ACE Comprehensive Reference Specification
The unified framework that production-grade agent platforms use to make context work at scale
Comprehensive reference for Agentic Context Engineering - the discipline of managing LLM context as a compiled system rather than an append buffer. Covers the four-layer memory architecture, the compiler thesis, nine scaling principles, nine failure modes, domain memory patterns, and the self-improvement framework that lets agents learn without retraining.
Also connected to
The stateless paradox: how conversational AI maintains the illusion of memory on protocols designed to forget everything
The distributed systems problem hiding inside every multi-agent AI system: how do agents share what they know without drowning in what they don't need?
How to architect context that scales across hundreds of agents without degradation
Reference specification for retrieval augmentation patterns in agentic systems, covering vector search, hybrid retrieval, and context window optimization.
Quick explainer: 3-4 minute narration script for Claude Code Harness...