Cognitive Layers
Content-hash drift detection beats markdown walls for AI agent specs.

Structured plain text spec aiming to replace flat RAG embeddings.
AI developers, knowledge management enthusiasts
Obsidian · Logseq · Dendron
Content-hash drift detection beats markdown walls for AI agent specs.
Identity-based memory vs similarity—clean separation of deterministic truth from probabilistic reasoning.
Knowledge graph traces beat vector similarity for multi-hop reasoning queries.
Cube alternative for AI agents, but semantic layers already exist.
The describe → plan → act split is an elegant, accessibility-inspired way to give LLM agents actionable UI context: annotate with data-ai-* attributes or use the Marker component, call describe(), send it to a planner, then client.act() executes DOM instructions. It's a clever middle layer that turns messy DOM state into structured inputs for server-side planning, though adoption will hinge on robust selector semantics and out-of-the-box integrations with popular LLMs and automation backends.
Graph-walking MCP tools beat RAG for agent memory when nobody solved coordination yet.