I've switched over to Rex as my primary terminal and AI system.
So no more Kitty, Ghostty, Herdr, or any of that.
But I was having trouble getting an invite to the iOS app (email delivery issue).
So I just made my own client.
I just make my own software now.
Introducing Claude Meetings: add Claude to your team’s video call and it builds docs, whiteboards, and other artifacts with you while you’re still talking.
Starting to roll out in beta on Team and Enterprise plans.
Really happy with how my new Router system works in LifeOS.
It's Opus 5.5 by default but it knows to go up to Fable for things that require high intelligence or scrutiny, like security decisions...
And it can decide to use any of my other models in the harness as well.
@TomQuinn8 It's early, so not really any without a lot of human expertise.
But this is what's changing very fast.
I expect 2027 to be a step change in this regard.
I think these are bad comparisons.
All of those are powerful tools. They are not agents. This is too extreme, but a better metaphor:
- Hacking tools are machine guns
- Malicious AI is a Thanos Guantlet
If you tell a machine gun to take over a city or carry out a coup, it won’t do anything because it’s a machine gun.
If you snap your fingers with a Thanos Gauntlet, saying “disrupt the power grid”, shit happens.
Yes, they are both tools and they are both weapons. But there are nowhere near the same thing.
For those who recall, when HD Moore released Metasploit, the community debated whether it would make hacking too easy, arm script kiddies, and give attackers an advantage. The same conversation took place with L0phtCrack, and SATAN before then. History tells us how this plays out already.
I have a new concept I call The Bitter Wall.
- The Bitter Lesson tells us to stop micromanaging AI
- Basically: let smarter AI figure out the steps
- But there's a limit to this
- The output can only be as good as our articulation of what we want
https://t.co/yB53JRpRcc
I have a new concept I call The Bitter Wall.
- The Bitter Lesson tells us to stop micromanaging AI
- Basically: let smarter AI figure out the steps
- But there's a limit to this
- The output can only be as good as our articulation of what we want
https://t.co/yB53JRpRcc
Thanks for telling me the part most people skip.
But the part that I skip when I see that sentence is the rest of whatever you were going to say.
It’s the number one AI tell right now.
@sortofadev I started messing with agents in 2023. and was already doing some pretty functional stuff in 2024. By last year, I already had my harness and was doing many employees worth of work.
Just a reminder for people who are freaking out about the AI takeover stuff in 2027...
Whenever we get RSI or ASI or whatever milestone you care about, that's one date...but it's not the only date that matters.
It doesn't say anything about the integration time for getting that tech into the actual world.
My friends and I have been doing AGI-adjacent stuff for years already, and yet there are companies still refusing to use AI, or only using it as a chatbot.
No matter how big of a jump we see in 2027, dispersion will still take time.
Just a reminder for people who are freaking out about the AI takeover stuff in 2027...
Whenever we get RSI or ASI or whatever milestone you care about, that's one date...but it's not the only date that matters.
It doesn't say anything about the integration time for getting that tech into the actual world.
My friends and I have been doing AGI-adjacent stuff for years already, and yet there are companies still refusing to use AI, or only using it as a chatbot.
No matter how big of a jump we see in 2027, dispersion will still take time.
This post by Anthropic is massively overlooked, and these are my biggest takeaways:
- Claude now leads 26% of Anthropic's AI R&D work. In February it was under 1%
- AI collaborates on or leads over 90% of that R&D work. In August 2025, going by the chart, it was about 4%
- About 30,000 AI agents do research and engineering at Anthropic at any one time (on one platform)
- Those agents made over a billion decisions in one month. 1 in 47,000 got blocked
- Monitors flag ~100,000 agent transcripts a week, and only ~50 reach a human
- To build the index, Claude agents read staff Slack and docs and mapped 15,000 R&D tasks
- Claude agreed with humans more often than humans agreed with each other (59% vs 35%)
- Agents get their own identities that survive model upgrades. They coordinate on an open message board, so they can check each other's work
https://t.co/8egkHXqw1n