the smartphone, and a host of software technologies built on it,3 have birthed what is essentially a parallel, non-union, motion-picture industry consisting of YouTube, TikTok, Instagram, Twitch, Twitter, and their many other social-video rivals, all of which rely on the free or barely compensated labor product of people acting as de facto writers, directors, producers, actors, and crew. Even if they’d never see it this way, YouTubers and TikTokers are effectively competing with Hollywood over the idle hours of consumers everywhere; more to the point, they’re doing what any non-union workforce does in an insufficiently organized industry: driving down labor compensation.

Almost no one I know has work; most people’s agents and managers have more or less told them there won’t be jobs until 2025. An executive recently told a friend that the only things getting made this year are “ultra premium limiteds,” which sounds like a kind of tampon but actually just means “six-episode miniseries that an A-List star wants to do.”

YouTubers’ lack of collective bargaining power isn’t just bad for me and other guild members; it’s bad for the YouTubers themselves. Ask any professional or semi-professional streamer what they think of the platform and you’ll hear a litany of complaints about its opacity and inconsistency

now the streaming gold rush—the era that made Dickinson—is over. In the spring of 2022, the Federal Reserve began raising interest rates after years of nearly free credit, and at roughly the same time, Wall Street began calling in the streamers’ bets. The stock prices of nearly all the major companies with streaming platforms took precipitous falls, and none have rebounded to their prior valuation.

Thanks to decades of deregulation and a gush of speculative cash that first hit the industry in the late Aughts, while prestige TV was climbing the rungs of the culture, massive entertainment and media corporations had been swallowing what few smaller companies remained, and financial firms had been infiltrating the business, moving to reduce risk and maximize efficiency at all costs, exhausting writers in evermore unstable conditions.

The new effective bosses of the industry—colossal conglomerates, asset-management companies, and private-equity firms—had not been simply pushing workers too hard and grabbing more than their fair share of the profits. They had been stripping value from the production system like copper pipes from a house—threatening the sustainability of the studios themselves. Today’s business side does not have a necessary vested interest in “the business”—in the health of what we think of as Hollywood, a place and system in which creativity is exchanged for capital. The union wins did not begin to address this fundamental problem.

To the new bosses, the quantity of money that studios had been spending on developing screenplays—many of which would never be made—was obvious fat to be cut, and in the late Aughts, executives increasingly began offering one-step deals, guaranteeing only one round of pay for one round of work. Writers, hoping to make it past Go, began doing much more labor—multiple steps of development—for what was ostensibly one step of the process. In separate interviews, Dana Stevens, writer of The Woman King, and Robin Swicord described the change using exactly the same words: “Free work was encoded.” So was safe material. In an effort to anticipate what a studio would green-light, writers incorporated feedback from producers and junior executives, constructing what became known as producer’s drafts. As Rodman explained it: “Your producer says to you, ‘I love your script. It’s a great first draft. But I know what the studio wants. This isn’t it. So I need you to just make this protagonist more likable, and blah, blah, blah.’ And you do it.”

By 2019, the major Hollywood agencies had been consolidated into an oligopoly of four companies that controlled more than 75 percent of WGA writers’ earnings. And in the 2010s, high finance reached the agencies: by 2014, private equity had acquired Creative Artists Agency and William Morris Endeavor, and the latter had purchased IMG. Meeting benchmarks legible to the new bosses—deals actually made, projects off the ground—pushed agents to function more like producers, and writers began hearing that their asking prices were too high.

Executives, meanwhile, increasingly believed that they’d found their best bet in “IP”: preexisting intellectual property—familiar stories, characters, and products—that could be milled for scripts. As an associate producer of a successful Aughts IP-driven franchise told me, IP is “sort of a hedge.” There’s some knowledge of the consumer’s interest, he said. “There’s a sort of dry run for the story.” Screenwriter Zack Stentz, who co-wrote the 2011 movies Thor and X-Men: First Class, told me, “It’s a way to take risk out of the equation as much as possible.”

Multiple writers I spoke with said that selecting preexisting characters and cinematic worlds gave executives a type of psychic edge, allowing them to claim a degree of creative credit. And as IP took over, the perceived authority of writers diminished. Julie Bush, a writer-producer for the Apple TV+ limited series Manhunt, told me, “Executives get to feel like the author of the work, even though they have a screenwriter, like me, basically create a story out of whole cloth.” At the same time, the biggest IP success story, the Marvel Cinematic Universe, by far the highest-earning franchise of all time, pioneered a production apparatus in which writers were often separated from the conception and creation of a movie’s overall story.

Joanna Robinson, co-author of the book MCU: The Reign of Marvel Studios, told me that the writers for WandaVision, a Marvel show for Disney+, had to craft almost the entirety of the series’ single season without knowing where their work was ultimately supposed to arrive: the ending remained undetermined, because executives had not yet decided what other stories they might spin off from the show.

The streaming ecosystem was built on a wager: high subscriber numbers would translate to large market shares, and eventually, profit. Under this strategy, an enormous amount of money could be spent on shows that might or might not work: more shows meant more opportunities to catch new subscribers. Producers and writers for streamers were able to put ratings aside, which at first seemed to be a luxury. Netflix paid writers large fees up front, and guaranteed that an entire season of a show would be produced. By the mid-2010s, the sheer quantity of series across the new platforms—what’s known as “Peak TV”—opened opportunities for unusually offbeat projects (see BoJack Horseman, a cartoon for adults about an equine has-been sitcom star), and substantially more shows created by women and writers of color. In 2009, across cable, broadcast, and streaming, 189 original scripted shows aired or released new episodes; in 2016, that number was 496. In 2022, it was 849.

supply soon overshot demand. For those who beat out the competition, the work became much less steady than it had been in the pre-streaming era. According to insiders, in the past, writers for a series had usually been employed for around eight months, crafting long seasons and staying on board through a show’s production. Junior writers often went to the sets where their shows were made and learned how to take a story from the page to the screen—how to talk to actors, how to stay within budget, how to take a studio’s notes—setting them up to become showrunners. Now, in an innovation called mini-rooms, reportedly first ventured by cable channels such as AMC and Starz, fewer writers were employed for each series and for much shorter periods—usually eight to ten weeks but as little as four.

Writers in the new mini-room system were often dismissed before their series went to production, which meant that they rarely got the opportunity to go to set and weren’t getting the skills they needed to advance. Showrunners were left responsible for all writing-related tasks when these rooms shut down. “It broke a lot of showrunners,” the A-list film and TV writer told me. “Physically, mentally, financially. It also ruined a lot of shows.”

The price of entry for working in Hollywood had been high for a long time: unpaid internships, low-paid assistant jobs. But now the path beyond the entry level was increasingly unclear. Jason Grote, who was a staff writer on Mad Men and who came to TV from playwriting, told me, “It became like a hobby for people, or something more like theater—you had your other day jobs or you had a trust fund.” Brenden Gallagher, a TV writer a decade in, said, “There are periods of time where I work at the Apple Store. I’ve worked doing data entry, I’ve worked doing research, I’ve worked doing copywriting.” Since he’d started in the business in 2014, in his mid-twenties, he’d never had more than eight months at a time when he didn’t need a source of income from outside the industry.

“There was this feeling,” the head of the midsize studio told me that day at Soho House, “during the last ten years or so, of, ‘Oh, we need to get more people of color in writers’ rooms.’ ” But what you get now, he said, is the black or Latino person who went to Harvard. “They’re getting the shot, but you don’t actually see a widening of the aperture to include people who grew up poor, maybe went to a state school or not even, and are just really talented. That has not happened at all.”

“The Sopranos does not exist without David Chase having worked in television for almost thirty years,” Blake Masters, a writer-producer and creator of the Showtime series Brotherhood, told me. “Because The Sopranos really could not be written by somebody unless they understood everything about television, and hated all of it.” Grote said much the same thing: “Prestige TV wasn’t new blood coming into Hollywood as much as it was a lot of veterans that were never able to tell these types of stories, who were suddenly able to cut through.”

The threshold for receiving the viewership-based streaming residuals is also incredibly high: a show must be viewed by at least 20 percent of a platform’s domestic subscribers “in the first 90 days of release, or in the first 90 days in any subsequent exhibition year.” As Bloomberg reported in November, fewer than 5 percent of the original shows that streamed on Netflix in 2022 would have met this benchmark. “I am not impressed,” the A-list writer told me in January. Entry-level TV staffing, where more and more writers are getting stuck, “is still a subsistence-level job,” he said. “It’s a job for rich kids.”

Brenden Gallagher, who echoed Conover’s belief that the union was well-positioned to gain more in 2026, put it this way: “My view is that there was a lot of wishful thinking about achieving this new middle class, based around, to paraphrase 30 Rock, making it 1997 again through science or magic. Will there be as big a working television-writer cohort that is making six figures a year consistently living in Los Angeles as there was from 1992 to 2021? No. That’s never going to come back.”

As for what types of TV and movies can get made by those who stick around, Kelvin Yu, creator and showrunner of the Disney+ series American Born Chinese, told me: “I think that there will be an industry move to the middle in terms of safer, four-quadrant TV.” (In L.A., a “four-quadrant” project is one that aims to appeal to all demographics.) “I think a lot of people,” he said, “who were disenfranchised or marginalized—their drink tickets are up.” Indeed, multiple writers and executives told me that following the strike, studio choices have skewed even more conservative than before. “It seems like buyers are much less adventurous,” one writer said. “Buyers are looking for Friends.”

The film and TV industry is now controlled by only four major companies, and it is shot through with incentives to devalue the actual production of film and television.

The entertainment and finance industries spend enormous sums lobbying both parties to maintain deregulation and prioritize the private sector. Writers will have to fight the studios again, but for more sweeping reforms. One change in particular has the potential to flip the power structure of the industry on its head: writers could demand to own complete copyright for the stories they create. They currently have something called “separated rights,” which allow a writer to use a script and its characters for limited purposes. But if they were to retain complete copyright, they would have vastly more leverage. Nearly every writer I spoke with seemed to believe that this would present a conflict with the way the union functions. This point is complicated and debatable, but Shawna Kidman and the legal expert Catherine Fisk—both preeminent scholars of copyright and media—told me that the greater challenge is Hollywood’s structure. The business is currently built around studio ownership. While Kidman found the idea of writer ownership infeasible, Fisk said it was possible, though it would be extremely difficult. Pushing for copyright would essentially mean going to war with the studios. But if things continue on their current path, writers may have to weigh such hazards against the prospect of the end of their profession. Or, they could leave it all behind.

if you just think about the business model of the internet as — there’s a box that you can upload some content into, and then there’s an algorithm between you and an audience, and some audience will find the stuff you put in the box, and then you put an infinity amount of stuff into the box, all of that breaks.

more and more of the stuff that you consume is designed around pushing you towards a transaction. That’s weird. I think there’s a vast amount of white space in the culture for things that are not directly transactable.

We constantly ask huge amounts of the population to do things that are very rote. Keep inputting this data on forms, keep filling out this tax form. Some lawyers arguing for the Supreme Court, a lot of them just write up various contracts. And that’s a good job in the sense that it pays well, it’s inside work, but it doesn’t ask you to be that full of a human being.

I think a lot of organizations are not set up for a lot of people to use judgment and discernment. They treat a lot of people like machines, and they don’t want them doing things that are complicated and step out of line and poke at the assumptions in the Excel doc. They want the Excel doc ported over without any mistakes.

I think a lot of organizations are not set up for a lot of people to use judgment and discernment. They treat a lot of people like machines, and they don’t want them doing things that are complicated and step out of line and poke at the assumptions in the Excel doc.

I distinctly remember life before computers. It’s an experience that I had quite viscerally. And that shapes my view of these tools. It shapes my view of these companies. Well, there’s a huge generation now that only grew up in this way. There’s a teenage generation right now that is only growing up in this way. And I think their natural inclination is to say, well, this sucks. I want my own thing. I want my own system of consuming information. I want my own brands and institutions.And I don’t think that these big platforms are ready for that moment. I think that they think they can constantly be information monopolies while they are fending off A.I.-generated content from their own A.I. systems. So somewhere in there all of this stuff does break. And the optimism that you are sensing from me is, well, hopefully we build some stuff that does not have these huge dependencies on platform companies that have no interest at the end of the line except a transaction.

these models in their most reductive essence are just statistical representations of the past. They are not great at new ideas.And I think that the power of human beings sort of having new ideas all the time, that’s the thing that the platforms won’t be able to find. That’s why the platforms feel old. Social platforms like enter a decay state where everyone’s making the same thing all the time. It’s because we’ve optimized for the distribution, and people get bored and that boredom actually drives much more of the culture than anyone will give that credit to, especially an A.I. developer who can only look backwards.

the idea is, in my mind at least, that those people who curate the internet, who have a point of view, who have a beginning and middle, and an end to the story they’re trying to tell all the time about the culture we’re in or the politics we’re in or whatever. They will actually become the centers of attention and you cannot replace that with A.I. You cannot replace that curatorial function or that guiding function that we’ve always looked to other individuals to do.

I think as the flood of A.I. comes to our distribution networks, the value of having a powerful individual who curates things for people, combined with a powerful institution who protects their integrity actually will go up. I don’t think that’s going to go down.

The ability of generative AI tools to analyse huge datasets can also be used to help spark creative inspiration. This can help us if we’re struggling for time or battling writer’s block. For example, if a social media manager is looking for ideas on how to engage alumni on Instagram, they could ask ChatGPT for suggestions based on recent popular content. They could then pick the best ideas from ChatGPT’s response and adapt them. We may use these tools in a similar way to how we ask a colleague for an idea on how to approach a creative task.

We may use these tools in a similar way to how we use search engines for researching topics and will always carefully fact-check before publication.

we will not publish any press releases, articles, social media posts, blog posts, internal emails or other written content that is 100% produced by generative AI. We will always apply brand guidelines, fact-check responses, and re-write in our own words.

We may use these tools to make minor changes to a photo to make it more usable without changing the subject matter or original essence. For example, if a website manager needs a photo in a landscape ratio but only has one in a portrait ratio, they could use Photoshop’s inbuilt AI tools to extend the background of the photo to create an image with the correct dimensions for the website.

What we have now is a profusion of well-cast, sleekly produced competence. We have tasteful remakes of familiar titles. We have the evidence of healthy budgets spent on impressive locations. We have good-enough new shows that resemble great old ones.

Put these two forces together — a rising level of talent and production competence on the one hand, the pressure to deliver versions of something viewers already like on the other hand — and what do you get? You get a whole lot of Mid.

MID IS NOT the mediocre TV of the past. It’s more upscale. It is the aesthetic equivalent of an Airbnb “modern farmhouse” renovation, or the identical hipster cafe found in medium-sized cities all over the planet. It’s nice! The furniture is tasteful, they’re playing Khruangbin on the speakers, the shade-grown coffee is an improvement on the steaming mug of motor oil you’d have settled for a few decades ago.

Mid is fine, though. It’s good enough.

Mid TV, on the other hand, almost can’t be bad for some of the same reasons that keep it from being great. It’s often an echo of the last generation of breakthrough TV (so the highs and lows of “Game of Thrones” are succeeded by the faithful adequacy of “House of the Dragon”).

As more people drop cable TV for streaming, their incentives change. With cable you bought a package of channels, many of which you would never watch, but any of which you might.

So where HBO used to boast that it was “not TV,” modern streamers send the message, “We’ll give you a whole lot of TV.” It can seem like their chief goal is less to produce standout shows than to produce a lot of good-looking thumbnails.

Cities are commonly mapped and surveilled like the internet, said to be made up of “networks” and clusters of “users.”

A City Is Not a Tree can provide us with some answers. As Alexander argued almost 60 years ago, our minds are inclined to categorize the world as a tree, but an organic society and city actually resembles a semilattice. And just like with a city, organizing the internet like a tree stifles it completely.

The internet hasn’t become a tree, but there are certainly those who would like it to resemble one. Both leading tech platforms and governments believe themselves to be capable of containing information and separating its parts. The process started in earnest after the Arab Spring (2010-2012), when it became clear that online activity could produce shocks with real-world consequences. A growing pessimism about technology in the hands of the public developed at the top, as the interests of both “public safety” and profit converged to more deliberately plan the internet and mediate its branches. Simply put, complex systems are easier to surveil when information is neatly siloed into branches. It also simplifies data collection for advertisers.

Overlap on the internet is made possible through search and indexing which has, in almost all cases, badly declined.28 Google, as the leading indexer, has been the prime target of enshittification despite its market dominance increasing.29 Additionally, most platforms are walled gardens that are not easily searchable, their content only being found because it was reposted in another walled garden. Platforms have an interest in making sure users stay in their domain as much as possible. This makes overlap especially difficult by design, and so much of the internet now exists as islands on the periphery as a result. Effectively, that which would make a semilattice of the internet dynamic and alive is being dismantled.

Like a city, the internet is a receptacle for life, and how it organizes itself has consequences for the psychological well-being of its users.

Guadagnino brought them Challengers, which will be released this month. Reznor said, “He started us down a path, saying, ‘What if it was very loud techno music through the whole film?’ ” (This is exactly what it turned out to be.)“I wish I had his notes,” Ross said of Guadagnino. “His notes were so fucking funny on what each piece was meant to do.”“Oh, yeah,” Reznor said. “ ‘Unending homoerotic desire.’ It was all a variation on those three words.”

inside look at how Perplexity builds product—which to me feels like what the future of product development will look like for many companies:AI-first: They’ve been asking AI questions about every step of the company-building process, including “How do I launch a product?” Employees are encouraged to ask AI before bothering colleagues.Organized like slime mold: They optimize for minimizing coordination costs by parallelizing as much of each project as possible.Small teams: Their typical team is two to three people. Their AI-generated (highly rated) podcast was built and is run by just one person.Few managers: They hire self-driven ICs and actively avoid hiring people who are strongest at guiding other people’s work.A prediction for the future: Johnny said, “If I had to guess, technical PMs or engineers with product taste will become the most valuable people at a company over time.”

Typical projects we work on only have one or two people on it. The hardest projects have three or four people, max. For example, our podcast is built by one person end to end. He’s a brand designer, but he does audio engineering and he’s doing all kinds of research to figure out how to build the most interactive and interesting podcast. I don’t think a PM has stepped into that process at any point.

We leverage product management most when there’s a really difficult decision that branches into many directions, and for more involved projects.

The hardest, and most important, part of the PM’s job is having taste around use cases. With AI, there are way too many possible use cases that you could work on. So the PM has to step in and make a branching qualitative decision based on the data, user research, and so on.

a big problem with AI is how you prioritize between more productivity-based use cases versus the engaging chatbot-type use cases.

we look foremost for flexibility and initiative. The ability to build constructively in a limited-resource environment (potentially having to wear several hats) is the most important to us.

We look for strong ICs with clear quantitative impacts on users rather than within their company. If I see the terms “Agile expert” or “scrum master” in the resume, it’s probably not going to be a great fit.

My goal is to structure teams around minimizing “coordination headwind,” as described by Alex Komoroske in this deck on seeing organizations as slime mold. The rough idea is that coordination costs (caused by uncertainty and disagreements) increase with scale, and adding managers doesn’t improve things. People’s incentives become misaligned. People tend to lie to their manager, who lies to their manager. And if you want to talk to someone in another part of the org, you have to go up two levels and down two levels, asking everyone along the way.

Instead, what you want to do is keep the overall goals aligned, and parallelize projects that point toward this goal by sharing reusable guides and processes.

Perplexity has existed for less than two years, and things are changing so quickly in AI that it’s hard to commit beyond that. We create quarterly plans. Within quarters, we try to keep plans stable within a product roadmap. The roadmap has a few large projects that everyone is aware of, along with small tasks that we shift around as priorities change.

Each week we have a kickoff meeting where everyone sets high-level expectations for their week. We have a culture of setting 75% weekly goals: everyone identifies their top priority for the week and tries to hit 75% of that by the end of the week. Just a few bullet points to make sure priorities are clear during the week.

All objectives are measurable, either in terms of quantifiable thresholds or Boolean “was X completed or not.” Our objectives are very aggressive, and often at the end of the quarter we only end up completing 70% in one direction or another. The remaining 30% helps identify gaps in prioritization and staffing.

At the beginning of each project, there is a quick kickoff for alignment, and afterward, iteration occurs in an asynchronous fashion, without constraints or review processes. When individuals feel ready for feedback on designs, implementation, or final product, they share it in Slack, and other members of the team give honest and constructive feedback. Iteration happens organically as needed, and the product doesn’t get launched until it gains internal traction via dogfooding.

all teams share common top-level metrics while A/B testing within their layer of the stack. Because the product can shift so quickly, we want to avoid political issues where anyone’s identity is bound to any given component of the product.

We’ve found that when teams don’t have a PM, team members take on the PM responsibilities, like adjusting scope, making user-facing decisions, and trusting their own taste.

What’s your primary tool for task management, and bug tracking?Linear. For AI products, the line between tasks, bugs, and projects becomes blurred, but we’ve found many concepts in Linear, like Leads, Triage, Sizing, etc., to be extremely important. A favorite feature of mine is auto-archiving—if a task hasn’t been mentioned in a while, chances are it’s not actually important.The primary tool we use to store sources of truth like roadmaps and milestone planning is Notion. We use Notion during development for design docs and RFCs, and afterward for documentation, postmortems, and historical records. Putting thoughts on paper (documenting chain-of-thought) leads to much clearer decision-making, and makes it easier to align async and avoid meetings.Unwrap.ai is a tool we’ve also recently introduced to consolidate, document, and quantify qualitative feedback. Because of the nature of AI, many issues are not always deterministic enough to classify as bugs. Unwrap groups individual pieces of feedback into more concrete themes and areas of improvement.

High-level objectives and directions come top-down, but a large amount of new ideas are floated bottom-up. We believe strongly that engineering and design should have ownership over ideas and details, especially for an AI product where the constraints are not known until ideas are turned into code and mock-ups.

Big challenges today revolve around scaling from our current size to the next level, both on the hiring side and in execution and planning. We don’t want to lose our core identity of working in a very flat and collaborative environment. Even small decisions, like how to organize Slack and Linear, can be tough to scale. Trying to stay transparent and scale the number of channels and projects without causing notifications to explode is something we’re currently trying to figure out.

Companionship content is long-form content that can be consumed passively — allowing the consumer to be incompletely attentive, and providing a sense of relaxation, comfort, and community.

Interestingly, each individual “unit” of music is short-form (e.g. a 3-5 minute song), but how we consume it tends to be long-form and passive (i.e. via curated stations, lengthy playlists, or algorithms that adapt to our taste).

If you’re rewatching a show or movie, it’s likely to be companionship content. (Life-like conversational sitcoms can be consumed this way too.) As streaming matures, platforms are growing their passive-watch library.

content isn’t always prescriptively passive, rather it’s rooted in how consumers engage it.

That said, some content lends better to being companionship content: Long-form over short. Conversational over action. Simple plot versus complex.

Short-form video requires more attention & action in a few ways: Context switching, i.e. wrapping your head around a new piece of context every 30 seconds, especially if they’re on unrelated topics with different styles Judgment & decision-making, i.e. contemplating whether to keep watching or swipe to the next video effectively the entire time you’re watching a video Multi-sensory attention, i.e. default full-screen and requires visual and audio focus, especially since videos are so short that you can easily lose context Interactive components, e.g. liking, saving, bookmarking,

With how performative, edited, and algorithmically over-optimized it is, TikTok feels sub-human. TikTok has quickly become one of the most goal-seeking places on earth. I could easily describe TikTok as a global focus group for commercials. It’s the product personification of a means to an end, and the end is attention.

even TikTok creators are adapting the historically rigid format to appeal to more companionship-esque emotions and improve retention.

When we search for a YouTube video to watch, we often want the best companion for the next hour and not the most entertaining content.

While short-form content edits are meant to be spectacular and attention-grabbing, long-form content tends to be more subtle in its emotional journey Long-form engagement with any single character or narrative or genre lets you develop stronger understanding, affinity, and parasocial bonds Talk-based content (e.g. talk shows, podcasts, comedy, vlogs, life-like sitcoms) especially evokes a feeling of companionship and is less energy-draining The trends around loneliness and the acceleration of remote work has and will continue to make companionship content even more desirable As we move into new technology frontiers, we might unlock novel types of companionship content itself, but I’d expect this to take 5-10 years at least

TikTok is where you connect with an audience, YouTube is where you consolidate it.5 Long-form content also earns creators more, with YouTube a standout in revenue sharing.

YouTube paid out $16 billion to creators in 2022 (which is 55% of its annual $30 billion in revenue) and the other four social networks paid out about $1 billion each from their respective creator funds. In total, that yields $20 billion.”

Mr. Beast, YouTube’s top creator, says YouTube is now the final destination, not “traditional” hollywood stardom which is the dream of generations past. Creators also want to funnel audiences to apps & community platforms where they can own user relationships, rely less on algorithms, engage more directly and deeply with followers, and enable follower-to-follower engagement too

Interestingly of course, an increasing amount of short-form video, including formats like clips and edits, seems to be made from what originally was long-form content.8 And in return, these recycled short-form videos can drive tremendous traffic to long-form formats and platforms.

90% of people use a second screen while watching TV. We generally talk about “second screen” experiences in the context of multiple devices, but you can have complementary apps and content running on the same device — you can have the “second screen” on the same screen.

YouTube itself also cites a trend of people putting YouTube on their real TV screens: “There are more Americans gathering around the living room TV to watch YouTube than any other platform. Why? Put simply, people want choices and variety … It’s a one stop shop for video viewing. Think about something historically associated with linear TV: Sports. Now, with [our NFL partnership], people can not only watch the games, but watch post-game highlights and commentary in one place.”

If I were to build an on-demand streaming product or any kind of content product for that matter, I’d build for the companionship use case — not only because I think it has a higher ceiling of consumer attention, but also because it can support more authentic, natural, human engagement.

All the creators that are ‘made’ on TikTok are looking for a place to go to consolidate the attention they’ve amassed. TikTok is commercials. YouTube is TV. (Though yes, they’re both trying to become each other).

certainly AI and all the new creator tools enabled by it will help people mix and match and remix long and short formats all day, blurring the historically strict distinctions between them. It’ll take some time before we see a new physical product + content combo thrive, and meanwhile the iPhone and its comps will be competing hard to stay the default device.

The new default seems to be that we’re not lonely as long as we’re streaming. We can view this entirely in a negative light and talk about how much the internet and media is contributing to the loneliness epidemic. Or we could think about how to create media for good. Companionship content can be less the quick dopamine-hit-delivering clips and more of this, and perhaps even truly social.

Long-form wants to become the conversational third space for consumers too. The “comments” sections of TikTok, YouTube and all broadcast platforms are improving, but they still have a long way to go before they become even more community-oriented.

I’m not an “AI-head” but I am more curious about what it’s going to enable in long-form content than all the short-form clips it’s going to help generate and illustrate, etc.

The foreground tends to be utilities or low-cognitive / audio effort (text or silent video). Tiktok is a foreground app for now, YouTube is both (and I’d say trending towards being background).

Forget trying to decide what your life’s destiny is. That’s too grand. Instead, just figure out what you should do in the next 2 years.

Try to define yourself by what you love and embrace, rather than what you hate and refuse.

Where you live—what city, what country—has more impact on your well being than any other factor. Where you live is one of the few things in your life you can choose and change.

Once a month take a different route home, enter your house by a different door, and sit in a different chair at dinner. No ruts.

Every now and then throw a memorable party. The price will be steep, but long afterwards you will remember the party, whereas you won’t remember how much is in your checking account.

Most arguments are not really about the argument, so most arguments can’t be won by arguing.

invent your own definition of success. Shoot your arrows first and then paint a bull’s eye around where they land. You’re the winner!

There should be at least one thing in your life you enjoy despite being no good at it. This is your play time, which will keep you young. Never apologize for it.

You have 5 minutes to act on a new idea before it disappears from your mind.

The patience you need for big things, is developed by your patience with the little things.

When you are stuck or overwhelmed, focus on the smallest possible thing that moves your project forward.

For steady satisfaction, work on improving your worst days, rather than your best days.

Your decisions will become wiser when you consider these three words: “…and then what?” for each choice.

If possible, every room should be constructed to provide light from two sides.  Rooms with light from only one side are used less often, so when you have a choice, go with light from two sides.

There is a profound difference between thinking less of yourself (not useful), and thinking of yourself less (better).

Always ask yourself: what would change my mind?

Becoming one-of-a-kind is not a solo job. Paradoxically you need everyone else in the world to help make you unique.

If you need emergency help from a bystander, command them what to do. By giving them an assignment, you transform them from bewildered bystander to a responsible assistant.

The most common mistake we make is to do a great job on an unimportant task.

Don’t work for a company you would not invest money in, because when you are working you are investing the most valuable thing you have: your time.

Fail forward. Failing is not a disgrace if you keep failing better.

Do not cling to a mistake just because you spent a lot of time making it.

For small tasks the best way to get ready is to do it immediately.

What others want from you is mostly to be seen. Let others know you see them.

When you try something new, don’t think of it as a matter of success / failure, but as success / learning to succeed.

use your honesty as a gift not as a weapon. Your honesty should benefit others.

A good sign that you are doing the kind of work you should be doing is that you enjoy the tedious parts that other people find tortuous.

Celebrating the success of others costs you nothing, and increases the happiness of everyone, including you.

To tell a good story, you must reveal a surprise; otherwise it is just a report.

a long horizon allows you to compound small advances into quite large achievements.

Often ideas are rejected because of the tone of voice they are wrapped in. Humility covers many blemishes.

When you are right, you are learning nothing.

Very small things accumulate until they define your larger life. Carefully choose your everyday things.

If you are impressed with someone’s work, you should tell them, but even better, tell their boss.

Humility is mostly about being very honest about how much you owe to luck.

The phrase a picture is worth a thousand words has two popular origin stories. One version credits advertising executive Frederick R. Barnard, who attributed the phrase to an ancient Chinese proverb. The closest Chinese equivalent translates to “Hearing something a hundred times isn’t better than seeing it once.” In other words, the Chinese Origin was made up: “…the Chinese derivation was pure invention. Many things had been thought to be ‘worth ten thousand words’ well before pictures got in on the act;”

the true origin of the proverb is not Chinese but adspeak.3 It shows how the phrase has morphed into a commercial, facile cliche.

Letting images and pictures compete for supremacy reduces the complex relationship between images and words into a direct, quantifiable comparison. Words and images function differently

A few carefully chosen words can say what 1,000 stock images cannot. The right image can counter cynicism, closed-mindedness, or an automatic dismissal of a convincing argument.

Tell your audience how you interpret the image. What the image means.

Use images to complement, not repeat or overshadow, the text. Get rid of images that are just there to add color.

Stock images are clichés. Clichés can be easily turned on their head because of their simplistic topic. You want to communicate that you’re diverse and you end up telling people that you’re a company run by a minority. Or you want to communicate success, but the focus on two middle-aged white people ends up communicating their privilege.

Whether you like it or not, people will read into this picture as well and they won’t find a lot of valuable or advantageous information in it. It again mostly says: “This boring website thinks that I don’t see that this is a meaningless stock image.”

Pictures have an impact when they tell a story that only a picture can tell.

if you had showed VisiCalc to a lawyer or a graphic designer, their response might well have been ‘that’s amazing, and maybe my book-keeper should see this, but I don’t do that’. Lawyers needed a word processor, and graphic designers needed (say) Postscript, Pagemaker and Photoshop, and that took longer.

I’ve been thinking about this problem a lot in the last 18 months, as I’ve experimented with ChatGPT, Gemini, Claude and all the other chatbots that have sprouted up: ‘this is amazing, but I don’t have that use-case’.

A spreadsheet can’t do word processing or graphic design, and a PC can do all of those but someone needs to write those applications for you first, one use-case at a time.

no matter how good the tech is, you have to think of the use-case. You have to see it. You have to notice something you spend a lot of time doing and realise that it could be automated with a tool like this.

Some of this is about imagination, and familiarity. It reminds me a little of the early days of Google, when we were so used to hand-crafting our solutions to problems that it took time to realise that you could ‘just Google that’.

This is also, perhaps, matching a classic pattern for the adoption of new technology: you start by making it fit the things you already do, where it’s easy and obvious to see that this is a use-case, if you have one, and then later, over time, you change the way you work to fit the new tool.

The concept of product-market fit is that normally you have to iterate your idea of the product and your idea of the use-case and customer towards each other - and then you need sales.

Meanwhile, spreadsheets were both a use-case for a PC and a general-purpose substrate in their own right, just as email or SQL might be, and yet all of those have been unbundled. The typical big company today uses hundreds of different SaaS apps, all them, so to speak, unbundling something out of Excel, Oracle or Outlook. All of them, at their core, are an idea for a problem and an idea for a workflow to solve that problem, that is easier to grasp and deploy than saying ‘you could do that in Excel!’ Rather, you instantiate the problem and the solution in software - ‘wrap it’, indeed - and sell that to a CIO. You sell them a problem.

there’s a ‘Cambrian Explosion’ of startups using OpenAI or Anthropic APIs to build single-purpose dedicated apps that aim at one problem and wrap it in hand-built UI, tooling and enterprise sales, much as a previous generation did with SQL.

Back in 1982, my father had one (1) electric drill, but since then tool companies have turned that into a whole constellation of battery-powered electric hole-makers. One upon a time every startup had SQL inside, but that wasn’t the product, and now every startup will have LLMs inside.

people are still creating companies based on realising that X or Y is a problem, realising that it can be turned into pattern recognition, and then going out and selling that problem.

A GUI tells the users what they can do, but it also tells the computer everything we already know about the problem, and with a general-purpose, open-ended prompt, the user has to think of all of that themselves, every single time, or hope it’s already in the training data. So, can the GUI itself be generative? Or do we need another whole generation of Dan Bricklins to see the problem, and then turn it into apps, thousands of them, one at a time, each of them with some LLM somewhere under the hood?

The change would be that these new use-cases would be things that are still automated one-at-a-time, but that could not have been automated before, or that would have needed far more software (and capital) to automate. That would make LLMs the new SQL, not the new HAL9000.