clstrns

"House of David" has been a breakout hit for Amazon. The historical drama series attracted nearly 50M viewers in its first season and hit #1 on the U.S. charts. And the showrunner, Jon Erwin, says it couldn't have been made without AI. The future of filmmaking is hybrid.

My biggest takeaways from @danshipper: 1. The future of work will happen inside Codex or Claude Code. Instead of putting AI into your SaaS tool, you’ll use your SaaS tools inside your favorite AI agents' in-app browser. Dan spends all his time in Codex now—writing documents, managing email, doing research, everything. He's using Google Docs, PostHog, and everything he needs within the agent's in-app browser. The agent can see what he’s doing, and has all of his context, so he and his agent collaborate quickly and super effectively. 2. Automation is a lie—every automation needs a human. Dan's company doubled in size this year despite being incredibly AI-forward. Why? Because in order to make automation work well, you need humans making sure everything keeps working. This is why benchmarks are misleading—they measure AI on problems we’ve already framed and can score, but there’s always a higher frame. 3. PMs will win the AI era. Marcus, a former PM who previously ran Axios’s writing product, joined Every after getting super AI-pilled. Now he runs their product Spiral, and ships faster than anyone on the team. He pairs technical knowledge with spiky product sense, deep user empathy, and an eye for what matters. Dan thinks any PM who gets really AI-native will be incredibly dangerous because the building is done for you—what matters is figuring out what to build and if it’s great. 4. Full-stack designers are becoming superheroes. Designers used to make beautiful interactions that engineers didn’t want to build or couldn’t execute properly. Now designers don’t need to hand things off; they can build it themselves. Designers are naturally creative people, and AI is the perfect tool for them because it lets them bring their vision to life without the traditional bottlenecks. 5. SaaS is not dead. In fact, Dan is bullish on SaaS stocks. When users bring their own AI (via Codex or Claude Code) to use SaaS products, the user—not the SaaS company—pays for tokens. This saves SaaS company’s margins. Since the agents need their own seats, Dan predicts that agents will create massive new demand for SaaS because there will be tons of agents using these products at high volume. 6. Every company will have one “super-agent” inside their Slack that every employee will use. Dan initially thought every employee would have their personal work agent, like a shadow AI org chart, but he’s completely flipped his view. He realized agents need humans who care about them. When someone gets tired of maintaining their personal agent, it becomes useless. The winning model is one forward-deployed engineer or AI-savvy person who maintains a company-wide agent (like Shopify’s River or Viktor), and then it trickles down to more specialized team agents as models improve and become less fiddly. 7. The AI job apocalypse is not happening, but you do need to evolve to stay relevant. Models make yesterday’s human competence cheap. But because everyone uses the same models, it all looks the same if you use it the default way; it becomes commoditized slop. Humans then take that frozen competence and use it to make something new and interesting for their specific situation. The key: “ride the models”—use them for everything you do, try new models when they drop, keep turning over rocks. 8. We will read way more AI-generated writing, and we will like it. Human writing is incredibly important for things that matter, but for internal docs, planning, and email, AI-generated is often better because most people are bad at writing strategy documents. 9. Build software for humans and agents to use together. The current model is building a CLI that an agent uses independently. Instead, you and your agent should be using the app together. This creates new design challenges—agents can make a billion requests in three seconds, so you need approval flows, inboxes that summarize what happened, logs, and easy rollback. 10. Forward-deployed engineers are the new most essential role. The big model companies have teams of people managing their internal agents, and those teams aren’t going away. It’s different from traditional software building, and certain engineers love it. As models get better, this role will evolve—you’ll be managing more agents doing more things.

This is a pretty deep question / assertion that is difficult (for me) to disagree with right now. It reminds me of the first "letter quality" printer in Upson Hall and how using it for freshman work generated reactions from my professors. Many thought the "format" distracted from the content and was some sort of ruse on my part. Others thought the formatting caused them to look more carefully at the work as a result. Still others told me to use a typewriter like a normal student. A wakeup call was a a chemistry lab I turned in with one note on the first page "Incredible presentation. Crap writeup. See me!" Then Macintosh came out and everything changed. What will be Macintosh for AI generated/assisted writing?

Dykstra complained about this too way back in 1972. At his Turing award lecture, he said that programmers had no confidence that their software would last because better machines, and better platforms would come along. “But most important of all, the programmer himself had a very modest view of his own work: his work derived all its significance from the existence of that wonderful machine. Because that was a unique machine, he knew only too well that his programs had only local significance and also, because it was patently obvious that this machine would have a limited lifetime, he knew that very little of his work would have a lasting value. Finally, there is yet another circumstance that had a profound influence on the programmer’s attitude to his work: on the one hand, besides being unreliable, his machine was usually too slow and its memory was usually too small, i.e. he was faced with a pinching shoe, while on the other hand its usually somewhat queer order code would cater for the most unexpected constructions. And in those days many a clever programmer derived an immense intellectual satisfaction from the cunning tricks by means of which he contrived to squeeze the impossible into the constraints of his equipment.” having said that it is somewhat ironic that people like me, and Eric Raymond, and probably many others, are using agents to resurrect 30 year-old software programs. Of course that doesn’t exactly resurrect the code, but it does resurrect the vision that those programmers had way back then.

I have written so much software in my life, half the things I thought were throw away ended up sticking around for years, and half the things I thought were permanent were thrown away within the month. I largely think the reason why we see so much crap software is because people think software they are writing will only be around for a moment.

1/ It's 1985. I just did stand-up on David Letterman the night before. Five minutes. I'm 27 years old and I think I've made it. My agent calls me the next day and fires me.

@Fredosphere @antoniogm Actually I think that’s right.

@antoniogm @clstrns Sidewinder missile guidance system?

Anyone know what this is? Hint: it’s completely mechanical, yet invented within living memory, and there’s no modern electrical version that can do the task for the required duration or with the requisite reliability.

@antoniogm Wind vane auto pilot?

Levie’s Law of AI Psychosis: The farther away you are from the actual work the more confident you are that humans are no longer needed I like it

CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI. So when they play with AI, they see the happy path results, often not considering the next 10 or 20 things that have to happen to get sustainable results from agents. “Look I made this awesome product prototype”. Yes but you didn’t have to review the code before it went into production and fix a bunch of issues. “Look I generated a contract”. Yes but you didn’t verify all the terms before it goes out to the counterparty and didn’t have to wire up all the past contracts to work with. The best thing you can do as a CEO is to use AI a *ton* to figure out the real implications of agents in the enterprise, and come out the other side with an appreciation for both the upside and the real work that goes into them.

GPT 5.5 turned out a steaming pile overnight and wow is anyone actually good at this yet? This is starting to feel like programming again, that feeling it’s impossibly hard and painful

This is the future: You load up a crypto wallet or credit card with some cash, and your tireless AGI agent scours the world for an answer, paying incrementally for whatever data or content it needs, delivering an answer previously only available via sky-high monthlies and expensive human analysis. It's a total flippening of the Internet's monetization model: subscriptions, seat licenses, conventional ads...all gone.

If you can learn one thing that's genuinely novel to you, you can learn anything.

love that AI is revealing managerial effectiveness to be a moral fiction

The reason agents are so good at Linux is that all 40 million lines of kernel code was part of the pre training. Along with every other open source dependency. This really does make every obscure error message shallow, and the system completely malleable.

This might actually be the best time to get into math. Soon enough everyone will have a field medalist level math *tutor* at their disposal.

It keeps hitting me how dumb and meaningless so much of "programming" was, now that AI has pushed the tide out and you can see the essential problems laid bare. Naming variables is not one of them.

Absolutely incredible. This from a drug that was *not* designed to attack tumors. Far more impactful than almost any other single treatment we’ve tried over the last few decades. Imagine what could happen when we actively start fine tuning it for cancer treatment.