Today I'm publishing a new essay, Policy on the AI Exponential. AI is progressing extremely fast—much faster than the policy process was built to handle. The essay lays out where I think the technology is now, and the action needed to close the gap: https://t.co/Lh6PWae178
a prompt I've been using a lot recently:
implement <SPEC> and while you do, keep a running implementation-notes.html file (or markdown) with decisions you had to make weren't in the spec, things you had to change, tradeoffs you had to make or anything else I should know
Agent view is the best Claude Code native way to manage multiple sessions, kind of like tmux built for CC.
We spent a lot of time getting the details right, I hope you enjoy it.
Someone finally documented how to actually use Claude Code.
22K+ stars. claude-code-best-practice.
Direct from Boris Cherny and team:
→ Always use plan mode, give Claude a way to verify
→ Ask Claude to interview you using AskUserQuestion tool
→ Use Git Worktrees for parallel development
→ /loop - schedule recurring tasks for up to 3 days
→ Code Review - fresh context windows catch bugs the original agent missed
→ /btw - side chain conversations while Claude works
→ Make phase-wise gated plans with tests for each phase
→ Use cross-model (Claude Code + Codex) to review your plan
→ CLAUDE[.]md should target under 200 lines per file
→ Use commands for workflows instead of sub-agents
→ Have feature-specific sub-agents with skills instead of general QA or backend engineer
→ Vanilla Claude Code is better than complex workflows for smaller tasks
→ Take screenshots and share with Claude when stuck
→ Use MCP to let Claude see Chrome console logs
→ Ask Claude to run terminal as background task for better debugging
→ Use cross-model for QA - e.g. Codex for plan and implementation review
The community workflows included:
→ Cross-Model (Claude Code + Codex) Workflow
→ RPI (Research Plan Implement)
→ Ralph Wiggum Loop for autonomous tasks
→ Github Speckit (74K stars)
→ obra/superpowers (72K stars)
→ OpenSpec OPSX (28K stars)
The billion-dollar questions it addresses:
→ What should you put inside CLAUDE[.]md?
→ When should you use command vs agent vs skill?
→ Why does Claude ignore CLAUDE[.]md instructions?
→ Can we convert a codebase into specs and regenerate code from those specs alone?
The daily habits:
→ Update Claude Code daily
→ Start your day by reading the changelog
→ Follow r/ClaudeAI, r/ClaudeCode on Reddit
Repost it. Bookmark it.
Exclusive: Meta just released Llama 3.1 405B — the first-ever open-sourced frontier AI model, beating top closed models like GPT-4o across several benchmarks.
I sat down with Mark Zuckerberg, diving into why this marks a major moment in AI history.
Timestamps:
00:00 Intro
00:38 Meta’s Llama 3.1 rundown
03:44 Real-world use cases for Llama 3.1
06:15 Educating developers on open-source AI tools
09:43 Societal implications of open-source AI
13:00 Balancing power and managing bad actors
14:40 Open source and global competition
16:59 Accelerating innovation and economic growth
20:04 Zuck on Apple and lessons from the past
24:22 Future of AI: Llama 3 and beyond
26:43 Prediction: Billions of personalized AI agents
31:32 Factors to changing anti-AI sentiment
We have trained ESM3 and we're excited to introduce EvolutionaryScale.
ESM3 is a generative language model for programming biology. In experiments, we found ESM3 can simulate 500M years of evolution to generate new fluorescent proteins.
Read more: https://t.co/iAC3lkj0iV
University of Cambridge is the 3rd-best university in the world.
And they have just released free online courses for everyone.
Here are 10 courses you don't want to miss in 2024: ↓