When you figure out the right abstraction it feels like this👨‍🍳💋🤌

Suggestions for energy and focus Sunlight in the AM indirectly supports your mitochondria setting you up to feel energetic throughout the day. (Huberman talks about this) If you work at a desk have your desktop so you look up not down, because looking up is associated with

Small teams beat big companies because they share context instinctively. They move as one. Same principle separates effective AI from expensive failures. It's not about smarter models. It's about context engineering. This is why I'm building @BuildOS Ok done bye.

Two things you can do NOW: Build your knowledge corpus - Centralize all documentation - Have AI index everything - Pull only what's relevant Document your context - Talk to an LLM about your work - Today's context = tomorrow's AI capability

Mr Steve Jobs, may he rest in peace, got this. Mr. Chesky gets it. You don't let smart people run wild—you create crystal-clear context. Regular syncs. Shared docs. Obsessive alignment. For AI, this "micromanagement" IS context engineering.

Workflow builders miss this completely: Smart LLMs = raw material More tools = more raw material Context engineering = the actual process As AI gets smarter, you don't want to prescribe every step. You want AI making the RIGHT decision based on the relevant context.

Those "build a website in 30 seconds" demos? Sure, you get a website. But does it know your brand? Your customers? Your goals? For anything real, you need context that activates at decision points.

We've evolved: Prompting → say something, get something Prompt engineering → carefully craft what you say Context engineering → give carefully crafted information at the edges Context engineering = layers of information that guide decisions at critical moments

Smart people with great tools, left alone, create chaos: - Engineers build features nobody asked for - Data insights never reach sales - Customer feedback dies in silos - Teams pull in different directions The problem isn't intelligence. It's alignment.

This sounds like the same conventional wisdom from business: "hire smart people and let them do their thing." Except Brian Chesky called BS on this in his founder mode speech. Here's why it matters for AI ↓

Everyone's obsessed with making AI smarter and giving it more tools. New workflow builders everywhere. Higher benchmarks. AGI. The singularity. The formula: Smarter AI + more tools = success Sound familiar? Well I am pattern matching this to something specific.

I feel like I know a secret about how to approach AI. Most people approaching AI are missing one ingredient. It's the same ingredient that enables small teams to beat big teams. And it isn't well understood 🧵

Don’t forget to thank you llm agents after they do a good job. You might want them to remember your gratitude later on.

I just want to take a moment and appreciate the robustness of VS Code. It’s got me, Codex and 2 Claude Code terminal agents all working simultaneously in one editor. That seems like a lot, and vs code is just chugging along not complaining.

Remember DO a good job and think like a senior engineer ✍️

One of the nicest patterns to use with Claude Code Catch and Log errors —> feed errors to Claude code —> Claude code fix errors —> ^ great simple loop

Proud of this Build-OS is getting better and becoming easier to use everyday

You know you are doing something right when you want to thank your LLM for all its hard work. ^ This is the result of crispy context engineering

If you aren’t already creating context docs, start small and start saving yourself some time. These docs are the building blocks for creating your own personal operating system

We should be actively documenting, preserving, and curating human knowledge - not generating synthetic substitutes. The question isn’t just “how do we make AI smarter?” It’s “how do we help AI remember what matters?”