Same 😭. The brain has gotten habituated to feel like doing anything else (scrolling, opening X, etc.) when I'm waiting for my agents to finish their work. And then the constant switching between multiple agent sessions. I think mindfulness meditation is the only way to go! 🧘

So stoked for this one! It's such a fascinating topic to be speaking about, and I couldn't have found two better people to present with! See you at @_odsc West in San Francisco next week!

I don't know who needs to hear this, but no matter who you are, the MOST important skill to train in the age of AI is critical thinking. When you see (or are told) something in the real world, you should aim to question *why* it is what it is, rather than just looking at *what* it is. Understand how things work. If one exercises critical thinking skills hard enough, you never stop (or tire of) learning. You just absorb new information like a sponge, and because you're always asking "why?" and "how?", you end up going wider and deeper than you ever did before you had AI. It was simply too hard to spend the time on that deep a study before. Now, you can.

Graphs 🤝 world models as they capture connectivity of state

Plea to Anthropic. Please don't release opus 5.6 and regress on 5.5, I beg you. I love 5.5, not ready to let it go 🥲

Quite a pertinent question to ask. We may not be there yet, but every day, it's more and more fair to ask why is this tool something I'd pay for, vs. something I'd build on top of open source?

Dunno what it is but I've barely felt the need to use 6.1 Sol all week 😂. Opus 5.5, it's soooooooooo good 😌 I wonder when OpenAI will be back.

This is a profound realization I came to only earlier this year. Thankfully, better late than never. There's still plenty of good days left to enjoy better health!

I agree with this take wholly, and I was approaching it wrong my whole life. The positive feedback loop of looking at yourself in the mirror everyday and liking what you see as you persist. It's only about comparing current you with last week's you, and that sustains itself 💪🏽

Die leetcode, die

The mechanism is really interesting. It seems like a classic "boom-bust" cycle. One spends more on R&D for the next gen of model, while the other spends more on inference/deployment scale. Then next month, the trend reverses. Super hard cost optimization to solve at these frontier labs!