Stanford just dropped a paper called Agentic Context Engineering (ACE) — and it might just end fine-tuning as we know it.
No retraining. No weights touched.
The model literally rewrites and evolves its own prompt, learning from every mistake and success.
🔥 The results:
🚀 +10.6% better than GPT-4 agents
💰 +8.6% on finance reasoning
⚡ −86.9% cost & latency
🧠 No labels. Just feedback
Everyone’s been chasing short, clean prompts.
ACE flips that idea completely.
Turns out, LLMs don’t want simplicity — they want context density.
They perform better when surrounded by rich, evolving information.
So yeah, the next wave of AI won’t be fine-tuned.
It’ll be self-tuned.
Welcome to the era of living prompts.
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