A Haystack pipeline can be perfectly wired and still unsafe. The retriever returns documents. Every component did its job. But if untrusted text moved through the pipeline as ordinary context, the trust boundary was lost. That is the problem this post is about. Not bad Python. A valid component connection only says: this value fits the next component It does not say: this value is safe to influen
The first time I had to sit down and write operating principles for two AI agents working on the same codebase, I had a moment of genuine déjà vu. It felt exactly like the early Foodora days. Too much speed, too little structure, and someone on the team absolutely certain they knew the fastest route even when the road wasn't built yet. Except this time the team is Claude and Codex. And I'm working
Comparison: Haystack 2.0 vs. RAGatouille 0.3 for Building High-Accuracy RAG Pipelines for Developer Docs Retrieval-Augmented Generation (RAG) has become the standard for building LLM-powered tools that answer questions using private or domain-specific data. For developer documentation (dev docs) — which includes technical jargon, versioned APIs, code snippets, and structured reference material —