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1. Psilocybin helped human cells live longer in the lab. The cells stayed younger for longer and kept dividing more than usual before aging out. And the protective tips on DNA (telomeres), which wear down with cell divisions, stayed intact for longer. 2. Psilocybin

This is really cool work—markdown language for LLM prompting:

Lovable just raised $200M at a $1.8B valuation led by Accel. This all started unexpectedly with me calling my friend at 6AM to go for a walk. I've never shared this story before: (thread)

I'm joining Erik Torenberg at a16z on the new media team. Our mission: curate the most important conversations in technology (via podcasts, writing, and group chats), capture our world as it transforms, and write the history of the future in advance. If that compels you, DM me.

woah claude code recovered from a bad architectural direction btw new n&w hack coming soon

juggling two claude codes and i’m the bottleneck

prompts as data structures feels very natural (can you spot the bug?)

JSON is the new spec

i’m so hyped

once bun build can compile bun: bindings to node it’s over

Use Gemini CLI to capture your coding style by recursively analyzing your code :-)

🤣 I think I style have some domain like arewedatingthesameguy.ai

Getting all my wisdom teeth removed was one of my most ecstatic / psychedelic experiences Kinda odd I know but it’s amazing what happens when you don’t resist and dive headfirst into it

For end user product quality / UI Even if you only know Python Use AI to use TypeScript It’s not even close

Today we're launching Subconscious: a new platform for building agents with long-horizon reasoning and tool use, backed by MIT research. One API call. Tool use. Context beyond existing limits. If you're building agents, let's talk.

At Academy of Management Global Meeting 2025 and about to DSPy-pill some management researchers who are talking about manual prompt engineering and fine tuning Spreading the gospel Omar Khattab

How does prompt optimization compare to RL algos like GRPO? GRPO needs 1000s of rollouts, but humans can learn from a few trials—by reflecting on what worked & what didn't. Meet GEPA: a reflective prompt optimizer that can outperform GRPO by up to 20% with 35x fewer rollouts!🧵

New paper: Reflective Prompt Evolution Can Outperform GRPO. It's becoming clear that learning via natural-language reflection (aka prompt optimization) will long be a central learning paradigm for building AI systems. Great work by Lakshya A Agrawal and team on GEPA and SIMBA.