
Agentic Search Works Best When It Writes Queries, Not Answers
SNEWPAPERS is a useful Show HN signal: the strongest agentic search products do not replace search results with prose. They teach the agent to operate a real search system.
6 articles

The Bayer and Thoughtworks PRINCE case study is a useful reminder that reliable agentic AI comes from context routing, traces, evals, monitoring, and human review, not from a better prompt alone.

SNEWPAPERS is a useful Show HN signal: the strongest agentic search products do not replace search results with prose. They teach the agent to operate a real search system.

OpenAI shipped an open-weight PII redactor. Here is how to wire it into a real ingestion pipeline locally, fast, with zero leaks, and how it benchmarks against Presidio and a regex baseline.

A production-grade RAG pipeline with Claude. Chunking that survives real documents, retrieval tuning that actually moves the needle, citation tracking, and the prompt caching trick that makes RAG cheap enough to ship.

Agents forget everything between sessions. Here are the patterns that fix that: CLAUDE.md persistence, RAG retrieval, context compression, and conversation summarization.

How RAG works, why it matters, and how to implement it in TypeScript. The technique that lets AI models use your data without fine-tuning.
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