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Loop Engineering: Building Self-Correcting AI Agents Without Token Bloat
Most agent frameworks make a fundamental architectural mistake: they loop the LLM directly on its own conversational history.
By turn 30, the model is re-reading 100,000+ tokens of stale compiler errors
