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
AI coding tools are starting to look similar on the surface: they all offer chat, agents, code edits, terminal awareness, and some form of autocomplete. But the real differences are in the workflow. The question is less “which one has AI?” and more “where does the AI live in your development process?” For me, VS Code is still the baseline. It is flexible, extensible, familiar, and easy to compose
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 —