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Highlights

  • I generally think I have done a good job anticipating the direction and pace of AI over the few years I have been writing this Substack, but I think I recently got something fairly large wrong. In the last year I have been posting about how I suspected that humans would have to approach working with agents as a manager, deciding how to delegate work to agents and specifying how those agents should be organized. I thought that getting agents to work effectively as a group would take careful construction, akin to building a company, and that this would take time to figure out. (View Highlight)
  • I fell prey to The Bitter Lesson, the hard truth, learned over and over again, that things that we thought required elaborate human rules and thinking can be solved with the brute force of better machine learning systems and more AI. The Bitter Lesson is everywhere among AI startups and companies adopting AI. A huge amount of effort went into building elaborate computer systems to feed AIs the right information at the right time, but AI systems have learned to seek out information themselves. The same thing happened to prompting. People built elaborate templates and chains of prompts that walked the AI through a task one step at a time. Then newer models turned out to be better at planning the steps themselves, and, as our research shows, planning steps have much less value. The history of the Bitter Le— (View Highlight)
  • — you know what? I don’t really need to explain the Bitter Lesson, I asked Claude to do it in a music video. With one prompt, Fable wrote the lyrics and submitted it to Suno; Opus 5.5 did everything else using code alone without any image generation (How did Opus 5.5 pull this off? The Bitter Lesson tells you!). I gave no feedback at all. (View Highlight)
  • As somebody who teaches managers and has published research on management, I guess I believed that managing agents would be different. Humans have been working on management for a very long time without fully figuring it out. It seemed like the kind of thing that would need to be designed by people, at least for a while. (View Highlight)
  • It turns out that organizing work is just one more thing AI can learn to do. (View Highlight)
  • The number one app in the App Store right now is Meta’s Muse, a personal agent that promises to do work for you. OpenAI has now released a competitor tool, called dots. They aren’t alone: SpaceX’s Grok Bot, Instinct, and Gemini Spark all do similar things, more or less. All of these agents draw inspiration from a phenomenon you might remember from earlier this year, OpenClaw. (View Highlight)
  • The idea of OpenClaw and its successors, which I will call Clawlikes, is that they give an AI agent access to a computer and connect to your accounts (emails, financial records, etc.). They analyze and react to that data in real time, even when you aren’t looking. The trick is that you talk to the model like you would a person, sending it messages on Slack or SMS or WhatsApp, and it also proactively reaches out to you, like a person would. For dots, you can actually jump on a call with your agent as well. You basically get an infinitely patient personal assistant that looks out for you. Increasingly, I have discovered that they are finding my mistakes, rather than having me identify theirs. (View Highlight)
  • As one useful example, one of my personal agents contacted me because an email I sent to our town for a permit had the wrong project number on it. The catch was that I was the one who made the mistake, and I am not 100% sure how the AI spotted the error. Fortunately, it helpfully wrote a draft correcting the issue, so that is good (if a little freaky). As another example, Muse noticed that an airline credit of mine was about to expire and, when I asked, contacted American to request an extension. (As a side effect, every firm’s customer service agents are about to be overwhelmed with Clawlikes negotiating for better deals using voice and chat channels made for humans). (View Highlight)
  • It is tempting to judge these agents by the list of things they can do, like booking travel or canceling subscriptions. I think the more important thing is what you no longer have to tell them. You don’t need to type in tons of context, the AI learns it from your messages. You don’t have to give them a plan, they develop plans themselves. They figure it out. (View Highlight)