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. One core service layer behind four surfaces (MCP, HTTP, A2A, Cloudflare Worker). Four live vertical workers: deal-risk, secondary-sanctions, agentic-trust, Gulf maritime exposure. 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.
MCP integration for product context when Cursor already handles code context.
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.