Stanford just pulled off something wild 🤯 They made models smarter without touching a single weight. The paper’s called Agentic Context Engineering (ACE), and it flips the whole fine-tuning playbook. Instead of retraining, the model rewrites itself. It runs a feedback loop write, reflect, edit until its own prompt becomes a living system. Think of it as giving the LLM memory, but without changing the model. Just evolving the context. Results are stupid good: +10.6% better than GPT-4 agents on AppWorld +8.6% on finance reasoning 86.9% lower cost and latency The trick? Everyone’s been obsessed with clean, minimal prompts. ACE shows the opposite: long, dense, self-growing prompts win. Fine-tuning was about changing the model. ACE is about teaching it to change *itself.* This isn’t prompt engineering anymore. It’s prompt evolution.