uses chatbots for first drafts. That is real. It is also a sound bite, not really a structural shift.

The reported, workflow-specific account from a public-company CEO, the version that would let an employee actually feel like their leader is in this shift with them, has, as far as I can tell, not been written.3 But that also makes it a huge communications opportunity, internally and externally, for CEOs with concrete examples.

I had a version of this conversation with a client a couple months ago. The public-company CEO wanted more visibility in the AI-and-leadership discourse. The instinct was thought leadership: an op-ed, a podcast, a keynote, a thread on what AI means for the industry. My counsel: AI opinions are cheap. AI building and proof is novel and notable. Show how your own week has changed. Show the workflows you have broken and rebuilt. Show the things you can now do that you could not do six months ago, not as a flex, as evidence.

That is the part the Armstrong-style emails skip, and it is the part that would do the most work for them. A paragraph in those letters about “here is how my own job has changed, here is what I have stopped doing, here is what I now do that I could not,” would be worth more than every “AI is core to our future” sentence put together. It would also be the thing that gives the survivors permission to actually move, because somebody at the top did it first.

I’m not picking on Brian here, or not trying to. He just happens to be the CEO who sent this type of message this week. In fact, he is a real engineer-founder not that far removed from the non-CEO version of himself, the one who was writing code at Airbnb. The probability that he is not using AI heavily, right now, in interesting ways, is roughly zero.

Which is what makes the silence in the email so striking. This is a CEO who gets it, probably uses it extensively, and still wrote a 14% layoff letter that gives you no evidence of either. If you have ever managed people, you know what that reads as.

For CEOs about to make AI-driven workforce decisions (or more likely, the comms teams writing the letter on their behalf), there is no rhetorical workaround here. If you want the message to land as credible, you have to show you are doing as you say just as much as you are telling everyone else their lives are being transformed.

Otherwise the email is not a strategy. It is an anthropology paper about a company that happens to be yours.

Like much of tech, I’ve been obsessively monitoring the posts and liveblogs of the courtroom developments in Musk v. Altman et al. It’s ignited some flashbacks in me from circa 2012, when I was running point on comms for Google around Oracle v. Google, tech’s last big trial of the century.

It’s too early in the trial to compile anything approaching overarching learnings or teachable moments, and the characters involved are truly sui generis in ways that break easy extrapolation into unified theories about How CEOs Should Handle Trial Comms.

But here’s what I’ve observed so far, in no particular order.

1. There’s a vast asymmetry between the two parties. Elon has nothing to lose and everything to gain. Sam et al are in the opposite position. That means Elon can take many more risks with trial and comms strategies, pressing the line of what will piss off the judge.

2. It’s notable that Elon’s lead attorney is Marc Toberoff, a Hollywood IP litigator introduced to him by best bud Ari Emanuel. That kind of says everything about how Team Elon is approaching this: not as a contract case, but as a battle over the rightful ownership over something iconic in culture.

3. Trials are messaging exercises as much as legal or evidentiary ones. Each party should be able to express their theory of the case in one sentence. Elon has a wonderfully succinct message: “It’s not OK to steal a charity.” As far as I can tell from reports of the proceedings, Sam et al don’t really have as powerful a line? (A free bad one: “If Elon’s a nitwit, you must acquit.”)

4. Gotta hand it to him: as a comms tactic, Elon’s amplification of the New Yorker profile of Sam was inspired and basically cost him nothing. He’s just taking dollars from one pocket and putting them in the other. I’ve also observed a ramp-up in Starlink ads as well, so the house ad campaigns are firing on all cylinders across his empire.

5. OpenAI’s had this trial messaging/rapid response page up on their site for a while as you can see by the entry dates, but they didn’t update it at all in the month before the trial, as far as I can tell. It did a serviceable job of surfacing things in/from discovery, but it’s MIA now as the trial plays out.

6. Wachtell. Are we sure they’re good?1 At this kind of case, I mean. Trial comms is not the same craft as defending a $50 billion M&A deal.

7. The trial in the court of public opinion is largely settled by the discovery process; the trial either affirms that opinion or (if things go off the rails) disproves it. In this case, we’ve been sitting with the discovery docs for about two years, and nothing that’s happened has really changed any minds.

8. Hey execs: maybe don’t keep diaries? Relatedly, all these constant-ambient-listening AI personal devices are going to be an evidentiary gold mine sooner than later.

9. Speaking of discovery, you’d think after all the brutal and embarrassing lawsuit discovery processes the Valley has seen over the years, tech execs would learn to use the Phone part of their phones to discuss sensitive matters. Maybe this time it’ll stick.

10. We’ve yet to have a really great meme from the trial, either a super-viral answer in testimony, judge admonishment, or even courtroom sketch artist rendering a la Tom Brady or SBF. It’s going to happen, though. (Where’s the prediction market for that?)

11. Along those lines, one of the parties (or more plausibly one of their emissaries) should hire their own courtroom artist to sit in the gallery and produce meme-worthy illustrations. Fill the visual vacuum and do it through your own lens. It’d probably test the gag-order line, but it’d be fun to see someone try.

12. Does anyone else remember how E! produced a daily dramatized version of the OJ Simpson civil trial because the judge didn’t allow cameras in the courtroom?2 It’s a shame TBPN’s owned by one of the parties, because I’d kill for a nightly or even weekly dramatization of Elon on the stand and they’d be the perfect place for it.

13. Absent that, go get those weird Taiwanese animated news report folks for the trial. That’s just some free content alpha for tech publications right here.

14. The VC Twitter silence around this trial is deafening. If it were any other two principals, it’d be a field day, but no one wants to piss off either Elon or Sam in the course of engagement farming.

15. Sam can’t win the trial in the court of public opinion. He can only lose it less. Elon can’t lose. He can only win it louder. Plan accordingly.

DC feels like a far-off land to most of tech, even to most of tech comms. But it has become dramatically more important during the second Trump presidency, with no sign of that abating.

Crypto and AI super PACs are getting their first real test in the Illinois and Texas primaries after sweeping 2024. The AI preemption fight is live on the Hill and in statehouses at the same time, with no Biden-era executive order left to anchor the federal position. The U.S. is nearly two months into a shooting war in Iran. And underneath all of it, the posture a tech company takes toward Washington this quarter determines what leverage it has in Washington next year.

But the legibility of Washington is hard if you are not enmeshed in it on a daily basis. The cadence, the personalities, the procedural levers, the real-versus-performative distinctions, none of it reads cleanly from the outside. And underneath all of it, the posture a tech company takes toward Washington this quarter determines what leverage it has in Washington next year. The part you can’t see from San Francisco is the part that actually moves.

So I called Nu Wexler. Nu worked on policy comms at Twitter, Meta, and Google, and was a longtime policy hand in Congress. He now has his own DC-based consultancy Four Corners Public Affairs. I've known him since our Twitter days, when even VICE hailed him as the best policy comms person in the business. When I want to understand what Washington is actually thinking right now, not what DC Twitter is performing, he's the first call I make. What follows is our conversation, edited for length and clarity.

The meta-takeaway I left with: the most expensive mistake a tech company can make about Washington is to confuse what is said for what is true. The Times reporter belittled at a press conference is what is said. The senior official taking her call on background is what is true. That gap is where policy actually happens. It’s also the gap that is hardest to see from the Valley.

Jim: When you talk to in-house tech policy leads, what are they having the hardest time getting their non-DC colleagues back at HQ to take seriously about Washington right now?

Nu: The biggest challenge for tech companies is navigating Trump and the political chaos associated with him. How closely do companies want to work with him? What are the reputational risks? For some companies, it’s all or nothing. They see 2026 as the last year to get anything done because it’s going to be very hard to pass their bills through a Democratic Congress. The smarter companies are trying to inch back to the center and rebuild bridges for when Democrats control Congress.

Jim: What does “inching back to the center” actually look like?

Nu: It’s a political calculation first. Money moving to Democratic candidates and potential committee chairs. Getting plugged back into center and center-left policy communities, not just The Heritage Foundation. More events with Democrats on the Hill. Covering both sides.

Jim: For companies whose CEOs aren’t all-in on Trump — the median tech CEO who isn’t politically aligned either way — what’s your number-one piece of counsel right now?

Nu: Make sure you have relationships on both sides of the aisle, so you’re covered after the election. Tone down the public praise of Trump. Consider talking to a broader set of media outlets. This is the high watermark for conservative media because so many people are trying to go on Fox or Newsmax to get Trump’s attention. You don’t have to do what everyone else is doing.

Jim: What’s the state of media consumption at the policymaker level? Not the unwashed masses — the people with their hands on the levers.

Nu: The Trump administration has worked hard to elevate conservative media outlets and influencers, giving them access to the White House and Pentagon briefing rooms. Simultaneously, they’ve tried to freeze out mainstream, established outlets. If the New York Times or CNN asks a question at a press conference, whether it’s Trump, Hegseth, or Patel, they’ll spend ten seconds belittling the reporter before maybe answering.

Jim: But that’s cheap heat for the base, right? Are Republican elites still influenced by the outlets they publicly scorn?

Nu: Oh, absolutely. That’s why the West Wing senior staff sat for Vanity Fair portraits. That’s why Trump still takes Maggie Haberman’s calls. The reporters he actually calls tend to be from the regular mainstream outlets that conservatives profess to hate. They know those outlets still shape media narratives. This Saturday is the White House Correspondents Dinner, and senior administration officials will be sitting at tables hosted by the Post, the Times, ABC, PBS, all the outlets they claim to despise.

Jim: Crypto is having a down moment as a market, but as a political force, it still carries a lot of water. I saw the latest Fairshake fundraising numbers this week — $180 million just for the midterms. Even if crypto isn’t the cool-kid industry in the Valley, in DC it’s still a top dog.

Nu: It’s because of the Fairshake war chest. Members of Congress may support crypto, oppose it, or be indifferent, but they’re all afraid of negative TV ads.

Jim: Which raises a question about the limits of that approach.

Nu: Right. If your industry is feared but not liked, what does that get you? It can help you block legislation. Does it help you pass legislation? I don’t know. Fairshake has done a good job getting candidates to support crypto bills or at least hold their fire. But passing legislation requires bipartisan support. Their tactics have leaned heavily on Democratic primaries, running ads that aren’t about crypto — they’re about other issues that boost or pull down candidates. That doesn’t do much for popular opinion on crypto. If you look at the early ‘26 primaries in Illinois and Texas, the crypto and AI super PACs are batting about .500.

Jim: Whereas they basically swept in 2024.

Nu: That was a Republican wave election, and they were careful about the candidates they targeted. A potential Democratic wave in ‘26 might be tougher.

Jim: On AI policy, the public polling looks contradictory. Everyone says they want guardrails. Everyone opposes preemption in their own backyard. What are you seeing?

Nu: Large majorities support AI safety and think we need a federal standard. Ask them about state preemption specifically, in their own state, and they oppose it. So they want both: state regulation and federal preemption. The media frame tends to be Bernie and AOC versus Trump, because that fits the familiar political narrative. But the pro-safety coalition is more bipartisan than people think. If you read local coverage of data center fights, it skews more conservative. A lot of data centers are in rural, Republican districts. Land use is a conservative sticking point.

Jim: And the super PACs won’t tell us much about where the public actually lands.

Nu: No, because they don’t run ads on AI. Leading the Future and the crypto PACs ran ads about immigration and inflation last cycle. Healthcare will probably dominate ‘26. That’s perfectly legal and fine, but it means you cannot look at the midterms as a referendum on AI.

Jim: What’s actual AI usage like inside DC? Does it break down along party lines?

Nu: Washington lags Silicon Valley on day-to-day usage, full stop. The way you’ve written about your own setup in Person Familiar, it’s different from how most of my friends here operate. There are people here coming up with new ways to automate things and use AI for research. It’s happening. But it’s nowhere near as prominent as it is in your world out there.

Jim: And is there a partisan split in usage?

Nu: In campaigns, Republicans have been faster to adopt AI, particularly generative AI. Democrats are still wary. Deepfakes, AI-generated ads, Republicans have had very few qualms about using them. Democrats are very careful to avoid it.

Jim: Outside the campaign world?

Nu: The rest of professional DC is looking for ways to use it. Still a smaller share of the workflow than in the Valley, but the curiosity is there.

Jim: Defense tech has taken a front seat narrative-wise the last year and a half. Alex Karp’s vociferousness, Palmer Luckey at Anduril. What are they doing that the rest of tech should be paying attention to?

Nu: They’ve capitalized on America First sentiment. They’re not just positioning their technology as effective tools —

Jim: They’re wrapping it in the flag.

Nu: Exactly. And they’ve done it in a way that other tech companies previously couldn’t. Project Maven is the obvious counterexample. But Anduril from the start said, “We’re a defense products company.” They’re not a search engine or a social media company. That attracts a workforce that isn’t going to protest executive decisions internally. Big Tech can’t just copy the posture. They spent 20 years building the opposite workforce.

Jim: What are the policy headwinds the Iran war is creating for tech?

Nu: The big surprise is that tech infrastructure in the Middle East is now a top target. When companies started talking to the Gulf states, especially Saudi Arabia, about data center infrastructure, I don’t think they imagined getting targeted by Iranian drones. That’s an additional vulnerability as they look to expand in the region.

Jim: A threat vector that Meta or Google security teams weren’t planning for.

Nu: The pitch from the sovereign wealth funds was: we’re in a time of peace and stability, we have capital to invest, you have customers in the region, don’t worry about our history. That’s not true at the moment.

Jim: Hypothetical. I’m a head of comms, and my CEO wants to crack the DC market. We don’t want to go full MAGA. Don’t want to go anti-MAGA either. What’s the playbook?

Nu: Build a campaign with bipartisan appeal, so you’re covered in either midterm outcome. Practically: build out a Washington office with Republican and Democratic staffers. Hill meetings on both sides. White House and Pentagon outreach — and remember, a lot of the Pentagon is genuinely bipartisan. Working with DoD isn’t MAGA. Balance your media outreach across outlets that cover the left and right. Spread your sponsorship dollars evenly. Same with think tanks.

Jim: How does someone outside DC build the actual muscle of reading DC — not hire a lobbyist, not subscribe to more newsletters, but develop a muscle?

Nu: Come visit. Meet staffers. Meet reporters. Get a feel for the rhythm. A lot of the quirks of this place — the congressional schedule, staffer culture, where people actually conduct business outside the House and Senate floor — only make sense once you’ve spent time here. Then hire for expertise over relationships. If you go through the lobbying roster for a lot of large tech companies right now, you can almost pick out the firms that were hired for access versus expertise. Access hires are expensive, and you have to re-staff every four years. Expertise lasts.

Jim: Parting advice for the Person Familiar reader sitting outside DC?

Nu: Tech used to be very bipartisan. Companies used to announce policy hirings in tandem: a Republican and a Democrat. Noah’s Ark. We’ve gotten away from that, especially in ‘25. The industry would be wise to return to it. You can go all in on Trump and get executive orders, but those aren’t durable. Congressional legislation is. It gives companies certainty. It lets you plan. Right now, a lot of the world could change next year.

The single most important number in AI right now has nothing to do with benchmarks, parameters, revenue, or compute. That number is 99.

According to a Data for Progress survey from February, voters who rarely or never use AI view the technology unfavorably by a 42-point margin. Voters who use it at least once a day? Favorable by 57 points.

A 99-point swing.

We all know it’s not just one poll. Navigator Research and Pew both found the same pattern: the groups who view AI most favorably are the groups who use it most. The Stanford HAI 2026 AI Index, released Monday, found a 50-point gap between AI experts and the general public on AI’s impact on jobs.

This isn’t new ground for readers of this newsletter. As I wrote earlier this year, the conventional response from the AI industry has been to treat this as an education problem. If people just understood the technology better, they’d come around. More blog posts. More explainer videos.

But the data doesn’t say people need to understand AI better. It’s telling us they need to touch it. They need to use it for something that matters to them, not in the abstract, but In their actual lives. And right now, the industry is failing spectacularly at making that happen for the vast majority of Americans.

The original corporate experience lab

When Disneyland opened on July 17, 1955, Tomorrowland was, by Walt Disney’s own admission, a bit of a mess.1 It was the last land to be finished, budget cuts had gutted the original plans, and what remained was, basically, a corporate showcase. Monsanto sponsored the Hall of Chemistry. Kaiser Aluminum had the Hall of Aluminum Fame. Richfield Oil backed Autopia. TWA put its name on Rocket to the Moon. American Motors sponsored Circarama Theater. There was even a Bathroom of Tomorrow that was basically a giant ad for Crane Plumbing.

But despite how overtly branded it all was, people went and experienced it. They drove on Disney’s model of a limited-access freeway at Autopia 11 months before Eisenhower signed the Federal-Aid Highway Act. They walked through Monsanto’s House of the Future and saw microwave ovens most Americans wouldn’t own for another two decades, wall-mounted televisions, and picture phones. They stood inside Circarama, an 11-camera 360-degree theater that was effectively a VR room 60 years before consumer VR. They took a simulated trip to the moon 14 years before Apollo 11.

And then Walt did it again. For the 1964 New York World’s Fair, he partnered with Ford, General Electric, Pepsi-Cola, and the state of Illinois to create four major attractions. GE funded the Carousel of Progress, a rotating theater showing how electricity had transformed American domestic life through the decades.2 Ford commissioned the Magic Skyway.

The exhibits were so popular that they boosted their sponsors’ sales, and all four eventually migrated to Disney parks. The fair itself drew 51 million visitors across its two seasons, roughly the same attendance Disneyland did in its first decade.

The app is not enough

This wasn’t quite advertising, and it wasn’t quite education. It was experience design at a scale that changed how millions of people felt about the future. And it worked because Disney understood something that the AI industry hasn’t yet figured out: you don’t convince people the future is good by telling them. You let them live in it for twenty minutes.

For the past two decades of our internet-dominated public lives, the answer has been: here’s an app, go figure it out. 56% of Americans already use AI tools, according to Brookings, and for the ones who’ve made the leap using these tools to write, plan, or debug, it actually is transformative. The polling proves it.

But pulling your phone out of your pocket is not an interruptive experience. It requires you to have already decided AI is worth your time, already overcome the cultural headwinds, and figured out a specific use case on your own. That’s asking a lot of people who, by a 23-point margin, think the risks of AI outweigh the benefits.

Google’s Super Bowl ad this year was the closest anyone has come to getting this right. A mom and her kid, anxious about moving, using Gemini to visualize what the empty rooms would look like with their stuff in them. Pulling color palettes from family photos. No parameters. No mention of the model. The ad barely said the word “Gemini.” It was entirely about a job to be done, to steal the Clayton Christensen framework, that has nothing to do with AI and everything to do with making a scary life transition feel manageable.

But an ad is still an ad. Sixty seconds of watching someone else use AI is not the same as using it yourself.

What Tomorrowland would look like today

If I were at OpenAI, Anthropic, or Google, I’d be obsessing over this question: how do you create physical, experiential encounters with AI that meet people where they already are?

Not “come to our AI experience center.” Not a tech demo at TED. Something closer to what Disney and his corporate partners did: experiences about something people already care about, that involve AI without being about AI.

Go looking for a real, physical AI encounter in the United States today — a place where a non-user can walk in and touch the technology — and you find Refik Anadol’s Unsupervised at MoMA, which drew enormous crowds for five months in 2022 and 2023, and a long-teased spin-off called Dataland in Los Angeles that still hasn’t opened. That’s art, not product. The closest thing on the product side is Meta AI running on Ray-Ban Meta glasses through LensCrafters. Frontier labs have no sustained physical consumer presence at all. They’ve outsourced civilian first-touch to hardware retailers they don’t control and one Refik Anadol.

Imagine a Home Depot aisle where you point at the part under your sink and get a three-step repair plan with the exact SKUs on this store’s shelves. A grocery store that proposes three dinners using what’s in your pantry plus two items on sale this week. A high school counselor’s office where the AI reads a transcript and produces a realistic reach-match-safety college list in the same meeting the family is already having. The common thread: the person is physically where the job happens, the AI does something that depends on the environment, and a trusted local intermediary stands between the user and the model.

Walt didn’t build Tomorrowland alone. He went to Monsanto, TWA, Kaiser Aluminum, and said: we’re going to build a place where people can experience the future, and you’re going to sponsor it. Those companies got that Disney could deliver an audience at a scale no corporate showroom ever could.

The AI companies have something Disney never did: an experience they can put in everyone’s hand, no animatronic house required. Put someone in front of a screen, tell them to point at their living room, and watch their face when the AI redesigns it in real time. What’s missing isn’t the raw material. It’s the intentional experience design that takes AI out of the phone and into someone’s life at a moment they didn’t expect.

The testing grounds still exist. U.S. public libraries log more than a billion in-person visits a year across 17,000 branches. The Smithsonian draws well over 15 million visitors a year across 21 museums—all free. State fairs move millions. Expo 2025 Osaka drew 29 million last year, the closest thing the modern world has to the 1964 New York World’s Fair, and no frontier AI lab showed up. None of these venues are being used seriously by the companies building the most important technology of the decade.

The precedent that matters most is the one staring the industry in the face. Starting in 1997, the Gates Foundation put internet-connected PCs in more than 11,000 American libraries, which is how a very large number of Americans first touched the web.3

OpenAI has ChatGPT Edu. Anthropic has Claude for Education. Google has Google for Education. These are basically licensing programs. They are useful. They are not encounters.

Every AI company is spending untold sums on content marketing, developer relations, and ads. That works for the audience that already gets it. For the other 74% of Americans who don’t, information isn’t the bottleneck. Experience is.

No amount of content marketing will close a 99-point opinion gap. That gap closes one person at a time, the moment they use AI for something that actually matters to them and think: Oh, I get it.

OpenAI acquired TBPN last week, the founder-hosted daily tech talk show, with assurances of editorial independence. It’s the latest expression of an instinct that hits every company eventually: when you get big enough and rich enough, you want to own the media channels that surround you.

It’s logical. It’s rational. And it is almost always the wrong play. In fact, the most successful marketing and communications exercise of this century worked in exactly the opposite direction.

Surviving to Thriving

When Liberty Media1 partnered with Netflix in 2018 on what would become Formula 1: Drive to Survive, they did something that would make most corporate communications teams physically ill: they gave production company Box to Box Films editorial control, including final cut.2

The producers could tell whatever story they found. Team principals behaving like tyrants and swearing like sailors. Driver feuds. A team plunged into bankruptcy administration mid-season by a group of creditors, which included one of their own drivers. A team forced to fire its Russian driver and strip its title sponsor’s name off the car after Russia invaded Ukraine, its owner later investigated for sanctions violations. All of it, on screen, for millions of people who’d never watched a grand prix.

This is the precise opposite of how virtually every other sports documentary property works. When LeBron produces a film about LeBron, or a tech CEO commissions a documentary about their founding journey, the subject holds final cut. And what gets systematically removed? Tension, conflict, and surprise. The exact ingredients that make anything worth watching. Drive to Survive has all of them.

The show debuted in 2019 and became a phenomenon: the No. 1 title on Netflix in 33 countries at its peak, averaging nearly 17 million views per episode by its fifth season. It’s run for eight seasons so far and spawned an entire genre of Netflix sports docuseries, all chasing the formula Drive to Survive invented.3

The response produced the most remarkable growth story in modern media. ESPN’s annual U.S. rights payment went from roughly $5 million to $75–90 million. This year, Apple took over at $150 million a year, a 30-fold increase from where the sport started less than a decade ago. F1 now has 827 million fans globally, up 63% since 2018. The audience went from overwhelmingly old, male, and European to 42% women and 43% under 35. In the U.S., 39% of adults now identify as F1 fans.4 More than half of them cited Drive to Survive as a reason they started watching. Average team valuations went from roughly $500 million in 2019 to $3.4 billion today. Even Haas, a perpetual midfielder, is worth $1.7 billion.

Not all of this is attributable to Drive to Survive. Liberty Media made smart decisions across the board: cost caps, new race formats, US market expansion. And F1 itself is a formidable media operation: F1 TV and a YouTube channel with over 14 million subscribers. They’re very good at going direct. But Drive to Survive was and still is the gateway drug.

The marketing impact doesn’t stop there. Then-Oracle CMO Ariel Kelman has said the show drew him to F1 — and Oracle subsequently became Red Bull Racing’s title sponsor. Total team sponsorship revenue crossed $2 billion in 2024 and continues to climb. LVMH signed a ten-year global partnership with F1, pegged at $1 billion. Cadillac so badly wanted its brand connected to the sport that it paid $450 million just for the right to join the grid.

The real plot twist: Mercedes and Ferrari, the two most prestigious teams and legendary auto brands, both sat out the show’s first season. Mercedes had won five straight constructors’ championships. Ferrari is Ferrari.5 Why would you let cameras in without a veto pen? Within two seasons, Mercedes and Ferrari’s own sponsors were pressuring them to participate. The teams that played it safe got punished by their own partners.

Going Direct Boring

I’ve written before about the structural forces pushing companies toward owned media: the trust gap between business and press, the shrinking atomic unit of news consumption, the ever-widening ratio of PR professionals to reporters. Those forces continue unabated.

But the going direct shift solved a distribution problem without solving the quality problem. Companies now have platforms, tools, and audience access. What most of them refuse to develop is the willingness to tell stories that are actually interesting. Media properties within companies face structural headwinds that editorial independence clauses can’t fully address.

It’s not about anyone’s intentions. You don’t need editorial interference to change the dynamic. You just need a logo on the paycheck.

Consider Coinbase. In 2022, they released COIN: A Founder’s Story, a documentary about CEO Brian Armstrong and the company’s journey to going public. They commissioned the film, hired an Emmy-winning director, and put millions behind it.6 The production quality was fantastic. The reviews were not.

The Information‘s headline nailed it: “The Coinbase Story Is Worthy of Cinema. The Film It Made for Itself Isn’t.” And it is boring, which is a shame, because when the film veers into the human dynamics of the cofounder relationship, what building something that becomes massively successful actually does to people over time, there are flashes of something compelling. But those moments get drowned out by crypto explainers and corporate retelling.

There’s a version of owned media that works. Red Bull Media House has spent two decades producing thrilling and entertaining content. The Felix Baumgartner stratosphere jump drew more than 8 million concurrent viewers, one of the most-watched live events on YouTube. But notice what Red Bull’s best content is actually about: the athletes and the feats, never the drink. Red Bull is a patron, not the protagonist. A Medici with a metal can. The less the content is about you, the more it does for you.

I’ve diagnosed this pattern before as Main Character Syndrome: the tendency for companies to cast themselves as the hero of their own story and systematically remove anything that doesn’t support the narrative. The F1 case reveals the flipside. If you do insist on being the character, you have to be a fully-rounded character, warts and all. The villains, the feuds, the backstabbing team principals, and the drivers who hate each other aren’t bugs in Drive to Survive. They’re a feature.

All Gas, No Brakes

There’s a quote by Jason Isbell, one of the greatest living American songwriters, that’s stuck with me for years. Speaking to Variety in 2023 about his unflinching HBO documentary Running With Our Eyes Closed: “Either you make a documentary that you’re completely comfortable with, or you make one that’s worth watching. There’s not really a whole lot of in-between.”

If you want to be the protagonist of your own story but you’re not willing to show the parts that make you three-dimensional, you end up with COIN or any number of athlete vanity projects. Or, in a more pedestrian form, the carefully managed LinkedIn post from the CEO that 47 people liked because they work for him.

My point here isn’t about final cut so much as it’s about what you’re optimizing for. Most companies going direct are going direct with hagiography. They paid for the microphone with nothing interesting to say into it, because everything interesting got killed in discomfort, legal review, or the CEO’s “one small note.” They’re optimizing for control, but the best marketing optimizes for audience. Those two impulses are in direct tension, and almost every company resolves it the same way.

Drive to Survive generated an estimated $290 million in streaming revenue for Netflix and turned a sport most Americans couldn’t name three drivers in into one with 52 million U.S. fans. Not despite the lack of control, but because of it. Sometimes the biggest communications risk is playing it too safe.

The 2026 IPO season appears to still be on despite everything else in the world working against it. SpaceX is now on file confidentially for what will likely be the largest IPO ever. OpenAI is cutting side quests and getting its business into fighting shape while building CFO Sarah Friar’s public profile. Anthropic, Stripe, and Databricks might be joining the party too. Renaissance Capital estimates 200 to 230 IPOs in 2026, raising $40 to $60 billion.

So it’s time to start talking about the comms side of IPOs again. I have personal history here, having been on the team that took Twitter public. The playbook for companies was pretty simple then: don’t jump the gun, get institutional investors comfortable with your story and your management, have a clean listing day free of drama, smile as you ring the bell.

The information sphere around markets and business was relatively simple, too: CNBC and Bloomberg for TV, a handful of outlets plus wires for the business press, maybe a few trades. Retail investors were a rounding error, and their stock trades still cost money to execute.1

That was 13 years ago. The market and the media have transformed. But as far as I can tell from my conversations with those who work on and have been through recent IPOs, the playbook still hasn’t.

The Retail Revolution Isn’t Just Meme Stocks

Retail investors now regularly account for nearly 20% of daily U.S. equity trading volume, up from low single digits before COVID. On high-volume days, that goes up to roughly 40% of equity volume and up to 50% of options volume. During the first half of 2025, individual investors poured $1.3 billion per day into the markets, a 32.6% year-over-year increase, with record net inflows of $155.3 billion.

The ownership numbers are just as striking. The typical S&P 500 company has direct retail ownership in the low-to-mid twenties, percentage-wise. A lot of the biggest names in tech are well above that baseline. Apple at roughly 34%. Palantir: 35%. Tesla: 29%, which on roughly 3.2 billion shares outstanding means more than a billion shares in individual hands. Amazon: 25%.

The information ecosystem serving these investors has flipped entirely. FINRA’s 2024 investor survey found that YouTube is now the most-used social platform for investment information, and is relied on by 61% of investors under 35. r/WallStreetBets went from 100,000 members in 2016 to more than 13 million.

And there’s a generational tailwind that makes all of this look modest: approximately $120 trillion will transfer to millennials and Gen Z over the next 20 years. Retail participation could get much, much bigger.

Enter the Stock Stans

The most engaged retail investors don’t function like, sound like, or behave like “shareholders.” They’re more like online fandoms. This shift is behavioral and cultural.

I’m calling them Stock Stans.

These are individual investors whose relationship to a stock is identity, not just investment. They build their thesis around it, argue about it online, create content evangelizing it, recruit their friends into it, and treat attacks on the company like personal affronts. Think Taylor Swift’s Swifties or BTS’s ARMY, but with brokerage accounts. Organized, vocal, fiercely protective, and loyal through the rough patches in a way fair-weather followers never are.

“Bang-up job, Jim, you discovered meme stocks five years late,” you say. But while Stock Stans are certainly involved in meme-y tickers, what’s novel now is every major stock now has them.

Costco (~30% retail ownership) shareholders treat the stock the way they treat their Costco membership: as a lifestyle commitment. The customer-shareholder overlap is nearly total, the buy-the-dip conviction is fierce, and the community discusses earnings and hot dog prices with equal intensity.

During Disney’s 2024 proxy fight, 75% of its retail shareholders (~33% of the company) voted to support the board against Nelson Peltz. Retail proxy participation is typically dismal, but Disney’s individual holders showed up and were near-unanimous. That constituency existed because Disney is the kind of company people feel they belong to, not just own.

The phenomenon scales up from there. Palantir’s 2025 is the upside case. Wall Street said overvalued, but Palantir had spent years cultivating its retail base: Alex Karp’s unfiltered public persona, earnings calls that close with a direct address to individual investors, a mission-driven narrative (”strengthening the West”) that gives stans something to believe in, not just bet on. When institutional skepticism hit, the stans held, bought dips, and made the bull case on social media to an audience sell-side research could never reach. The stock surged more than 150%.

CoreWeave’s 2025 IPO shows what happens when you fail to account for the power of retail. Enthusiasm for the AI narrative drove the stock from a $40 IPO price to $187 by June. But CoreWeave had enthusiasm without narrative infrastructure: no executive social presence, no mission narrative beyond “GPU cloud,” no relationship with the retail investors buying its stock. When institutional concerns emerged (62% revenue concentration in a single customer, significant debt), retail had no framework to evaluate them and no reason to believe. The stock lost more than half its value from its peak.

Both companies faced institutional headwinds. One had spent years cultivating stans with conviction. The other had cheap heat it couldn’t sustain.

RoaringKitty‘s DNA got spliced with NYSE and NASDAQ’s, and now the evolutionary trait is everywhere, permanently. And I don’t think any companies heading into an IPO, save for SpaceX2, have the slightest idea how to harness it.

Updating the Playbook

Stock Stan communities will form around your IPO whether you build for them or not. They’re already assembling on Twitter, Reddit, Discord, and TikTok around every company in that pipeline. The only variable is whether you have any influence over the narrative they construct, and to what business end. Textbook communications challenge.

To be clear: nobody wants to be a meme stock. The opportunity is more specific and more durable than that: an informed base of committed individual shareholders who provide downside resilience in selloffs, amplification in the information sphere, and governance support when it counts. Not a mob. A constituency.

One company has actually figured this out, and unless you’re a complete corporate governance savant, you will never guess it. The paragon of progressive investor relations and corporate comms thinking is... ExxonMobil.

They’ve created a dedicated “Individual shareholders“ section as a top-level IR navigation item, with plain-language business explainers and introductory videos. They’ve also created a first-of-its-kind Voluntary Retail Voting Program in consultation with the SEC that lets individual shareholders pre-authorize their shares to be voted in line with board recommendations. An oil company built the retail investor infrastructure that the world’s most dynamic, forward-thinking economic sector hasn’t thought to build.

So why hasn’t anyone else?

The institutional pricing mechanism works. The roadshow exists for defensible reasons. Brunswick Group published a piece last month calling retail investors a “market force,” and they’re right. But the reckoning has happened at the thought leadership level. It hasn’t filtered down to the IPO process or the comms execution surrounding it. The gap isn’t the IPO event, but everything around it: the IR infrastructure, the narrative strategy, the post-listing engagement model. All still built for one audience.

Every structural incentive in the advisory ecosystem works against closing that gap. Investment bankers still get paid on institutional allocations. The standard IPO retail allocation remains roughly 10% of shares, even though retail already owns 30-60% of comparable companies post-IPO. Securities lawyers remain incentivized to minimize novelty. Communications advisors like Brunswick calcify around “best practices” from a decade ago (which, to be fair, were best practices a decade ago).

I audited the IR websites of more than 25 major public tech companies to see how deep the inertia runs. Not one has a page, a section, or even a paragraph designed for individual investors. Tesla, Palantir, Coinbase, Robinhood: companies with massive retail followings, or whose entire businesses depend on retail investors, all running the same institutional template built by the same two IR platform software vendors.3

A Forward-Thinking IPO Comms Approach

If you’re heading communications for a tech company approaching an IPO (or advising one), here’s what needs to change.

Establish retail-facing communications practices before the quiet period makes them impossible. This isn’t “your CEO should do business podcasts”. That’s general comms advice any firm would give you today. Retail-oriented communications for a still-private company means building specific practices that serve an audience with different information needs than institutional investors. Your CEO regularly explaining the business and its decisions in plain language on platforms where retail investors actually gather. A company content practice that makes the business intelligible to non-analysts—not thought leadership, but “here’s what we do and why it matters”—in terms a future retail shareholder can follow. Visual communication designed for screenshots and sharing, not just roadshow decks. Two-way engagement on the platforms that will become your Stock Stan communities.

Some of the smartest IPO candidates have already been building this muscle. Stripe publishes an annual letter disclosing some business metrics, but it’s mostly a Berkshire-style narrative-driven communication designed to be read by anyone. OpenAI’s CFO Sarah Friar has been publishing financial milestones on the company blog in plain language. Databricks disclosed crossing $4.8B ARR timed to its fundraise. These companies are establishing a pattern of voluntary, plain-language financial communication while still private. When the quiet period arrives, that pattern already exists.

Design your IPO materials for two audiences. Retail investors will read your S-1. The question is which parts they latch onto, and whether you’ve given them something to work with or left them to find the scariest-sounding risk factor on their own. Robinhood’s comms team didn’t choose for Reddit to fixate on the 80% payment-for-order-flow revenue disclosure. CoreWeave’s team didn’t choose for the 62% Microsoft concentration stat to become the bear case. Those were the most legible, surprising facts in the filing, and retail made them the story by default. Think about your materials through the lens of what’s most legible and shareable, and whether the narrative retail constructs from your filing is the one you’d choose.

Airbnb came close to getting this right. The prospectus summary outlined the company’s narrative arc, explained its reason for being, and laid out why hosts partner with them. But the rest of the S-1 was the standard perfunctory layout of the business in Wall Street terms. Write the business overview so it’s intelligible to someone who’ll never build a DCF model. Or even better than writing, illustrate it. Make growth charts that work on a phone screen. Give the stans something to go to work with. The SEC dictates a lot, but they don’t dictate that you be boring.

Broaden who the roadshow is for. The traditional roadshow is a series of private meetings with institutional investors. Retail investors, who will own a significant chunk of the company within months, have no real access to the story, the management team, or the narrative framework that informs institutional investment decisions. What they do get is a hastily produced equivalent of a public-access TV version of the roadshow with the CEO and CFO talking over institutional slides for 30 minutes, posted because the SEC says you more or less have to. The vendor ecosystem for this output markets a smooth process and on-time delivery, not breakthrough content. The quality bar is on the floor.4

A company that invested real creative energy here — a retail-facing version of the roadshow narrative designed for the person who’ll never sit in a Goldman conference room — would have zero competition. The story you tell institutional investors should be accessible to the people buying shares on Robinhood. The platform to deliver it already exists. Someone just has to actually try.

Build the IR infrastructure nobody else in tech has. A dedicated retail investor section on your IR site that treats them like first-class citizens, like ExxonMobil5. Not a transfer-agent FAQ, but a real, plain-language explanation of your business and results designed for the social-first environment where your retail shareholders actually live. And maintain it after listing. This can’t be an IPO-day stunt or token nod. Persistent infrastructure that treats retail investors as a constituency worth an ongoing conversation, not a checkbox.

And now a word for my securities lawyer friends: Put down your pitchforks. I can hear you already.

Reg FD. Selective disclosure. Quiet period. Gun-jumping. Real constraints. But the legal boundaries seem wider than most practitioners assume.6 Reg FD and the quiet period are two separate legal regimes that most comms professionals conflate. The JOBS Act and its 2019 extension loosened pre-IPO communications significantly. The SEC’s 2013 Netflix investigation established social media as a valid Reg FD disclosure channel. Rule 421(b) requires plain-English prospectuses. The line is clear: building general corporate reputation is permitted; conditioning the market for a specific offering is not.

The standard guidance from firms like Wilson Sonsini is “do not begin new communications practices” during the IPO process. Sound advice, and it creates an imperative most companies miss: establish retail-facing practices well before the IPO is on the horizon, so they’re a documented pattern of behavior, not a novel initiative your lawyers have to evaluate during the process. The legal framework doesn’t argue against building for retail. It argues for building for retail early. (It’s worth noting what firms like Wilson Sonsini haven’t published: any guidance on how retail’s growth changes the IPO communications calculus. The most-cited academic treatment of the retail revolution, by Penn Law’s Jill Fisch, argues that the regulatory posture should be facilitation, not restriction. The law firms haven’t caught up to the law professors, which is delicious irony.)

No major tech company does any of this today. It’s an open goal.

Everything I’ve said above is easier to state from my outside position. I’m not Sarah Friar trying to land the plane of a likely-trillion-dollar OpenAI IPO, with all the attendant pressure and responsibility that entails. I’m not running a sprawling global corporate comms advisory with non-tech clients who might get spooked by what the weirdos in Silicon Valley are trying.

But the biggest, most in-demand companies also have the most license to do things differently, and in doing so set new standards that obviate a generation of stale best practices. The stans are already assembling. The only question is who shows up to meet them.

And really, do you want to get out-innovated by an oil company?

Sam Altman and other AI leaders like to talk about a phenomenon called the capability overhang. It’s a shorthand for the gap between what these frontier LLM models can accomplish today and what people are actually doing with them. I’ve spent the last year consulting with comms teams on AI tooling alongside the usual work of narrative, positioning, and crisis, and I can confirm: in communications, the overhang is enormous.

Here’s what the state of the art looks like at most organizations right now. The company’s engineering or IT team has deployed a platform. ChatGPT, Claude, Gemini, a custom harness that lets people pick models by task. The comms team has access. They use it periodically. And what they use it for is, almost universally, some version of “smarter Google”. Paste in a draft, ask for revisions. Provide some background materials and ask for a first pass. Summarize this. Rephrase that. Conversational search with better prose on the back end.

The engineering teams knew immediately what to do with them. The design teams probably had ideas. The comms team got a login and a pat on the back.

Nobody has shown them what’s possible.

Users and Builders

I’ve written before about the difference between being a user of AI and being a builder with it. That distinction matters even more here than it did when I was talking about shipping silly interactive projects on a weekend.1

Every comms team I talk to is trying to become better users of AI. Better prompts, better workflows, a template library, maybe a series of lunch-and-learns. That’s the wrong frame.

The point is building systems: wiring together your knowledge, your workflows, your standards, and your tools into something that operates continuously, not something you just open in a browser tab when you need a first draft.

I know this because I built one.

I run a one-person strategic communications consultancy. No more than five concurrent clients, spanning from growth-stage private companies to Fortune 500 and everything in between. Over the past year, I’ve built what I call a self-driving comms operation: roughly 60 integrated components running on a backbone of Claude/Claude Code, Obsidian, Todoist, Granola, and a pile of connectors and scripts that would probably cause a normal person to back slowly out of the room.2

I use the word “operation” deliberately here. Not self-driving strategy. Not self-driving judgment. Not self-driving client relationships. The operations: prep, research, scheduling, monitoring, formatting, task routing, the thousand small acts of administrative hell that eat your days if you let them.

Let’s go through a normal day. At 5:30 a.m., a script scans my calendar and creates transit buffers with real drive times. At 6 a.m., an inbox sweep classifies overnight email by urgency and turns anything actionable into tasks. A morning briefing, assembled from dozens of feeds and tailored searches, lands on my phone before I wake up.

When I sit down, two commands set up the day. A morning sweep triages every open task, classifies each one as something AI can handle, something it can prep for me, or something that needs my brain, and dispatches parallel agents to start executing the approved items. Then a time-blocker pulls the remaining tasks, maps them against my calendar with real-time drive distances, and builds a schedule down to the five-minute buffer, complete with errand batching, gym slots, and rollover recommendations for anything that doesn’t fit.

Throughout the day, meeting transcripts get scanned for commitments I made, and tasks appear automatically with full context. At night, a process walks my entire knowledge base and weaves backlinks between related documents.

Then there’s the queue. Whenever I hit something I know Claude can handle (draft this follow-up, research this company, update this note, clean up this task list), I tag it #dothisclaude. Every hour, a job picks up tagged tasks, executes them against my full set of tools and context, and reports results to me via Telegram.

The work just... appears. I went from pulling work through a conversation to pushing tasks into a queue that resolves itself. That is a very different relationship to AI than opening a fresh chat window and, once again, explaining the entire backstory of a task you already explained three sessions ago.

All-in monthly cost of all this: a middling dinner for two in San Francisco.3

Does it actually help get things done? I had Claude audit my daily work throughput for the last six months, measured by tasks marked completed in Todoist, normalized for complexity and scope. The analysis showed a 2.5 to 3x increase from when I didn’t have this system in place to when I did.

And that’s just throughput. It doesn’t capture the four hours a day back for work that requires my brain. There are projects I’ve taken on since building this (outlining a book, building open-source tools, being much more diligent about getting Person Familiar out every week) that I simply would not have had the bandwidth to attempt before.

The work that defines our profession isn’t coverage reports. It’s stubbornly, unavoidably human: creating narrative tension, reading a room, managing situations with real people and real emotions, finding ways to do things nobody’s done before. AI tools are literally derivative: their outputs are derived from what came before. We’re in the business of new because new captures attention and moves hearts, minds, and markets.

So the focus on operations is deliberate. Automate the machinery so the people doing the work have time and space for the thinking, the creativity, and the strategy that no system can replicate. Operations matter enormously, but they’re the layer you can actually put on rails.

The Hard Part Wasn’t the Tech

Of course, this was easier for a solo practice. The knowledge lives in one head, the voice is one voice. I was the architect, the domain expert, and the end user simultaneously. But the lessons still translate directly.

The hard part was never the AI. The hard part was articulating what I used to do by feel. Why does this draft sound wrong? Why does this meeting prep feel incomplete? Why do I keep tightening this same kind of opening paragraph? Why does one calendar invite feel polished and another look like it was assembled by raccoons?

Every time I answered one of those questions explicitly, the system got better. It developed standards, checks, and rules. We refined its editing patterns and made them context-specific. The discipline wasn’t technical. It was self-knowledge.

That discipline is exactly the same whether you’re one person or fifty or five hundred. The institutional knowledge that makes a comms team excellent already lives inside the team. Your senior VP who can brief the CEO before a hostile reporter call without breaking a sweat. The media lead who reads a reporter’s tone and knows before the story runs whether it’ll be fair. That internal comms manager whose editing instincts are so good that everyone routes drafts through her before anything goes out.

That knowledge is the asset. That’s the work I’ve been doing with comms teams over the past year: not building the system for them, but helping them see their own operation clearly enough to build the right one.

This is also where I’ve seen the most common failure mode. Someone decides to build the system for the team. They interview everyone, map the workflows, disappear into a room, and emerge with a framework, a Notion workspace called “Comms OS,” and a workshop nobody asked for. Six weeks later, the team is doing the work the old way. The system that got built reflected how an outsider understood the team’s work, not how the team actually does it. The people inside the operation can feel that difference immediately. Systems built for teams collect dust. Systems built with teams compound.

And compounding is the thing. You codify one workflow, and you realize six others could work the same way. You structure one piece of institutional knowledge, and the whole context layer starts getting richer. The first time you help someone on a team build something, not use a tool but build a thing, the whole frame shifts. I’ve watched it happen enough times to know it’s reliable. That first build is the unlock, and everything after it moves faster.

It’s Time to Start

None of this requires starting with sixty components. The first build that usually matters most (and the one I’d recommend to any team trying this for the first time) is automated meeting processing. Connect your transcript tool and your task manager. After every call, the system pulls out commitments, updates the relevant files, and drafts the recap. An afternoon to set up, maybe two. Thirty to forty-five minutes saved from the first week.

That’s it. That’s the first rung. Once you have it, something shifts. The project files get richer every time a transcript is processed, which means every future meeting prep improves, which means the system starts earning its own keep. People stop asking “does this AI stuff actually do anything?” and start asking “what else can we put on rails?” Every recurring frustration is a spec for the next build.

Every C-suite in technology is pushing organizations to show results with AI. CEOs and CFOs at public companies need to speak with specificity about what AI has actually changed in their operations. And right now, almost no comms team has a great answer.

That gap is an opportunity, and it won’t last. The teams that build this now, thoughtfully, with their people rather than for them, will have what amounts to an unfair structural advantage that grows every week.

Your comms operation, whether in-house or at an agency, already works a certain way. There’s a rhythm: people check things, prep things, route things, update things, chase things down. Some of that work requires the full weight of their professional judgment. A lot of it doesn’t. Look at the parts that don’t.

That’s where this starts. Not with a transformation strategy or a vendor evaluation or a slide deck about the future of communications. With one workflow at a time that makes next Monday morning better than last Monday.

Jensen Huang walked onto the floor of San Jose’s SAP Center yesterday and held a capacity crowd’s attention for over two hours, no teleprompter, announcing $1 trillion in projected chip orders through 2027, a new rack architecture called Kyber, a prototype data center designed for space, and a live robotics demo starring Olaf from Frozen. He closed with singing robots and an animated lobster performing a campfire song.1

If you’re a communicator looking for actionable takeaways from all this, I can save you some time. Here’s one version of a playbook:

1. Be the CEO of the most important company in the world for the most important technology in the world right now.

2. Have cool jackets or some other signature piece of clothing.

3. Double your revenue estimates once or twice a year.

If you can be Jensen Huang and Nvidia, I highly recommend it. It seems to be going great and really fun.

But most of us and our executives can’t be Jensen and Nvidia, sadly. So if you’re studying yesterday’s GTC keynote looking for communications lessons (and you should be), what’s actually transferable? For me, it’s a specific technique he used that most companies could actually adapt, and that is quietly the most strategically savvy part of the entire two-hour performance.

To briefly head this off: yes, any time you talk about a live stage presentation by a tech exec, you’re implicitly judging it against Steve Jobs in the same way every rock band gets judged against The Beatles. Jobs understood the keynote as performance, not announcement, and so does Jensen. But Jobs sold clarity—the future simplified until you felt smart enough to buy it. Jensen sells complexity—the future rendered so technically dense that you need a guide through it, and he just spent two hours proving he’s the only person who sees the whole picture. Different trick.2

OK, moving on.

Category Coronation

Roughly two hours into the keynote, Jensen turned to OpenClaw, the open-source AI agent framework that’s taken the tech world by storm since January. Creator Peter Steinberger, who now works at OpenAI, was in the audience. Jensen called it “the most popular open source project in the history of humanity” and compared it to Linux, HTML, and Kubernetes, all foundational, era-defining protocols.

Then he said: “Every single company in the world today has to have an OpenClaw strategy.”

The CEO of a $4.5 trillion semiconductor company, at his own flagship event, used his stage to crown someone else’s project as the defining technology of a new era.3 He compared it to the technologies that built the entire fucking internet and said the entire enterprise world needs to reorganize around it.

That looks generous and visionary. It’s one of the most self-interested things he could do.

Every always-on autonomous agent is an inference call. Every inference call burns GPU cycles. Every CEO who walks out of that arena thinking “we need an always-on agent strategy” is a CEO who’s about to triple their inference compute budget. Jensen doesn’t care if you use OpenClaw or some other framework. He doesn’t care which models you run or whose API you call. He cares that you’re running persistent agents that consume compute 24/7 instead of intermittent prompt-response sessions.

“Every company needs an OpenClaw strategy” is Nvidia’s 2026 version of 1970s/1980s Microsoft’s mission of “a computer on every desk and in every home.”

This is a specific, nameable communications technique: category coronation as demand creation. You take something external (a technology, a movement, a shift in behavior) and you elevate it to the status of an inevitability. You don’t argue for your product. You argue for the world in which your product is essential. And once your audience accepts the paradigm shift, the downstream purchase becomes inevitable without ever needing to be argued for directly.

Jensen never said “buy more GPUs.” He just needed executives around the world to believe the age of autonomous agents had arrived. Gravity takes care of the rest.

Why Nobody Else Does This

The natural question is: if this works so well, why don’t more companies do it?

Partly it’s a confidence problem. Category coronation requires you to not talk about yourself for extended stretches, and most executives find that physically painful. Their boards want the product mentioned. Their sales teams want competitive comparisons. Their comms teams have been trained to measure success in share of voice and message pull-through. Spending five minutes of a keynote praising someone else’s open-source project that maybe about a couple million people worldwide have played with is, to put it mildly, not what the average VP of product marketing would recommend.

Partly it’s a structural problem. Most companies communicate in a sequence that feels logical but is actually backwards: product → features → market context. Here’s what we built. Here’s why it’s good. And then, if there’s time, a gesture at the broader shift that makes it relevant. Jensen inverts the entire thing: market context → paradigm shift → inevitability → (oh, and we happen to be the infrastructure underneath all of it). The product is never the subject of the sentence. The shift is the subject. The product is just... there. Quietly essential.

And partly it’s an earned-credibility problem. You could chalk this up to “well, Jensen can do this because he’s Jensen,” and that’s not entirely wrong. I’ve written before about attention strategies and whether you’ve earned the one you’re running. Jensen can pull off the Greatest Showman routine—the arena, the two-hour runtime, the Olaf cameo and the space data center teases—because the showmanship is built on delivered roadmaps and quarterly beats-and-raises.4 Strip away the leather jacket and the singing robots, and there’s still a $1 trillion order book. If Nvidia were missing shipments or Vera Rubin were vaporware, the keynote would feel like what I’ve called elsewhere vibe writing. All hat and no cattle.

But if you have the products and you have the results, you don’t need the leather jacket. The technique works at any scale, and the mechanics are the same.

The Three Moves

Start with the shift, not the product. What if the first five minutes of your CEO’s next keynote, blog post, or podcast appearance weren’t about your company at all? What if they were about a change in the world that your audience is already feeling but hasn’t quite named? Jensen opened not with Nvidia’s revenue but with the thesis that the token is the fundamental unit of a new computing paradigm. By the time he got to specific products, the audience had already bought the frame.

Crown something external. This is the part that feels counterintuitive, and it’s the part that makes the whole thing work. Find the technology, the movement, the behavioral shift that your product plugs into—and elevate that, not yourself. Jensen crowning OpenClaw as the Linux of the agentic era is structurally the same move as a cybersecurity company declaring “the zero-trust paradigm is now inevitable” or a fintech company saying “embedded finance is the new default.” You’re not selling. You’re declaring. And the declaration creates the demand.

Let the audience connect the dots. This is the hard part, and it’s where most companies flinch. If you’ve done the first two moves right—established the shift, crowned the external force—your audience is already thinking “okay, so who benefits from this?” The answer is you. But the moment you say it out loud, you break the spell. You go from prophet to salesman. Jensen’s discipline in never saying “buy GPUs” is the reason the whole thing lands. Most executives can’t resist drawing the line in crayon. Resist.

You could argue that category coronation only works when you’re the dominant infrastructure provider in a generational technology shift, and yeah, it helps. But the underlying structure—argue for the world, not the product; elevate something bigger than yourself; trust the audience to connect the dots—is available to anyone with a genuine thesis about why things are changing and the substance to back it up.

Jensen gets to be the showman because the cattle are real. But the showmanship isn’t the lesson. The lesson is that he never once, in two-plus hours, argued for Nvidia’s products. He argued for the inevitability of a world that runs on them.

When I started this newsletter, I said I was building an escape tunnel under the walls of the Thought Leadership Industrial Complex. Today we’re tunneling with dynamite, not shovels.

Ever since ChatGPT 3.5 set off an explosion of LLMs and other AI technology, communications agencies have been trying to figure out not just the consequences for their clients, but for their own businesses. Namely: what do we sell now? They needed new offerings to fit the new world.

Enter “generative engine optimization”—GEO—positioned as the successor to search engine optimization (SEO), the roughly 30-year-old practice of reverse-engineering search ranking signals to make an organization appear more prominently in results. GEO claims to do the same thing for LLMs that SEO did for search.

But it can’t. The people selling it should know it can’t. But they’re selling it anyway. And the only things getting optimized are their invoices.

Some critical disclosure before we begin: I was a senior executive at Edelman from 2020 to 2021, and until recently served as a senior advisor to Weber Shandwick. I ended that advisory relationship to avoid any conflicts of interest related to what I write here. My money is where my mouth is.

SEO Has Rules, GEO Has Vibes

As the internet and search took off in the mid-’90s to the early 2000s, the SEO industry sprang up around it much like towns sprang up around gold discoveries in the Old West.

SEO practitioners and Google have had a fractious relationship. Google et al would make changes, the SEO would grumble and adapt, and on it went. For all its bumpiness, the industry was built on a defensible premise: the system has rules, and we’ve figured out some of them. Google told you how it worked through published details about ranking signals. You could do things like build backlinks, stuff keywords into meta descriptions, and measure what happened. It was, and is, deterministic enough to reverse-engineer and legible enough to optimize.

LLMs don’t have ranking algorithms. They have statistical weights across billions of parameters, producing probabilistic language outputs. Ask an LLM the same question twice, and you’ll get different outputs. None of the frontier model companies can explain why their models cite what they cite. Anthropic’s own interpretability research has described the challenge of understanding how features steer model outputs as peering into a “black box.” None of this is secret.

And when LLMs do reach outside their own training data for answers, they’re not using some novel discovery mechanism. They’re querying traditional search engines: Bing, Brave, Google. The retrieval layer that GEO claims to have invented already exists. It’s called SEO.

So if the companies that built these systems are still publishing papers about trying to understand citation behavior, what exactly is a PR agency optimizing?

GEO’s Origin Story Is Already Crumbling

The entire GEO category traces back to a single academic paper: “GEO: Generative Engine Optimization,” out of Princeton and IIT Delhi. The paper’s headline claim, that “GEO can boost visibility by up to 40%”, has been repeated in every agency pitch deck, every trade article, and every retainer proposal that’s crossed a comms leader’s desk in the past year.

These materials blithely omit some important details.

The paper was submitted to ICLR 2024, one of AI’s most prestigious machine learning conferences, and then withdrawn. It was later published at KDD, a data mining conference—not a machine learning or NLP venue where the claims about LLM behavior would face the toughest scrutiny—but by then the “up to 40%” number had already been circulating for nine months via the arXiv preprint.

Plenty of time for the marketing machine to launder it into accepted fact.

The study mimicked a Bing-like workflow in which the LLM queries traditional search results first, meaning GEO depends on SEO. If you’re not already ranking in traditional search, you’re not getting cited by the generative engine. A detailed critical review found that all “optimizations” in the study were performed by AI, the keyword stuffing prompt (one of the tested “GEO strategies”) was omitted from the paper body and only discoverable in the source code, and the methodology has significant issues nobody in the industry pressure-tested because... the Princeton connection, I guess?

More recent academic work hasn’t been kinder. A subsequent study building on the Princeton framework notes that “current GEO practices are largely heuristic, relying on rules of thumb such as the use of quotations, authoritative tone, or FAQ-style structures” and that “existing metrics like the impression score do not translate directly to economic impact.”

An unreviewed study with significant methodological issues became the foundational citation for an entire service category, its headline number laundered through trade press and agency marketing until it hardened into accepted fact. It is not.

Three Studies, Three More Mortal Wounds

Let’s assume GEO were real, and there was a knowable, optimizable relationship between specific interventions and LLM citation behavior. You’d expect three things to be true: LLMs would cite sources reliably, the platforms would behave similarly enough to optimize for, and the interventions would be distinct from existing comms practice. In reality, none of those things is true.

LLMs hallucinate their own citations. A Nature Communications study published in April 2025, analyzing 58,000 statement-source pairs, found that 50–90% of LLM responses are not fully supported by the sources they cite. Even GPT-4o with web search — the best performer in the study — left approximately 30% of individual statements unsupported. Across the broader research literature, models fabricate 18–69% of their citations depending on the model and the domain. When researchers explicitly prompted ChatGPT to “only cite sources you can verify,” fabrication dropped from 47% to 41%. You are paying agencies to optimize your visibility in systems that cannot currently make reliable outside citations.

The platforms don’t agree on anything. Only 11% of domains get cited by both ChatGPT and Perplexity. ChatGPT without web browsing draws on parametric knowledge, e.g., whatever was in its training data. Perplexity runs real-time search against 200+ billion URLs. Google AI Overviews correlate with traditional SERP rankings. Claude uses Brave Search.

These aren’t variations on a theme. They’re fundamentally different architectures with different retrieval mechanisms, and the frontier model labs change those mechanisms without notice or documentation. Anyone selling “GEO strategy” is selling optimization for four different systems that work four different ways, and they can’t tell you how any of them decide what to cite.

The industry’s own data proves the service is redundant. This is the one that should end the conversation. Muck Rack’s “What Is AI Reading?“ analyzed over a million links cited by AI tools. The headline finding: 89% of AI citations come from earned media (since declining to 82% as OpenAI reduced Wikipedia reliance). Every GEO vendor cites this stat as proof that the category matters.

If 89% of AI citations come from earned media, then the driver of AI visibility is the same thing agencies already sell and have always sold. Muck Rack also found only 2% overlap between the journalists most pitched by brands and those most cited by AI engines. Their interpretation: “an adjustment to pitching practices could have a major impact on a brand’s GEO.” Translation: pitch better journalists. That’s just media relations.

These GEO merchants didn’t discover a new channel. They discovered that good comms works everywhere, including in LLM outputs, and slapped a new acronym on it.

Let’s Name Names

Let’s walk through how some of the comms industry’s most credible institutions are lending legitimacy to a service category that can’t demonstrate a causal mechanism and is undercut by research published by its own practitioners.

Edelman, the world’s largest independent PR firm, launched GEOsight in May 2025. Brian Buchwald, Edelman’s Global Chair of AI and Product, told the industry: “You can’t buy your way to the top of an AI-generated answer.” Finally, someone in GEO is right about something! And ironically, it makes a tacit argument against the existence of controllable optimization levers. But nobody seems to have noticed.

The architect of GEOsight described GEO in that same press release as requiring "a fundamentally different approach — one rooted in authority, earned media, and trust signals." Authority. Earned media. Trust signals. How is that not a description of what Edelman has sold for seventy-three years?

The actual GEOsight deliverables: baseline visibility audits, “earned-first optimization strategy” (read: strategic media relations), content structuring, and performance reporting. Strip the branded language, and you are looking at an Edelman retainer circa 2019 with a dashboard bolted on.

Four months later, Zeno Group launched GEOfluent. The product promises to “track brand visibility... identify which media outlets influence each model... uncover the keywords, prompts, and narratives shaping brand mentions... benchmark against competitors... connect AI answers back to owned and earned media.” Thomas Bunn, Zeno’s Global Chief Client Impact Officer, said GEOfluent “gives clients real-time insights and strategies to influence how they show up.”

What strategies, you ask? More earned media.

Here’s the funniest part: Zeno Group is a subsidiary of DJE Holdings. Two separately branded GEO products, launched within months of each other, sold to different client lists, delivering the same fundamental offering dressed in different clothes. It’s Ford marketing the Pinto with a new name and a Mercury badge.

INK Communications told O’Dwyer’s readers they’d identified “several controllable levers that B2B tech brands can use to influence how they show up in AI-generated responses to lower-funnel queries.” Controllable levers. For a system where the model companies themselves can’t explain citation behavior. Then they listed the levers: optimize your homepage, your product pages, and your metadata.

That’s technical SEO. They repackaged it, published it in a trade outlet, and called it a GEO-specific insight.

5WPR has built a full standalone GEO optimization service page, positioning it alongside their traditional PR offerings as a distinct capability. The deliverables are indistinguishable from content strategy and media relations.

Then there’s the gold rush tier. Alongside the agencies that anyone in this audience has heard of, an entire ecosystem of SEO shops has overnight renamed their services. I won’t link to any of them because I don’t want to give them any added SEO juice.

The category has generated its own self-referential content economy with retainers reportedly running as high as $50,000 per month, before anyone has demonstrated that the underlying service works. Go look for a public case study anywhere offering real proof. You won’t find one.

There’s nothing wrong with an agency telling clients that earned media matters more than ever in the age of AI-driven discovery. It’s true, and it’s a conversation every comms leader should be having. But there’s a line that gets crossed when an agency packages that observation as a distinct, optimizable discipline with proprietary methodology and its own retainer; when “earned media matters” becomes “we know the levers to pull to improve your position in LLM outputs, and they’re distinct from what you’re doing now.” One is honest counsel. The other is selling certainty that doesn’t exist.

A Moment of Clarity

Don’t mistake what I’m saying above as an indictment of the actual communications work of these agencies. Edelman, Zeno, INK, and 5WPR all employ real professionals who work hard to get real results for their clients. I know many people in these shops, and they’re passionate, smart, and criminally underpaid. The Edelman Trust Barometer is the single most important longitudinal research study in the profession. And as we’ve laid out above, these agencies were already doing the things that translate to success in this new era!

This is also not an argument that LLMs haven’t had an impact on information discovery, ascertainable or not, or that they’re inherently bad. AI is changing how information gets discovered. That’s real. You’d be hard-pressed to paint me as an AI naysayer. Wanting to monitor how your brand appears across LLM outputs isn’t a crazy desire. But it’s the difference between buying a thermometer and buying something claiming to be a thermostat.

Since we’re having a moment of clarity, here’s what a purely truthful version of this service would sound like:

“We don’t know why LLMs cite what they cite. Nobody does, not the companies that built them, not the researchers who study them, not us. What we can tell you is that good communications fundamentals like authoritative earned media, structured content, and consistent brand presence across trusted platforms seem to correlate with better AI visibility. We can monitor how you’re showing up and help you do more of what appears to work. But we can’t guarantee outcomes, we can’t explain the mechanism, and the platforms change without notice.”

That’s honesty. It’s also just communications consulting with a monitoring layer. You don’t need a new acronym or a new line item. You need better comms and a dashboard.

The reason nobody says this out loud is that “keep doing good comms” doesn’t beget a new high-margin revenue line. “GEO” does. An audit with a branded name, a dashboard with a proprietary feel, monthly retainers for monitoring a system with no proven optimization surface—that’s money in the bank. The entire category exists because agencies need new things to sell, not because clients have a new problem to solve.

The challenge

If you’re an agency selling GEO as a distinct discipline, I have five questions. I’ll keep them simple.

1. What is the causal mechanism between your recommended interventions and AI citation behavior? Not correlation. Causation.

2. Can you explain why ChatGPT and Perplexity cite different sources for the same query, and how your strategy accounts for architectures that diverge in this fundamental way?

3. What happens to your optimization strategy when a model updates its retrieval system, something that happens regularly, without notice?

4. What percentage of your GEO deliverables are things you would have recommended under your existing communications retainer? Be honest.

5. Can you name a single intervention unique to GEO, something you would never recommend for general communications effectiveness, that demonstrably improves AI citation rates?

If GEO is real, answer those. Publicly. If it’s not, stop rebadging the same thing you’re already doing and charging for it twice.

Erin Miller, VP of Corporate Comms at Yahoo, posted a job listing on LinkedIn last week for a “Global Communications AI Adoption Lead.” The role, as she described it, is someone who can “drive AI adoption across our global comms team, elevate data-driven storytelling, and shape how Yahoo’s narrative shows up in AI-driven discovery and emerging influence models.”

This is a real job posting for a job that almost nobody has done before. That alone is a signal worth paying attention to: one of the first times a major company's comms leadership has created a dedicated role at the intersection of AI and communications strategy.

But the more interesting thing about the posting isn’t what it says, but what it’s missing. The role Yahoo described is essentially an AI evangelist: someone who drives tool usage across the team and shapes narrative. That’s useful. It’s also not the role that will actually transform how a comms team operates.

The gap between what companies think they’re hiring for and what they actually need in order to succeed with AI tools is enormous. And getting it wrong will be expensive in ways that go beyond a bad hire.

The Role Everyone Needs and Nobody Knows How to Fill

Here’s the pattern I keep seeing. A head of comms walks into a budget review and gets the same message as every other department head: no new headcount, but we’ll fund AI initiatives. The CEO wants to hear that the comms team is leading on this. The board wants it in the quarterly update.

So the comms leader has three options, each flawed in its own way.

Option one: hire a big agency. They’ll sell you a six-figure advisory package, assign a team of eight (you’ll interact with two), and produce enough slide decks to fill a bookshelf. In four months, you’ll have a “Comms AI Transformation Roadmap” that looks great in a presentation and changes nothing about how your team actually works on a Tuesday morning.

Option two: bring in a management consultancy. McKinsey and Boston Consulting Group are standing up AI practices as fast as they can staff them. What you’ll get is a 25-year-old with a UChicago MBA running a global playbook designed for supply chain optimization and adapted for “communications” by swapping out some nouns. They don’t know your job because they’ve never done your job.

Option three: tap someone internal. Pick the most AI-curious person on your team and make them the tiger team lead. But that person is already slammed, probably doesn’t have line of sight into every workflow across the comms org, and there’s a real gap between being good with ChatGPT and knowing how to architect a system that transforms how a team operates.

What you actually need is someone who’s sufficiently savvy at comms and at building AI architecture. Not someone who uses AI tools. Someone who builds with them, who understands why a crisis response workflow needs a different context structure than a media monitoring workflow, because they’ve been in the room when the crisis hits and they know what information you’re scrambling for at midnight.

That person barely exists in the market right now. But they will, because they’re becoming essential.

The Context Problem

The reason most AI implementations in comms disappoint isn’t the technology. It’s the context, or lack thereof.

Anthropic’s engineering team published a piece last year called “Effective Context Engineering for AI Agents“ that I’d call required reading for anyone thinking about this space. The core insight: the quality of AI output isn’t determined by the prompt, but by the context—the structured information available to the model at the moment it generates a response. Get the context right and a five-word instruction outperforms a thousand-word prompt against a blank slate.

If you’re thinking “we already handle this because we’ve connected Gemini to our Google Workspace” or “our team uses Claude with Slack and Drive,” you have the beginning of a context layer. You don’t have a good one.

Connecting AI to your email, documents, and chat gives it access to your team’s explicit knowledge—the stuff that’s already been written down. That’s a fraction of what drives good comms work. How your CEO prefers to be briefed before earnings calls. Which journalists are genuinely curious about your space and which ones are fishing for a gotcha. What your CEO actually means when she says “make it tighter.” The relationship history with the reporter who just called about a story publishing in 45 minutes. That knowledge lives in your team’s heads, and when your team asks some hastily-rolled-out LLM chat product for help, none of it is available. The output is generic—Sameness as a Service—and it needs so much editing that it barely saves time.

The difference between a mildly useful AI setup and one that actually transforms how a team operates is whether someone has captured that tacit knowledge and structured it into a persistent layer the AI can draw on. That’s context engineering. And it requires someone who understands the domain deeply enough to know what’s worth capturing and how to get it.

“Forward Deployed”

This brings me to the term in the headline: the Forward Deployed Context Engineer.

The concept of a forward deployed engineer is not new. Palantir created the role in the early 2010s, calling them “Deltas”—engineers embedded directly in client operations who learn how decisions are actually made on the ground and build custom solutions around those realities rather than generic ones.1 The technical capability is table stakes. The domain-specific context is the moat.

The same logic applies to communications, and it’s why the three options I described earlier—agency, consultancy, internal enthusiast—all fall short. An agency doesn’t have the domain depth. A management consultancy doesn’t have the comms expertise. An internal AI enthusiast doesn’t have the systems architecture knowledge.

What you need is someone forward deployed in the truest sense: embedded in the comms operation, fluent in both the technology and the discipline, building context infrastructure that reflects how this specific team actually works.

What the Role Actually Does

Let me make this concrete, because “context engineering” risks becoming the same kind of terminology inflation I’ve criticized before in the AI agent space. A Forward Deployed Context Engineer in comms does three things.

The unglamorous foundation is capturing the tacit knowledge. That means interviewing senior team members to codify the frameworks they use but have never written down. It means building a relationship intelligence layer—not a media list with email addresses, but the qualitative intelligence about every journalist, analyst, and stakeholder the team interacts with that actually makes outreach effective. It means documenting editing patterns, voice standards, and crisis playbooks. All the institutional knowledge that currently lives in people’s heads and evaporates when they leave.

Then comes building the context layer. Once the knowledge is captured, it needs to be structured so AI tools can actually use it. This is where the technical fluency matters. Meeting transcripts become queryable archives. Editorial standards become automated quality checks. Stakeholder intelligence becomes contextual input for outreach drafting. Without this layer, you’re just prompting against a blank slate and wondering why the output sounds like it was written by someone who’s never worked in comms.

The real leverage comes from designing the workflows. Context without automation is a knowledge base—useful, but not transformative. The transformation happens when the context layer powers workflows that compress operational overhead2: editorial systems that enforce house style before a human editor touches the draft, crisis response tools that surface relevant history and approved positioning in minutes rather than the better part of an hour, stakeholder prep that assembles everything known about a journalist before a briefing without anyone having to ask for it.

None of this is hypothetical. I’ve built every one of these systems for my own practice.3 It’s time-intensive but life-changing, not just in terms of improved results but also the time I get back for stuff that actually needs my brain.

What This Means for You

If you’re a comms leader, the Yahoo posting should be a wake-up call. The temptation is to say “we need one of those too” and post a similar req. Before you do, ask yourself whether you’re hiring for what the role actually requires—deep comms expertise with true AI systems knowledge—or whether you’re hiring an “AI-curious comms person” and hoping they figure it out. Those are different things. The first transforms your operation. The second produces a Slack channel full of ChatGPT tips.

If you’re mid-career in comms and wondering where to invest your professional development, this is it. Not “learn to use AI tools.” That ship has sailed, and it’s table stakes. I mean learn to build with them. Understand how context layers work via MCP servers, RAG systems, content stores, and connectors. Get comfortable with the idea that your career’s most valuable skill might not be writing a perfect press release but building the system that produces consistently excellent ones. The people who develop this capability will be the most sought-after professionals in the industry within a year, because right now, almost nobody has it.

If you’re early in your career, you have an advantage your seniors don’t: you’re not unlearning anything. The people entering comms right now who treat AI fluency as a building skill rather than a productivity hack are going to leapfrog people with a decade more experience. It doesn’t require twenty years of experience, but it does require understanding what institutional knowledge actually matters and why, which means paying close attention to how the senior people around you make decisions.

The Window

The comms team that can walk into a budget review and say “we’ve implemented context-engineered workflows that increased our output capacity by 40 percent without adding headcount” just changed how the C-suite sees them. They’re no longer a cost center; they’re an operational model for everyone else.

The teams that build real context infrastructure now will have a compounding, almost-unfair advantage, because context layers get more valuable over time as they accumulate more institutional knowledge. The teams that wait will be trying to catch up to systems that have had a year’s head start absorbing how the organization actually works.

Two essays rattled financial markets this month. One, from Citrini Research, was a fictional macro memo from June 2028 describing an AI-driven economic crisis with cascading white-collar layoffs, a private credit implosion, and cracks in the $13 trillion mortgage market. The other, from AI startup founder Matt Shumer, was a personal account of how the latest AI models had rendered him unnecessary for the technical work of his own job and urged readers to prepare now for the death of white-collar work.

Both spread like wildfire across social media and generated a pile of breathless commentary. But they’re very different pieces of writing. The Citrini essay is genuinely captivating: a multi-dimensional speculative narrative that weaves together labor economics, private credit mechanics, mortgage market dynamics, and geopolitical consequences into a scenario that’s not totally implausible. The Schumer piece reads, ironically, as if it were substantially produced by the very tools it’s evangelizing.

Why did two posts of wildly different quality from people most investors had never heard of cause such a panic?

Narrative Consumers vs. Tool Users

The investors, analysts, portfolio managers, and finance influencers who consume pieces like these are sophisticated evaluators of financial logic. They can spot a flawed model from across a conference room. What they can’t do is evaluate whether the tech assumptions underneath those arguments are realistic on the stated timelines. That requires something financial analysis can’t provide: daily, hands-on experience with the actual products.

When Citrini posits that coding agents will let companies replicate mid-market SaaS products in weeks, or that consumer AI agents will route around credit card interchange fees, the finance audience evaluates the logic downstream of those assumptions. And the downstream logic is good! If those things happen, the cascading effects Citrini describes are plausible.

But someone who uses Claude Code every day to ship real software knows something the scenario takes for granted: the gap between “impressive demo” and “reliable production deployment at scale” is enormous, unpredictable, and not closing on any neat timeline.

Shumer’s piece reveals the same asymmetry but more crudely. His account of AI coding capability is credible: the latest tools really are remarkable for building software. But then he projects that experience uniformly across law, medicine, finance, accounting, and every other domain of knowledge. Anyone actually working in those fields would push back on that generalization, but the audience has no basis to.

AI coding tools are further along than AI tools in virtually every other profession, for structural reasons Shumer himself half-acknowledges: the labs built coding capability first because it helps them build more AI. His experience is real. His blanket application of it to everyone else’s job is not. (At least not yet.)

That this extrapolation was wrapped in AI-generated prose and still landed with the force of prophecy tells you everything about the state of the audience.

The Tomorrowland Effect

Walt Disney’s original Tomorrowland was compelling because it was a narrative about the future first and an engineering project second.1 Walt worked with scientists and engineers, but what made it resonate was the storytelling, making you feel something about what was coming, not just showing you a spec sheet.

The Citrini piece is a high-quality markets version of Tomorrowland: speculative fiction with financial fluency, built by people familiar with constructing market narratives. The Shumer piece is the gift shop version: mass-produced, shiny enough to catch the eye, but not something you’d put on a shelf.

Yet both move the same audience to the same action, and that’s actually the more concerning case. If only the Citrini piece had moved markets, you could chalk it up to the quality of the analysis. But when a clearly-AI-generated blog post produces a comparable reaction, you’re seeing something structural: the audience is grading the narrative, not the premise. They lack the messy, unglamorous, deeply unsexy middle layer of product experience that separates “technically possible” from “happening at scale next quarter.” Without it, anything well packaged enough lands as insight, and even things that aren’t particularly well packaged land too.

We saw this dynamic play out in miniature a few weeks ago. The market reaction to Anthropic’s Claude Cowork legal skills was notable. Legal services stocks dropped double digits when traders noticed the feature. But the plugin had been out since the previous Friday. Anyone who had actually installed it over the weekend would have had a different read. The legal skills are decent starting points for rolling your own workflows, not finished replacements for professional expertise. Enabling the legal skills does not conjure a Supreme Court justice into your laptop.

But if you haven’t opened Cowork, all you have is the press coverage, the feature announcement, and someone’s breathless Twitter thread. Those read very differently from the product experience.

Belief as Economic Force

Friend of the newsletter Kyla Scanlon coined the term “vibecession” to describe what happens when economic sentiment detaches from economic data.2 What we’re watching in AI is a sector-specific version of the same phenomenon: the market’s feelings about AI capability have detached from the product reality, and the feelings are moving real money.

A commenter on the Citrini piece, identifying themselves as working in a Mag7 AI division, made this concrete. It doesn’t actually matter whether a company can replicate a SaaS product with AI, they argued. What matters is whether they can credibly threaten to do so in a procurement negotiation.

The belief in AI’s capabilities, even one untethered from current reality, is already having real economic effects. If a procurement manager walks into a renewal conversation and says, “We’re exploring having AI replace your product entirely,” the SaaS vendor has to respond to that threat, whether it’s technically feasible or not. The bluff works because the vendor can’t be sure it’s a bluff. Margins compress, deals get restructured, real money moves on the strength of a narrative about capability, not capability itself.

This is where the calibration gap becomes self-reinforcing. Pieces like Citrini’s and Shumer’s feed the narrative. The narrative gives procurement managers ammunition. The ammunition produces real business outcomes. The outcomes appear to validate the narrative. It’s a strange loop where market fiction generates market fact.

Where This Puts Communicators

The calibration gap hits differently depending on where you sit as a comms person.

If you’re in comms at an AI company, this gap is awesome right now. The market is imbuing your products with god-like capabilities they don’t quite have yet, which drives investment, talent pipelines, enterprise deals, and the kind of procurement leverage that makes your sales team’s job easier. The rational short-term move is to say just enough not be technically lying and let the narrative do the heavy lifting.

But we’ve all seen this movie before. Every hype cycle has a correction, and the violence of that correction is proportional to the size of the gap between narrative and experience. The companies that survived those resets were the ones that had built enough real product credibility that the narrative coming back to earth didn’t take them out, too. The calibration gap is a tailwind until it’s a headwind. The comms teams at AI companies who are thinking about this now, while building genuine product credibility alongside the hype, getting real user stories into the market, and being specific where the zeitgeist is vague, are the ones who’ll have something to stand on when the music changes tempo.

If you’re in comms at literally anywhere else, be it a SaaS company, enterprise vendor, or startup that isn’t an AI company but lives in the blast radius of AI hype, the gap is a genuine strategic problem. Your customers are reading Citrini and Shumer and perhaps walking into renewal conversations with leverage built on narratives, not product evaluations. Your stock might be moving on someone else’s speculative fiction.

The opportunity here is real, though. There’s a premium on grounded perspective that’s genuinely scarce right now. Communicators who can translate between product reality and market narrative—who use these tools daily and can speak with specificity about what they do and don’t do—have a form of credibility most people in the conversation lack. Not “AI is going to change everything” hand-waving or “AI is overhyped” contrarianism. The specific, boring, valuable knowledge of what the tools actually do today, how fast that’s changing, and where the gaps remain between demo and deployment.

That gap won’t last forever. Eventually, enough decision-makers will use these products daily that the audience will develop its own immunity to narratives untethered from reality.

But right now, a work of well-crafted speculative fiction and an AI-generated blog post land with comparable force, and that tells you everything you need to know about how much room there is for someone who’s actually used the thing everyone else is just reading about.

Back in January, it came to light via FEC reporting that OpenAI’s president and co-founder Greg Brockman and his wife had made a monumental $25 million donation to MAGA Inc. last September—one of the largest individual political donations of 2025.

When interviewed by WIRED about his newfound political largesse, Brockman explained the check in rather grand terms. “This mission, in my mind, is bigger than companies, bigger than corporate structures,” he said. “We are embarking on a journey to develop this technology that’s going to be the most impactful thing humanity has ever created.”

The word that sticks out to me here is “humanity”. He writes a $25 million check with his wife to a partisan political operation, one with very specific policy positions affecting very specific people, and explains it in the language of humanity. The kind that lives in essays and mission statements, not the kind that has healthcare anxieties or gets deported or loses jobs or disagrees with you about politics. Capital-H, abstract, floating-above-the-fray Humanity.

Brockman is not an outlier. If you’ve worked in or around big tech for any length of time, you’ve met the type, probably several dozen of them. They’re everywhere in AI. They care enormously about Humanity. They’d do anything for Humanity. They just can’t be bothered with actual people.

And if these executives and companies don’t see and address the disconnect in their public messaging, they’re doomed to keep losing the battle for hearts and minds the industry desperately needs them to win.

The View From Orbit

When I contemplate a mascot for this type of executive, the image that comes to mind is blue, nude, and levitating: Dr. Manhattan.

For those who haven’t read writer Alan Moore and illustrator Dave Gibbons’ “Watchmen”, here’s the quick version: Jon Osterman is a nuclear physicist who gets disintegrated in a lab accident and reconstitutes himself as a being of godlike power. He can see across time. He can manipulate matter at the atomic level. He is, for all practical purposes, omniscient and omnipotent. And over the arc of the story, he gradually loses the ability to give a shit about people.

This isn’t a flaw in his character. Moore wrote it as the inevitable consequence of operating at that altitude. Manhattan can perceive the entire arc of human civilization. He understands the quantum mechanics underlying all of existence. He genuinely does care about humanity’s survival in some detached cosmic sense. But he can’t maintain a relationship with the woman he loves or comfort someone who’s grieving. Individual suffering becomes statistically insignificant when you’re tracking the movements of atoms and the trajectory of species.

The crucial part—the part that makes “Watchmen” more than a comic book—is that Manhattan doesn’t experience this as a loss, but as clarity. He thinks he’s seeing more clearly than everyone else. The people around him can tell that something essential has been lost, but he can’t see it himself because the view from orbit is so intoxicating.

Replace “nuclear physicist” with “AI executive,” and you have a disturbingly accurate portrait of a particular mode of tech leadership that has exploded across the industry over the past few years. (Minus the nudity, thankfully.)

Why the Abstraction is Irresistible

I don’t think these guys are truly indifferent. I’ve met and worked with many Dr. Manhattan types over two decades in this industry—an industry I'm personally and professionally invested in, as someone who builds with these tools daily and whose consulting business is substantially tied to AI. They are, in the majority of cases, formidably intelligent, voraciously curious, and capable of accomplishing amazing feats. The problem doesn’t lie in any of these things, but in the comfort the worldview they inhabit provides.

Humanity, the concept, is an extraordinarily comfortable thing to care about. It’s theoretical. It’s malleable. You can model it and optimize for it. You can write essays about it on a blank white page at the top of your company’s domain hierarchy, and nobody can pin you down on specifics.

People, on the other hand, are a nightmare. They’re real and present, messy, inconsistent, and contradictory. They get angry at you, sue you, organize against you, show up outside your office with signs. They have the temerity to worry about their job rather than the species-level trajectory of labor markets. They want to know why their kid is using your chatbot to cheat on homework instead of appreciating that you’re building the most important technology in human history.

Humanity holds still for your grand plans. People do not.

There’s a second force at work beyond comfort, one I’ve written about before: centering Humanity in your rhetoric casts you as the hero of civilization’s story. When Brockman says the mission is “bigger than companies, bigger than corporate structures,” he’s writing himself into a narrative where the $25 million to MAGA Inc. isn’t a political act with winners and losers, but a strategic move in the grand project. The partisan specifics dissolve into the universal mission. And if you can’t see that? Well, you’re just not thinking at the right altitude.

This is the rhetorical equivalent of a judo throw. By elevating the conversation to the civilizational plane, any critique of the specific decision looks petty and small by comparison. You’re worried about Medicare funding? I’m worried about the survival of Humanity. Who sounds more serious?

We’ve Already Run This Experiment

Here’s where it gets really instructive for the AI industry, and where Moore’s choice to root Dr. Manhattan in nuclear physics turns out to be more than a narrative device. The American nuclear industry already ran this exact communications exercise and failed catastrophically.

It started with a campaign draped in the language of progress. Eisenhower’s “Atoms for Peace” initiative, launched in 1953, was internally conceived as “psychological warfare”—a PR effort to manage public fear of nuclear weapons by redirecting attention toward the peaceful atom. They partnered with Walt Disney and sent traveling exhibits around the country. AEC Chairman Lewis Strauss promised that nuclear energy would give future generations electrical power “too cheap to meter.” All Humanity-scale rhetoric: the betterment of the species, the march of progress, the inevitable arc of science lifting all boats.

When the public began raising concerns about safety and costs, the industry commissioned research to understand why people weren’t getting on board. What came back was what social scientists now call the “deficit model”—the idea that public opposition was rooted in a deficit of knowledge, not a surplus of legitimate concern. The prescription was always more education, more persuasion, more explaining. Never more listening. The National Academies later observed that “trust is especially undermined if experts dismiss public concerns, or when these concerns are perceived to be dismissed.”

Let me be clear about causation, because the AI parallel only works if we’re honest about it. The communications failures didn’t kill nuclear power. The disasters did. But two decades of talking over the public meant the industry had built precisely zero reservoir of human-scale trust to draw on when the real crises hit. Nuclear pioneer Alvin Weinberg admitted in 1976 (three years before Three Mile Island) that “the public perception and acceptance of nuclear energy appears to be the question that we missed rather badly.” After TMI and Chernobyl confirmed the public’s worst suspicions, over a hundred planned U.S. reactors were cancelled.

Moore wrote “Watchmen” in 1986 and 1987, steeped in exactly this nuclear anxiety. Manhattan is the nuclear establishment made flesh: brilliant, powerful, operating with genuinely good intentions at the civilizational level, and absolutely useless to the individual humans whose lives were shaped by the technology he embodied.

The Wrong Solution to the Right Problem

Which brings us back to our Dr. Manhattan Syndrome-afflicted AI execs and what might be the most revealing detail in the WIRED piece: Brockman’s proximate motivation for ramping up political spending is that public opinion has turned against AI.

He’s very right about the problem. Pew Research Center data from mid-2025 shows that 50% of Americans now say they’re more concerned than excited about AI, up from 37% in 2021. Fifty-seven percent rate AI’s societal risks as high, while only 25% say the same about its benefits. Fifty-nine percent lack confidence that U.S. companies will develop and use AI responsibly. Those numbers are terrifying for anyone who builds or advocates for AI products.

But think about what the people behind those numbers are actually worried about. They’re not anxious about AI in the abstract, per se, but its implications. They’re anxious about their job, their kid’s homework, their creative work getting scraped without permission, their privacy. Human-scale concerns that are specific, personal, and grounded in the daily texture of individual lives.

And Brockman’s response to this very specific, very human anxiety is to... float further up into the philosophical stratosphere while writing a mega-checks to a partisan PAC and explaining it in the language of civilizational mission. It’s like a doctor hearing a patient who says, “My knee hurts,” who then delivers a lecture on the elegance of the musculoskeletal system. The patient doesn’t need you to appreciate the beauty of human biology. They need you to look at their damn knee.

The Pew data on AI skepticism, importantly, cuts across party lines. This isn’t a red or blue problem. By picking a partisan side and then wrapping it in Humanity language, Brockman has managed to simultaneously politicize a non-partisan anxiety and fail to address the underlying concern. He’s told half the country he’s against them politically, and told the other half he cares about them only as an abstraction. Nobody gets to feel like an actual human in this interaction.

This is the Dr. Manhattan Syndrome trap in action. The more godlike your perspective, the more you lose touch with the people your technology actually affects, and the less capable you become of addressing their concerns in terms they recognize as genuine.

A Thousand Songs in Your Pocket

There is another way to talk about transformative technology. Steve Jobs demonstrated it for twenty-five years.

Jobs rarely talked about ‘Humanity’ as an abstraction or a project to be managed. He almost never spoke about the ‘trajectory of the species’ in his product launches. Instead, he talked about you. Your pocket. Your music. Your photos. What you create with this thing. The entire Apple communications architecture was built around the second person singular.

When Jobs introduced the iPod, he didn’t say, “This device represents a paradigm shift in humanity’s relationship with media.” He said, “A thousand songs in your pocket.” When he launched the iPhone, he didn’t claim it would transform the trajectory of civilization. He showed you what you could do with it.

Even “Think Different”—the closest Apple ever got to a grand civilizational statement—was populated with specific people. Einstein. Gandhi. Lennon. Earhart. Actual humans with names and faces and stories, not a blank white page with portentous text.

Jobs was arguably more of a genuine visionary than any of these AI leaders. The man reinvented multiple industries. He had more right to talk in civilizational terms than Brockman does. But when he did, he framed it as a contribution to the species, not a control mechanism over it. He understood that to impact humanity, you have to build tools for individual humans. It was a strategic and philosophical choice rooted in the understanding that people don’t connect with abstractions.

Jobs stayed at ground level because that’s where the customers live. Dr. Manhattan floated away because the view from orbit was more beautiful. One of them built the most valuable company on earth. The other left the planet entirely.

This shouldn’t be read as an argument against having any kind of civilizational vision. You may need one, depending on your mission. The engineers grinding through hard problems on brutal timelines aren’t signing up for “a better chatbot.” The all-hands, the investor pitch, the recruiting dinner: these are exactly the right rooms for Manhattan altitude. Jobs had his own reality distortion field, too. He just kept it largely inside the building.

The error isn’t thinking at a civilizational scale. It’s delivering the recruiting pitch at the press conference. Different rooms. Different audiences. Different concerns.

It’s Not Too Late to Come Back Down

I know that comms practitioners at OpenAI, Anthropic, Google, and other major players in the AI industry read this newsletter. Some of you are friends, some are acquaintances. This part is for you.

The nuclear establishment had decades of calcified one-way communication before Three Mile Island blew the lid off. They had built an entire institutional culture around talking over the public’s head. By the time the crisis hit, the patterns were so deeply embedded that recovery was essentially impossible. That industry still suffers from it today, despite having one of the best safety records in the energy industry.

AI is, for all intents and purposes, four years old as a public-facing technology. ChatGPT launched in November 2022. The trust deficit right now is a trend line, not a fixed reality. The Pew numbers are moving in the wrong direction, but they haven’t calcified yet. There is still time to change the trajectory. But there has to be will, too.

And I don’t think the leaders of these companies are incapable of introspection and change, either. Dr. Manhattan Syndrome isn’t a permanent condition. It’s a habit of altitude, reinforced by an ecosystem—investors, conference organizers, friendly podcasters, peers—that rewards civilizational rhetoric and never demands specificity.

What breaking it looks like isn’t complicated, though it is uncomfortable. It means talking about people, not Humanity. It means naming trade-offs rather than papering them over with mission statements. It means your CEO sitting across from a skeptical reporter and engaging with specific concerns about job displacement, creative rights, privacy—on those terms, not by retreating to the cosmos. It means making your customer the protagonist of your story instead of casting your company as the hero of civilization.

Some of you comms people already know all this and have been making these arguments internally, only to be overruled by leadership teams drunk on the view from orbit. I’ve been that person. I know how it feels. Maybe this gives you a piece of evidence to bring into the next room where the decisions get made.

But here’s the real pitch: it works. Trust is built at the human level, one person and one concern at a time, not at the level of civilizational altitude. The companies that figure this out in the next few years will own the next era of technology. The ones that keep floating above it all will eventually discover, as Manhattan did, that they’ve drifted so far from the people they claim to serve that they’ve become irrelevant to them.

Here’s the final irony of the Dr. Manhattan metaphor, and the one most worth sitting with. The actual hero of “Watchmen” isn’t Manhattan, the guy with the godlike power, the civilizational perspective, and the ability to see across time. It’s the messy, compromised, ground-level humans making ugly choices in real time with imperfect information, conflicting loyalties, and the full weight of consequences on their shoulders.

Manhattan has the power. But he’s the least useful person in the room when it actually matters. He can reshape matter, but he can’t reshape public trust. He’s not the villain. He’s just irrelevant. And for someone who claims to care about Humanity, that might be the worst thing you can be.

You don’t have to be him. Put some pants on and come back down to earth. There are actual people down here who could use your help.

Roughly $1 trillion in software market capitalization has been wiped out since mid-January. Here’s the thing, though: the earnings are fine.

Jamin Ball at Altimeter, whose Clouded Judgement newsletter is the sharpest ongoing analysis of the SaaS landscape, pointed out that Q4 results have actually been solid. Companies are hitting their numbers. Some are beating them handily. This isn’t a business crisis, but the stocks are cratering anyway. So what is it?

It’s a narrative crisis. And almost every SaaS CEO in America is making it worse. Except one shining example.

The Flavors of Flailing

A few distinct CEO response patterns have emerged from the wreckage of Q4 earnings calls and public statements:

The Defiant Evangelist is the most common archetype, encompassing roughly half of public SaaS CEOs. Marc Benioff is its avatar. When Salesforce stock hit its lows (down over 20% for the year), Benioff went on his earnings call and called the death-of-SaaS narrative “nonsense” that “isn’t grounded in any customer truth.” He pointed to Agentforce as the fastest-growing product in Salesforce’s history. Meanwhile, he was laying off roughly 1,000 workers, including members of the Agentforce team itself. Jay Woods of Freedom Capital Markets called Salesforce the “poster child” for doubts about AI technology. Ball has pointed out that from 2002 to 2009, newspaper stocks declined in a straight line even as earnings grew for five of those years before the bottom fell out. When the gap between rhetoric and observable reality is that wide, bravado isn’t a strategy. It’s a tell.

The Provocateur-Disruptor is a smaller category but with an outsized blast radius. Satya Nadella provided the intellectual scaffolding for the entire selloff way back in December 2024 when he told the BG2 podcast that SaaS applications are “essentially CRUD databases with a bunch of business logic” that “will probably collapse in the agent era.” Flash forward to this February, when Alex Karp took the stage for Palantir’s Q4 earnings call and lit a match. His numbers were genuinely spectacular—70% year-over-year revenue growth, U.S. commercial revenue up 137%. But his commentary was incendiary1: “Welcome to our Palantir revolution, otherwise known as our earnings call.” “One of the truly iconic performances in the history of corporate performance or technology.” “You can divide companies into two categories: the quick and the dead.“

The market reacted directly to Karp’s argument that AI would render SaaS companies “irrelevant,” contributing to the roughly $300 billion that evaporated the following day.

And then there’s The Founder Returns, a category of one. Workday co-founder Aneel Bhusri came back from the executive chairman's seat with a $138.8 million compensation package to retake the CEO role. Something like $60 million of that requires only that he stay four years—no performance targets. The board itself isn’t sure this can be navigated. Bhusri’s return might be the most honest signal any SaaS company has sent all quarter.

A handful of companies—Cloudflare and CrowdStrike stand out here— have structurally sound arguments because AI agents directly increase demand for their products.2 Their stocks have held up better, relatively speaking. But they’re the exception, not the pattern.

What Nobody’s Saying

The most revealing thing about this entire earnings cycle is what’s conspicuously absent.

Almost no CEOs acknowledge that seat-based revenue models face structural compression, even though this is the central market concern. Nobody engages with what Ball calls “front door risk”—the possibility that AI agents capture incremental value atop existing platforms, pushing traditional SaaS down the stack to middleware. And no one acknowledges that SaaS growth rates have declined every quarter since the 2021 peak, a trend that predates AI anxiety entirely but which AI gave the market permission to reprice.

Morgan Stanley captured the environment’s verdict on ServiceNow after Bill McDermott delivered a beat-and-raise quarter that nonetheless sent the stock down 10%: “In an environment of heightened investor skepticism on incumbent application vendors, stable growth, in line with expectations, likely falls short of shifting the narrative.”

Read that line again. Stable growth likely falls short of shifting the narrative. The problem is explicitly a narrative problem, and these CEOs are losing.

One CEO Who Isn’t

Which brings me to Dylan Field.

In an exclusive interview with Alex Heath of Sources ahead of Figma’s earnings call, Field did something almost none of his peers are doing.3 He acknowledged the existential threat, engaged with it structurally, and offered a specific thesis explaining why it makes Figma more valuable rather than less.

Figma’s stock had fallen more than 80% from its post-IPO high before yesterday’s results, caught in the same sell-off punishing every SaaS company perceived to be in AI’s crosshairs. A Morgan Stanley analyst asked Field directly on the earnings call if he was “letting the fox into the henhouse” by partnering so openly with Anthropic through Claude Code integration. Where a Benioff might have called the premise nonsense and a Karp might have declared himself immortal, Field engaged.

He pointed out that virtually every frontier AI lab already uses Figma to design how they bring their models to users. He described the MCP server architecture Figma has built as infrastructure extensible to any coding tool—not a defensive moat but an open invitation. When Heath pushed him on the most extreme version of the fear—whether a sufficiently capable agent could render Figma itself redundant—Field had the line of the earnings cycle: “There's a difference between agents collecting context and agents producing work.” His argument is rooted in Jevons paradox: as AI output improves, teams will want to do more design, not less, and they'll do it in Figma.

You can agree with that thesis or not. But notice what he did that almost no other SaaS CEO is doing. He made a specific, falsifiable argument about why the structural threat operates differently in his domain. He addressed the fear of seat compression by explaining that Figma will be layering usage-based credit pricing onto its seat-based model starting in March. And he treated the Anthropic integration as an opportunity to demonstrate rather than a threat to deflect.

The stock was up more than 15% after hours.

The Comms Lesson

Most SaaS CEOs right now are still running the 2023 playbook: launch an AI product, cite early adoption metrics, declare the company a platform, and announce a buyback. But it’s 2026, and the market is discounting structural, not cyclical, risk. The ones getting punished most severely share a common trait: they treated AI disruption as a crisis to manage rather than a business-model challenge to address with specificity.

Field wove together a story. He offered a narrative explaining why the world these investors fear actually makes Figma more essential, grounded it in a specific economic concept rather than in vibe writing about the future, and took the hardest version of the question head-on rather than swatting away the easier one.

Benioff doesn’t have a thesis for his future. McDermott doesn’t have one. Karp has a thesis, but it’s about everybody else dying, which isn’t the same thing.

Field has one. And for the moment, the market is listening.

I saw something on Twitter1 this week that made me twitch. A startup announced its pre-seed funding with a cinematic video that wouldn’t look out of place as a Super Bowl teaser from last Sunday. Moody lighting, dramatic cuts, a sweeping tagline promising to transform an entire industry. The replies filled with insider hosannahs and hyped energy. The vibes, as the kids would say, were immaculate.

My initial reaction was skepticism: why is a pre-seed company spending resources on a cinematic mood reel before shipping anything? The more I probed my thinking, though, I realized my twitch was not about the video or the announcement strategy at all, but about what comes next for startups like this.

Because I’ve seen this movie before, and the second act is where founders get into comms trouble.

The VC Twitter dopamine doom loop

What this founder did actually makes perfect sense for where they are right now. At pre-seed, your audience is investors. Your job is to sell a vision, attract talent, and set up your next raise. If you can do that with a compelling video and some well-placed signal-boosting from your lead investor, that’s smart tactics for the stage you’re in.

At seed, you’re still mostly talking to investors, but you should be starting to talk to early customers. By Series A, your primary audience needs to have shifted dramatically: to customers, partners, and industry players who will determine whether this business actually works.

The problem isn’t that founders optimize for VCs and startup Twitter early on. The problem is that too many of them never stop. Still posting for the VC reply guys and optimizing announcements for tech Twitter engagement rather than for the customers and partners who actually matter at their stage.

This is audience capture, plain and simple, and it’s one of the sneakiest traps in startup communications. Not because the founder is doing something wrong at the start (quite the opposite), but because the dopamine loop that worked at pre-seed keeps delivering hits long after the comms strategy should have changed. And nobody in the founder’s immediate orbit has any reason to tell them to stop, because everyone in that orbit — the VCs, the other founders, the tech press — is also part of the captured audience.

Sugar highs versus spinach

Performing for VC Twitter is easy to measure and fast to reward. You post an announcement, you get engagement, you screenshot the metrics, you feel like your comms are working. The feedback loop is tight and gratifying. It’s a sugar high.

Building credibility with the people who actually determine your company’s fate is slow, ambiguous, and largely invisible on social media. It’s eating your spinach. The enterprise buyer who’s going to sign your first six-figure contract is not posting fire emojis under your Series A announcement. The industry incumbent whose partnership you need is not retweeting your founder’s builder-philosopher thread. The work that moves those people (targeted outreach, credible proof points, quiet relationship-building, trade press over tech press) most likely doesn’t generate Twitter impressions. It doesn’t feel like winning in the moment.

So founders keep going back to what feels good and what the ecosystem reinforces, because VCs want portfolio companies generating buzz, accelerators teach “building in public” which often becomes “performing in public,” and tech media covers funding rounds like product launches. The whole infrastructure is optimized to keep founders talking to the wrong room.

Clubhouse was the logical endpoint of this dynamic: a company where the captured audience wasn’t just the comms strategy but the product itself. At its peak in early 2021, the app was valued at $4 billion on the strength of rooms that were, overwhelmingly, VCs and founders performing for each other. Andreessen Horowitz led the round and hosted some of its most popular rooms, a closed loop so tight it could’ve been drawn with a compass. The invite-only model was a growth hack but also a mechanism for ensuring the captured audience stayed the only audience.

When Clubhouse finally opened up, regular people wandered in, looked around, and left. The product had been so thoroughly shaped by and for the insider feedback loop that it had nothing to offer anyone outside it. Clubhouse didn’t fail to find a broader audience. It optimized itself out of one.

You only get one launch

The separate but related thing founders underestimate: you only get so many “moments” with any given audience. You get one “introducing” moment. You get one launch. You get one first-customer milestone. These are finite, and each one should be calibrated to the audience that matters most at that stage.

If you spend your “introducing” moment on a pre-seed video optimized for VC Twitter, that’s fine. VCs were your audience! But your launch moment? That needs to be built for customers. Your first partnership announcement? That needs to speak to the industry. If you’re still producing cinematic mood reels and angel-name-drop cap tables at Series A because that’s what worked before, you’ve spent your most valuable narrative capital on an audience that can’t save you.

I’ve watched this play out repeatedly over my career. The founder who built their entire communications muscle around generating VC Twitter engagement struggles to pivot when the audience shifts. They struggle to talk to enterprise buyers, don’t have relationships with trade press, and haven’t built the quiet credibility that moves conservative industries. They’ve been training for a race they’re no longer running.

Tie yourself to the mast

There’s a famous moment in The Odyssey2 where Odysseus knows his ship is about to pass the sirens. He doesn’t pretend their song isn’t beautiful. He actually wants to hear it. But he also knows that if he’s free to act on what he hears, he’ll steer the ship straight into the rocks. So he has his crew tie him to the mast and plug their own ears with wax. The song plays, and it’s gorgeous. But the ship sails past.

The VC Twitter engagement loop is the sirens’ song. It’s not fake. At pre-seed, it was genuinely useful. Heck, it may have been the thing that got this founder their round. The danger isn’t in hearing it, but in still steering your ship toward it when your ship needs to be headed somewhere else entirely.

If I were advising the founder whose announcement I saw, I’d tell them to enjoy it, ride the wave, and use the attention to build relationships. But six months from now, take a cue from Odysseus. Build the mast: the advisors who will tell you hard truths, the comms discipline that forces you to ask who you’re actually trying to reach, the honest self-assessment to recognize when a tactic has outlived its usefulness. Tie yourself to it. Because the song will still be playing and the ship still needs to get somewhere.

I’m a 43-year-old white guy living in Marin County, so naturally, you expect me to talk about hip-hop.1

(Stick with me here.)

Let’s check in on the three protagonists of 21st-century rap’s most infamous beef. Just last night, J. Cole released “The Fall-Off,” his seventh and reportedly final album. It’s a double album, 24 tracks deep, the culmination of a project he first teased eight years ago at the end of “KOD”. He’s been building toward this moment for nearly a decade.

Kendrick Lamar won five more Grammys last Sunday, including Record of the Year for “luther,” making him the most-awarded rapper in Grammy history. The Grand National Tour with SZA grossed nearly $370 million. He’s at the absolute peak of a career built on treating every release as an event.

And Drake has been teasing his ninth album, “Iceman,” since last summer through cryptic YouTube livestream “episodes” and a drip feed of singles with no release date announced. Always present, always producing, always in the mix.

Though the three have achieved comparable levels of acclaim, they have very different relationships with attention. And these diverging approaches are more instructive frames about tech communications than you might think.

J. Cole: Directing Attention Outward

Let’s look at J. Cole first, since he just dropped. Cole spent the better part of a decade building toward a single release. He named his album after the thing every artist fears most (becoming irrelevant), then layered narrative across multiple projects, dropped hints in lyrics and interviews, and let anticipation compound until the release carried the weight of his entire career arc. “The Fall-Off” is the final chapter of a story that started with a mixtape called “The Come Up.”

But the defining Cole move is actually his label, Dreamville. He treats it as an ecosystem where he platforms other artists, produces for them, and creates events like Dreamville Fest, positioning him as a curator and community builder, not just a performer. He directs attention outward while quietly consolidating his own influence. He’s your favorite rapper’s favorite rapper, respected most deeply by the people actually doing the work.

The tech attention parallel is Stripe. Patrick and John Collison built a company that deliberately focuses on its customers' success rather than its own. The whole narrative is: we’re the infrastructure that makes ambitious companies possible. Stripe Press publishes books about economic progress and ideas that have nothing to do with payments, the same way Cole invests in documentaries, festivals, and artist development that transcend his own catalog. Both are saying the same thing: our taste and judgment matter as much as our core output.

Cole doesn't chase moments. He shows up steadily, delivers quality, and stays accessible without being overexposed. Stripe maintains the same rhythm: they publish, they speak at events, they ship, but they never feel like they're performing for attention. The consistency is the strategy.

The risk of this approach is specific to its generosity. When you spend years directing the spotlight toward your ecosystem, your customers, your community, you may train the market to look past you. Cole can sell out arenas, but the cultural conversation consistently treats him as the third name in the Cole-Kendrick-Drake trinity, despite arguably the most consistent catalog of the three. Stripe processes hundreds of billions in payments, but when the press covers a Stripe-powered company’s IPO, the story is about the company, not the infrastructure that made it possible. You become the stage, not the performer.

The tell that you’re executing this well versus poorly: are the practitioners in your space citing you as the standard? Or have you directed so much attention outward that even your advocates forget to mention you?

Kendrick Lamar: Strategic Scarcity

Kendrick operates in cycles of intense visibility followed by deliberate silence, and every cycle raises the stakes. Five years between “DAMN.” and “Mr. Morale & The Big Steppers” would kill most rappers’ momentum. For Kendrick, it built anticipation because the previous work justified the wait. “GNX” arrived as a surprise drop with zero advance singles. No rollout, no press tour. Just the work, landing like a meteor. The silence is the marketing.

The tech company that runs this play most clearly is Rockstar Games.2 They go completely dark for years between releases: no executive interviews, no conference appearances, no social media engagement from leadership, minimal corporate communication. Then they drop a single trailer, and it becomes the biggest cultural event in entertainment. GTA VI’s first trailer broke YouTube records without Rockstar doing a single press briefing. The work speaks, full stop.

But strategic scarcity only works if you have something worth the wait. Applied to mediocre work, it just creates an embarrassing gap between buildup and reveal. “GNX” could arrive unannounced because “DAMN.” and “To Pimp a Butterfly” and “good kid, m.A.A.d city” preceded it. GTA VI can coast on years of silence because GTA V sold 200 million copies. The catalog is the credibility.

Some honest indicators of whether a company has earned this posture: Is organic community growth happening without paid acquisition? Are strong candidates reaching out unprompted? Are journalists requesting access, or does every piece of coverage require extensive outreach? If the answers are mostly no, you haven’t earned strategic silence. You’re just… silent.

Kendrick didn’t start here, either. He had years of “Section.80” and “Overly Dedicated” and regional buzz, building a foundation. The discipline was in knowing when he’d earned the right to go quiet.

Drake: Omnipresence and Absorption

Drake’s attention strategy isn’t subtle and doesn’t pretend to be. He simply never cedes the conversation. A feature here, a loosie there, an Instagram caption that becomes a meme, a beef that dominates a news cycle, a surprise drop that resets the discourse. He treats every platform as a distribution channel and every moment as an opportunity to be in your feed. The “Iceman” rollout underway is classic Drake: drip-feeding content across platforms, staying perpetually in the cultural conversation, treating presence as its own form of leverage.

You can have a favorable or unfavorable opinion3 about Drake, but you can’t forget he exists.

The tech parallel is Meta. Zuckerberg’s company operates at the same relentless cadence—always shipping, always announcing, never letting a competitor’s moment go unanswered. TikTok surges? Reels ships within months. Twitter stumbles? Threads launches overnight. OpenAI captures the AI narrative? Meta pivots to open-source AI and floods the zone. Stay in the conversation at all costs, and trust that the distribution advantage will sort out the rest.

There’s a persona dimension, too. Both Drake and Zuck constantly read the room and shape-shift to stay relevant, which prompts a persistent question about authenticity that neither seems particularly troubled by. The reinventions aren’t distractions from the strategy. They’re part of it, each metamorphosis another reason to pay attention.

This is still the default mode in tech comms, and there are real contexts where it’s the right call.4 Pre-product-market-fit, you need awareness. Silence isn’t strategic, it’s suicidal. In enterprise, where buyers need constant reassurance that a vendor is active, going quiet creates procurement anxiety. Cadences exist for a reason.

The problem is when omnipresence becomes the only play, which is where most startups end up. Every product update gets a blog post, every integration gets a press pitch. This playbook made more sense when the tech press was a bigger ecosystem that would reliably cover your Series B or your Salesforce integration. Now it has diminishing returns. Journalists are burned out on undifferentiated pitches, the trade press has contracted, and your startup is in the same infinite scroll as everyone else’s.

Drake’s omnipresence works because he’s an artist with an audience so massive that even a mid single charts. Meta’s success stems from its having two billion users and its ability to ship to all of them overnight. Most companies don’t have that luxury. Presence without substance trains the market to expect noise rather than signal. Each announcement that doesn’t land makes the next one easier to ignore.

Matching the Strategy to the Moment

Here’s the thing most people reading this need to hear: you’re probably not Cole, Kendrick, or Drake yet, and that’s fine. You’re probably in your mixtape phase. The goal isn’t to run any of the three strategies above. It’s to build a catalog good enough to earn the right to choose one.

For a company in the mixtape phase, the job is straightforward if unglamorous: ship good work, figure out what resonates, build relationships with the journalists and communities that matter, and develop an instinct for what’s worth talking about. Some version of the Drake play, calibrated to your resources, usually makes sense here. But it should be in service of building the foundation, not mistaken for the strategy itself.

The honest question to ask: have we built enough of a catalog that any of these strategies is available to us? Or are we still proving we belong?

The hardest part of all this is that you’re rarely running one strategy across the board. Your developer audience might respond to Kendrick’s scarcity. Your enterprise buyers need Drake’s reassuring presence. Your platform and ecosystem story might warrant the Cole treatment.

Cole earned his ecosystem. Kendrick earned his silence. Drake earned his volume. The question isn’t which of these strategies is best. It’s whether you’ve earned the one you’re running.

There’s an epidemic running rampant on LinkedIn among comms and PR people. No doubt you’ve seen it, or perhaps, sadly, even been afflicted by it.

I’m speaking, of course, about the addition of “Storyteller” to what feels like half the practitioner population’s profile headlines.

There’s always been a latent vein of this in comms, but it experienced a super-spreader event in December with a Wall Street Journal piece documenting corporate America’s “storyteller” hiring spree. According to the Journal’s analysis, LinkedIn job postings mentioning “storyteller” doubled in the past year, with over 20,000 communications roles now using the term. Executives mentioned “storytelling” on earnings calls 469 times in 2025, up from just 147 a decade earlier.

Before I go further: I know. Critique of LinkedIn trends is itself a LinkedIn trend, and writing a newsletter about it is peak irony. I’m building my own narrative here while arguing that most corporate storytelling is bullshit. That tension is real, and I’ll come back to it.

But this particular trend irks me because what I’ll call Storytelling™ is rising at the same rate of consumer distrust. Something’s rotten in Denmark’s CMO office.

According to the 2025 Edelman Trust Barometer, 71% of global consumers agreed with the statement “I trust companies less than I did a year ago.” That’s a straight-up crisis.

Similarly, the Citizen Brands 2025 study found that 56% of consumers believe brands spend too much time talking about their values, up from 47% just a year earlier. More damning: 68% doubt the truth behind those claims.

University of Adelaide research found that consumers are “becoming more uncertain of brand communication due to misinformation, deep fakes, misleading claims, and perceived hypocrisy.” A majority of young people believe a brand is hiding something if it avoids certain topics.

Let me translate that from consultant-speak: people think companies are full of shit. This tracks with lived experience. If a friend tells you they “got sold a story” about something, are they speaking in a flattering way?

So yes, storytelling matters, but there’s something wrong with the stories, obviously. It’s not that audiences reject narrative inherently. Humans are wired for story. It’s that they can tell when a story is really about them versus when it’s a company admiring itself in the mirror and asking them to be voyeurs.

There’s a Family Guy clip from 2006 where Peter Griffin, at imminent risk of death, confesses to his family that he didn’t care for “The Godfather”. His reason? “It insists upon itself.” It’s a tight-if-confusing way of saying the movie demands reverence it hasn’t earned.1 Most corporate storytelling does the same thing.

Go back to any Storytelling 101 framework, be it Joseph Campbell’s hero’s journey, Aristotelian drama, whatever. Stories work because the protagonist is transformed through adversity. They face genuine conflict, make real sacrifices, emerge changed. The audience invests emotionally because there are actual stakes, peaks and valleys, and a reason for the audience to care.

Storytelling™ as practiced wants all of that emotional resonance without any of the vulnerability or transformation. The company is already great, has always been great, and just needs you to recognize its greatness. There’s no real conflict because conflict would mean admitting something was wrong. There’s no transformation because transformation would suggest the company wasn’t already perfect.

That’s not a story. It’s hagiography—saints’ lives written for the already converted. Audiences can smell it from a mile away. That’s what those consumer skepticism numbers are actually measuring.

But it’s not just the solipsism that grates. The dirty secret is that most corporate storytelling isn’t really for customers at all. Grand navel-gazing narratives serve VCs who need to believe they’re funding civilization-scale change. They serve executives who want to feel like protagonists in something meaningful. They serve press looking for trend pieces. They serve conference organizers booking keynote speakers. The customer is largely watching this performance and seeing through it.

Not all corporate storytelling is bad. Some companies do it brilliantly. The difference comes down to one thing: who’s the hero?

The best Apple marketing, the gold standard for tech for twenty-plus years, made you the creative, the Crazy One. They just made the tools, and the customer was always the protagonist. But most companies can’t resist main-character syndrome.

We’re living through a period where truth itself is contested territory. Political discourse has degraded trust in institutions broadly. AI is flooding the zone with synthetic content. According to Edelman’s research, 62% of respondents struggle to distinguish between truth and falsehood in media narratives.

Against this backdrop, “authentic storytelling” has become its own kind of performance. The tactics are now well-established: calculated vulnerability where brands share just enough weakness to seem relatable without revealing anything truly risky; manufactured imperfection with deliberate insertion of minor flaws to appear more human. People see through this subconsciously.

In their 2024 Red Sky Predictions, Havas Red argued that “truth telling will surpass storytelling as a key differentiator for brands.” I’d put it slightly differently: the issue isn’t story versus truth. It’s that truth has to be the foundation of the story, not a coat of paint over self-congratulation. And the first truth most companies need to accept is that they’re not the protagonist.

If you’re an in-house comms professional or an agency lead, here’s the framework that distinguishes good storytelling from performative bullshit.

Make your customer the protagonist. Every piece of content should answer: How does this make the customer the hero of their own story? If your answer is “It shows how great our company is,” just start over.

Embrace real trade-offs. If you can’t point to a specific limitation or challenge, you’re probably not being honest enough. Not enough tension. You should be able to identify hinge points in the story where you take a very different path.

Default to specificity. Vague aspirational language (“driving positive change,” “empowering communities”) is the refuge of companies with nothing substantive to say. Specific details, numbers, and commitments are harder to fake.

Test for authentic action. Before publishing any values-based message, ask: What are we actually doing about this? If the answer is “Just this post,” don’t post it. Your actions must precede and exceed your words. The research is clear: performative allies perform no better than companies that stay silent, and in many cases worse.

Most companies aren’t doing anything interesting or sexy enough to support an HBS-case-study-quality narrative. That’s fine. Most companies and brands don’t need to be centered in epic tales in order to be effective at driving business. They need to clearly explain what they do, who it’s for, and why it matters.2 They need to tell the truth about their products and services, including the parts that aren’t perfect. They need to cede the spotlight to the customers whose problems they’re solving.

None of this is as sexy as “Chief Storytelling Officer3.” It won’t generate keynote invitations or LinkedIn engagement or admiring profiles. But it builds something more durable: trust.

Almost everything written about AI and communications centers around productivity. How to crank out press releases faster, automate briefing docs, that kind of stuff. And that’s all correct: there’s real value in getting the grunt work done so people can focus on the parts of comms that actually require human judgment, creativity, emotions, and relationships.

But what I’ve been thinking about is that these tools don’t just help you write faster or generate media. They let you build things. This isn’t a grand revelation: vibe coding is a broadly understood thing. But I’m not sure the comms world has fully absorbed its significance and meaning or what’s now possible in the same way other disciplines have.

When I came to Google in 2010, the way the comms team assembled daily press coverage was, I kid you not, a rotating cast of the most junior people on the team would grind through manual Google News searches. We were at Google, for Pete’s sake, the Mecca for innovative software answers to information organization. It was absurd.

I made it my own little 20% time1 mission to try to find engineers who’d spare some resources to build us something better. There were some fits and starts, but it never happened in my tenure.

Flash forward to my time at Twitter. We’d have creative ideas for things we wanted to make—interactive experiences, stuff that could capture a cultural moment in ways that just lists of Tweets and press blasts couldn’t. The product and engineering teams were always sympathetic, but they’d come back and say they were slammed building whatever new thing leadership was prioritizing that quarter.

The ideas and spirit were always there. We just never had the resources or technical know-how ourselves to actually execute.

What’s different now is that comms people have the capabilities at their fingertips to do the execution themselves.

This past weekend, on a lark, I built this thing called Workplace Buzzword Slots. It’s a slot machine that generates ridiculous workplace thought leadership slop in the style of those post-Davos trend reports that flood LinkedIn every January. You know the ones I mean: about how we’re all entering our “authentic leadership era” or whatever.

It took me a couple hours. I had the concept, the tone, and core mechanics, iterated on the design and features with Claude Code, pushed it to GitHub, deployed it through Vercel for free, spent twelve bucks on a domain, plugged in my Claude API key, and it was live. I’m not saying it’s going to win any engineering awards or a Cannes Lion. But I shipped it. And shipping matters.

The constraint for comms people building things is no longer getting engineering help. The greatest constraint is, quite honestly, that the profession’s use of AI is an inch deep and a mile wide. We’re not thinking about AI as a tool for creating things—interactive experiences, internal tools, games, prototypes—that are themselves a form of communication, the ultimate way of showing rather than telling.2

This is a new surface. And I mean that in the same way you’d talk about media relations or executive comms as distinct surfaces, each with their own logic and possibilities. A press release describes something. A tool demonstrates it. Those are different things.

If you’re early in your career or want to work in comms: don’t just be a user of AI, be a builder with it. You don’t have to be prolific. You don’t have to publish anything! But if you’re not at least tinkering with this stuff, you’re going to get left behind. If you become the person in your organization who can take an idea from concept to shipped thing, you’re going to have a long career.

And if you’re in-house at a tech company, all this matters even more. Your executives and your technical colleagues are all playing around with this stuff on their nights and weekends. They’re building things, shipping side projects, developing intuitions about what’s possible. If you’re doing the same, you gain legitimacy at the table.

I don’t know exactly where this goes. But I know that the comms people who start treating “what can I build?” as a real question are going to end up somewhere interesting. The rest of us will be catching up.

It’s really easy to critique bad communications work. Usually it just hits you in the face. When things go wrong, it’s difficult to miss.

When things go right, though, the strategy and execution feel organic, subtle, almost invisible to most. It’s only those of us who like to look at the machinery that notice when a beautiful plan comes together.

This was one of those weeks for Anthropic. They grabbed momentum by the throat while simultaneously stepping on OpenAI’s. And they did it at the exact moment their rival is reportedly in code-red panic mode over Google’s latest releases.

The Anchor Moments

The week started with an exclusive deep dive in The Verge about Anthropic’s societal impacts team, a nine-person group tasked with finding “inconvenient truths” about AI that companies have incentives not to publicize. The piece reinforced Anthropic’s positioning as the organization that cares most about ethics and safety. It introduced characters, gave readers a window into the team’s working style, and landed quotes like this from team lead Deep Ganguli: “We are going to tell the truth. Because, one, it’s important. It’s the right thing to do. Two, the stakes are high. These are people. The public deserves to know.”

Then came Wednesday. The Financial Times reported that Anthropic had tapped law firm Wilson Sonsini to begin IPO preparations, with a potential listing as soon as 2026. The company’s investors, according to the FT, are “enthusiastic about an IPO, arguing that Anthropic can seize the initiative from its larger rival OpenAI by listing first.”

Later that same day, Dario Amodei took the stage at the New York Times DealBook Summit. He casually dropped that Anthropic’s revenue has grown 10x every year for three years: zero to $100 million in 2023, $100 million to $1 billion in 2024, and projecting $8-10 billion by end of 2025. He talked about the macro questions facing AI, the economic implications, and the responsibilities of the people building these systems.

The FT story breaking the morning of his high-profile appearance was, I’m sure, a complete coincidence!

Then on Thursday, Daniela Amodei sat down with WIRED’s Steven Levy at their Big Interview event in San Francisco. She made the case that the market will reward safe AI, directly countering critics like Trump AI czar David Sacks who had tweeted that Anthropic is “running a sophisticated regulatory capture strategy based on fear-mongering.” Her response? Companies building on Claude want reliability and safety. “No one says, ‘We want a less safe product.’”

(A post-script here after sending the newsletter: I somehow missed that Dario and Daniela also had a Fortune cover story that ran Tuesday *and* Inc. devoted its cover to naming Claude its “Co-founder of the Year” on top of all this, which just goes to show what a thunderclap of attention this week was for them.)

The Orchestration

What makes this week remarkable isn’t any single piece. It’s how they all fit together.

The Verge piece established the safety-first credibility with a human-interest hook. The FT story signaled corporate momentum and business seriousness. Dario’s DealBook appearance let him claim the mantle of responsible AI leadership on one of the biggest business stages of the year while talking hard numbers. Daniela’s Wired conversation reinforced the values message to a tech-native audience while demonstrating that Anthropic’s leadership bench extends beyond its CEO.

Notice what they accomplished: a wonderful pairing of “we’re the responsible ones” and “we’re winning anyway.” The safety positioning and the business momentum story reinforced each other. Being careful isn’t holding them back. The market is actually rewarding it.

Every communications person reading this knows how hard this is to pull off. Anchors like the DealBook and Wired appearances were probably set months in advance. The Anthropic comms team clearly looked at those dates and asked: What can we package around these moments that furthers our goals? What story do we want the world to see this week?

The timing context matters too. All of this happened while OpenAI is reportedly spiraling about Google. When your primary competitor is in firefighting mode, you run your offense. While they probably plotted at least a few of these components well in advance (conference appearances like Dario and Daniela’s in particular), Anthropic did exactly that. Their success now appears more inevitable than ever. They have business momentum, a clear sense of what they’re building and for whom, and a bright north star guiding them on values.

Compare this to the comms posture we’ve seen from other AI leaders lately. I wrote this year about Zuckerberg’s “Personal Superintelligence” essay, which was all hat and no cattle, vibe writing with no substance.

Anthropic, by contrast, showed their work. They gave journalists access to their safety team. They put executives on stage to answer hard questions. They let reporters dig into their operations and culture. They trusted that transparency would work in their favor. And it did.

What To Take From This

Game recognizes game. This was a masterclass. A few lessons worth extracting:

Build around anchors. Major executive appearances get scheduled months ahead. The best comms teams treat those dates as tentpoles and work backward to create complementary coverage that builds a cohesive narrative.

Make sure your business story and values story reinforce each other. Anthropic didn’t position safety as a tradeoff. They positioned it as an advantage. That’s harder to do than it sounds, and it requires genuine alignment between what you say and what you do.

Put your people on stage when you have a good story to tell. Both Amodeis did real interviews with real journalists who asked real questions. Neither hid in controlled environments or stuck to softball friendly outlets. That builds credibility in ways that press releases and blog posts never will.

Know when to run offense. When your competitor is distracted, don’t sit on your hands. Make your inevitability feel... inevitable.

I didn’t talk to any comms friends or acquaintances at Anthropic before writing this, by the way, though I do broadly think they’re a talented group of folks. I just watched it unfold in real time, appreciating the craftsmanship. This is what it looks like when thoughtful planning meets skillful execution. A tip of the cap.

I’ve been running an informal poll lately. When I’ve been catching up with comms leaders—people running teams at startups and established tech companies alike—I ask them: If you had to rebuild your comms function from scratch tomorrow, what would you do differently?

The answer is almost universal. They’d build a video team.

Not “invest more in video,” not “hire a video-forward agency,” not “get one talented Zoomer with an iPhone and a ring light,” an actual, dedicated, in-house video team. A director of photography who understands visual storytelling, an editor, and an audio specialist. Three people who can work together as a creative unit. That’s the minimum viable video team.

The way people consume information has shifted, and our profession hasn’t caught up. US adults now spend six hours and 45 minutes per day consuming video content across streaming, traditional TV, YouTube, and social platforms. They spend 16 to 17 minutes reading for personal interest. That’s a ratio of roughly 24 to 1. Look at your team or agency. Are you spending a comparable ratio of time on video-focused and text-focused-efforts or anything close to that? My guess is decidedly not. In fact, it might be the inverse.

This isn’t a generational quirk that will revert to the mean. Among Americans ages 15 to 24, only 9.5 percent read more than 20 minutes per day for pleasure. Approximately 80 percent engage with screens for 20-plus minutes daily. According to Deloitte’s 2025 Digital Media Trends survey, 56 percent of Gen Z considers social media content more relevant than traditional TV shows and movies. Half feel a stronger personal connection to social media creators than to television actors.

Right now, video capability lives almost entirely outside of companies. You hire a production company or a freelance crew when you need something shot. There are good reasons for this arrangement. The videographers I know value their freedom: the ability to work on projects that interest them creatively, to move between industries and clients, to avoid being locked into one company’s needs. It’s the same reason talented people start agencies or consultancies of any kind.1

But the imperative for companies to bring this function in-house has never been stronger. When video is a sometimes thing you hire out for, it stays peripheral to your communications strategy. When it’s an always-available capability sitting next to your comms team, it becomes central and second nature.

Don’t mistake this as me calling for the PR version of Pivot to Video at the expense of text-based output and text-based professionals. This isn’t an “either/or” situation, it’s an “and” situation. The truth is the modern media ecosystem demands more of everything just to break through.

And not all content or messages lend itself toward video consumption. Communications that index toward precision and reference-ability, especially financial and crisis communications, still lean toward text, especially in an age where machine-readability is becoming so much more important.

There are also huge audience-specific considerations. The data I presented above is top-line. Want to target 50-to-70-year-old policymakers in DC? Video’s in the mix, but in a style very different from a video game rollout to 13-to 25-year-old males whose time with text-based media we can probably handicap at “Cro-Magnon”. CFOs aren’t going to want to sit for a 10-minute video. Give them a doc they can scan in 90 seconds.

It gives me no pleasure to write any of this. I am, at my core, a word person.2 I default to thinking in prose first and pictures second. It’s what drew me to Twitter over Instagram back in the day. I love the craft of it, the precision it demands. But I can’t let that love blind me to how people actually communicate now, and neither can you.

So 2026 is the year I get serious about video: getting over the discomfort of recording myself, learning to edit, understanding the visual grammar of the medium, and building video into my own communications alongside the writing I do here. It feels uncomfortable in the way that acquiring any new skill does, but that discomfort is a signal that it matters.

I’d challenge everyone reading this to think about the same thing. What are you building into your comms work with video for the coming year? How central is it to your strategy versus how central it should be?

And since we’re heading into a new year, I want to hear from you. Who are the most talented video people you work with? The freelancers and small shops who do exceptional work and deserve more recognition? Email me with your recommendations, and I’ll compile a list in an upcoming edition to shine a light on the people doing this well.