New in Claude Code (research preview): dynamic workflows.
Claude writes an orchestration script on the fly, then spins up a large fleet of coordinated subagents in parallel to take on your most complex tasks.
Use the word "workflow" in a prompt to get started.
Caught up with @karpathy for a new @NoPriorsPod: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects
02:55 - What Capability Limits Remain?
06:15 - What Mastery of Coding Agents Looks Like
11:16 - Second Order Effects of Coding Agents
15:51 - Why AutoResearch
22:45 - Relevant Skills in the AI Era
28:25 - Model Speciation
32:30 - Collaboration Surfaces for Humans and AI
37:28 - Analysis of Jobs Market Data
48:25 - Open vs. Closed Source Models
53:51 - Autonomous Robotics and Atoms
1:00:59 - MicroGPT and Agentic Education
1:05:40 - End Thoughts
🚨 BREAKING: Passive studying is dead!
Claude can train your brain harder than most professors ever will.
Here are 10 Claude prompts to learn anything 10× faster 👇
The biggest threat to humanity isn't on that planet.
It's the mechanism that prevents humans from seeing what's actually happening while they stare directly at it.
Every existential threat.. climate, AI alignment, nuclear proliferation, resource depletion, persists not because solutions are unknown, but because the human mind cannot sustain attention on what produces no immediate dopamine response.
You're watching civilizational scale problems advance in real time while your attention system prioritizes notifications, tribal signaling, and the maintenance of comfortable delusions.
The threat isn't external. It's the architecture of consciousness that makes humans optimize for feeling informed rather than becoming effective.
🚨 DeepSeek just did something wild.
They built an OCR system that compresses long text into vision tokens literally turning paragraphs into pixels.
Their model, DeepSeek-OCR, achieves 97% decoding precision at 10× compression and still manages 60% accuracy even at 20×. That means one image can represent entire documents using a fraction of the tokens an LLM would need.
Even crazier? It beats GOT-OCR2.0 and MinerU2.0 while using up to 60× fewer tokens and can process 200K+ pages/day on a single A100.
This could solve one of AI’s biggest problems: long-context inefficiency.
Instead of paying more for longer sequences, models might soon see text instead of reading it.
The future of context compression might not be textual at all.
It might be optical 👁️
github. com/deepseek-ai/DeepSeek-OCR
🌍 The biggest decentralized science experiment of 2025 is starting now!
The protein design competition returns: we’re inviting scientists, engineers, and hackers from around the world to help design new proteins capable of neutralizing the Nipah virus, a pathogen with up to 75% mortality and no effective treatment.
All you need is a laptop to participate: submit your computational protein designs, and @adaptyvbio will synthesize and experimentally test 1,000 of the most promising proteins, with all results released open-source on @proteinbase.