ANTHROPIC JUST LEAKED AN INTERNAL ENGINEERING DOCUMENT - AND IT SAVES SOLO DEVELOPERS $300,000 A YEAR
the highest-leverage AI systems are no longer prompt-driven - they are loop-driven - and that one shift changes everything
Generate → Evaluate → Remember → Schedule → Optimize → Recurse
six layers, one loop, improves itself without a human
Generation: the system produces its own solutions - no human writes the brief
Evaluation: a second layer measures quality - the thing that can say no
Memory: every execution retains useful discoveries - the loop gets smarter each cycle
Scheduling: the system decides what happens next - nobody manages the queue
Optimization: behavior updates based on what worked - static prompts eventually hit diminishing returns
Recursion: remove any single layer - and system performance drops significantly
the role of the human shifts from operator to architect - and AI transforms from a prediction engine into an adaptive production system
the future of AI engineering is recursive
My dear front-end developers (and anyone who’s interested in the future of interfaces):
I have crawled through depths of hell to bring you, for the foreseeable years, one of the more important foundational pieces of UI engineering (if not in implementation then certainly at least in concept):
Fast, accurate and comprehensive userland text measurement algorithm in pure TypeScript, usable for laying out entire web pages without CSS, bypassing DOM measurements and reflow
🚨 BREAKING: Someone just rebuilt the entire AI assistant stack in Zig.
It's called NullClaw. The binary is 678 KB. It uses ~1 MB of RAM. It boots in under 2 milliseconds.
No runtime. No VM. No framework. No garbage collector. Just raw Zig.
Here's why this is absurd:
→ OpenClaw needs a $599 Mac Mini and 1 GB+ RAM
→ NanoBot needs 100 MB+ RAM and Python
→ PicoClaw needs 10 MB RAM and Go
NullClaw runs on a $5 board with 1 MB of RAM.
Same functionality. 0.1% of the resources.
Here's what's packed into that 678 KB:
→ 22+ AI providers (OpenAI, Anthropic, Ollama, DeepSeek, Groq, etc.)
→ 13 chat channels (Telegram, Discord, Slack, WhatsApp, iMessage, IRC)
→ 18+ built-in tools
→ Hybrid vector + keyword memory search
→ Multi-layer sandboxing (Landlock, Firejail, Docker)
→ Hardware peripheral support (Arduino, Raspberry Pi, STM32)
→ MCP, subagents, streaming, voice, the full stack
Here's the wildest part:
Every subsystem is a vtable interface. Swap any provider, channel, tool, memory backend, or runtime with a config change. Zero code changes.
It even encrypts your API keys with ChaCha20-Poly1305 by default.
2,738 tests. ~45,000 lines of Zig. Zero dependencies beyond libc.
100% Open Source. MIT License.
someone vibe coded a 3d city where every github developer is a building
more commits = taller building.
more repos = wider base.
lit windows = recent activity
@zerohedge Brazil spends $25 billion on the judiciary power solely yearly, summing the three powers, they spend $50 billion yearly.
1 million BTC at an agg price of $80.000 would be $80 billion. Brazil can easily pull this off but would need a massive El Salvador vibes to pull this off
@DavidOndrej1 "Agent Zero doesn't collect your data and runs locally"
"Proceeds to installation"
"Now choose a model to use with AgentZero"
Summary, you are still giving your data to the big companies, waste of time, this is not secure unless you run your models locally.
This is the google of AI agents
If you're building with AI agents, you need it
Search across 164+ agent skills
> Filter > Search > Copy install