Search posts, papers, and topics
A step‑by‑step tutorial showing how to add a typed decision layer (using Jev and Pydantic) to a LangChain agent so you can route requests to cheaper or more capable models and gate risky tool calls, with concrete Python code and cost‑trade‑off notes.
A step‑by‑step tutorial showing how to build a typed context‑compaction gate for AI agents in TypeScript using LangChain and Zod. It defines a discriminated‑union schema for keep/summarize/discard actions, implements a fast gpt‑4o‑mini classifier, validates decisions at runtime, and wires the gate as middleware in an agent loop, with testing and production‑grade tuning advice.
The article walks through building a TypeScript middleware that validates RAG citations by checking exact byte‑span offsets against source buffers, replacing fuzzy heuristics with deterministic guarantees. Benchmarks show sub‑millisecond verification for 1,000 citations across 50 documents.
