Carto – structural intelligence for AI coding agents (OSS)
Blast radius detection before AI edits code, competing with Cursor's codebase awareness.
Agenda Intelligence — product runtime + evidence-discipline layer for strategic intelligence agents. Four surfaces (MCP, HTTP, A2A, Cloudflare Worker) over one core service layer. Ships one live vertical worker: Middle Corridor Deal Risk Gate. Schema-validated I/O, evidence audit, geography routing. No live retrieval, no factual verification.
Evidence-discipline layer for agents solving hallucination in geopolitical risk analysis.
AI engineers building agents, Risk analysts
LangChain · LlamaIndex
Blast radius detection before AI edits code, competing with Cursor's codebase awareness.
Documentation templates that force AI agents to read architecture before coding.
Forces LLMs to debug with AST evidence instead of pattern-matching symptoms.
Structured plain text spec aiming to replace flat RAG embeddings.
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.
Schema-valid evidence packs for AI agents when generic evals miss domain nuance.