My unfiltered thoughts on personal agents. Grokbot has the best UI and it’s arguably the best overall. In a lot of ways they’re ahead. Their desktop app feels the best, and their multi-bot coordination is great: you can set a team lead and it passes tasks to the other bots. Grokbot also has the best “webhook” feature, which means you can easily turn outside events into triggers that start your agents. That speeds up background workflows like watching your email, Slack and more. It also has Cursor integration, so for bigger tasks Grokbot can spin up a Cursor cloud session with any model (until OpenAI cuts SpaceX off from their models, which I think will happen soon). Unfortunately, running frontier models through Cursor costs more than Claude or Codex. Still, they’re the only ones embracing a team of agents. It’s a really cool idea, but the more bots you have, the more time you spend managing and maintaining them. I’m starting to think one bot with different threads/channels is the right answer, which I’ll get to with Claude Duet. dots by OpenAI is rough around the edges right now, but it’s probably the most powerful if you use Codex, which I do. dots can spin up Codex sessions in the cloud or locally on your computer. So if you have coding or video editing workflows that need your local files, this is very useful. Codex computer use is also the best in the world: your dot can spin up a local Codex session that fully controls your computer, as long as it’s on. Their real-time voice is incredible. If you have your email and work tools connected, try this: go on a walk with headphones in, ask the agent to summarize your emails, have it draft replies and read them back to you, then send them off. If I remember right, this is close to a workflow you (Tim) used to have with your VAs before AI. It’s my favorite use case for personal agents. The one downside is that you have to call your agent, and it’s an awful experience. It literally rings, and it’s annoying. Muse by Meta is a toy. I’ve talked to a bunch of finance people I play poker with who all tried it and set up automations, and they all said it doesn’t reliably do what they want. It’s fast, and its user numbers will probably keep growing. But it’s basically free: you get a TON of usage without paying a dime. That’s NOT a trade I’m willing to make. An agent doing high-leverage tasks should be running at the Opus 5.5 or GPT 6.1 Sol level. Claude Duet - is in early access, so unfortunately not everyone can use it yet. First things first, it runs on Opus 5.5, the best model in the world. I’ve only had access for 72 hours, but Duet feels different from the others. It’s not a personified agent like Grokbot, dot or Muse, which gives it a more professional vibe that I like. When you ask your Duet agent to do something, it spins up a task, which is a new chat thread. All your threads show up in a Tasks tab, so it’s easy to see everything Duet is working on or has finished. And instead of creating more agents (like Grokbot), you create channels, just like Slack (I can tell @anthropic is Slack-pilled). I have a content channel, a finances channel, etc., which keeps different kinds of tasks separate. The only other app I’ve seen do this is Buzz by @jack, and it’s a good experience. Their strong point is documents (artifacts). If you want decks, high-quality docs or design mockups, Opus just wins. Period. It’s not close right now. Their weak point is real-time voice. It’s the worst of the bunch and borderline unusable, though I think they only added it a few days ago. Instinct lives in iMessage, has no app, and doesn’t do anything notable besides show you product suggestions you didn’t ask for. (Not ads, according to their team.) My hot take: The VM is overrated. SpaceX, OpenAI and Meta all talk about the VM your agent can use and feature it in their marketing. It’s not as useful as you’d think, because more and more websites block bots that visit their site on the cloud VM. All of these companies promise their agents can make payments, but most payments either take forever or get blocked altogether. SpaceX has a cool workaround with Grokbot that routes traffic through your computer so it uses your IP address. But I’d much rather the agent just USE my computer for the task, like dot does by handing it off to Codex. Also, i don't think normal people care about the virtual computer. If anything they get offended they have to "stream a computer". The problem with personal agents: by the time you read this, pick one, and test it for 7 days, every one of them will have released 10 new features and the whole landscape will have changed. It’s nearly impossible to keep up.

people are starting to realize. there *are* no moats left. the only true moat in existence was intelligence, and now that's out of the equation.

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is. 5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now. 6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text. They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it. 7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy. 8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies. Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here. 9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens. 10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity! 11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it. 12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable. 13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think. 14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data. 15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open. 16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down. 17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building? 18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone. 19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good. 20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped. 21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense. Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era. Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways. Happy to be home and locked in. Until next time!

This is why you shouldn’t listen to the people who say to jump from project to project. You will continually jump from thing to thing, meanwhile not actually building a real business

The people I met with high token usage were in general making no money and generating slop apps with no users Almost no exceptions

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