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
You know that feeling when your AI agent starts burning through your API budget at 3 AM and you only find out the next morning? Yeah, we've all been there. The observability space for LLM applications has exploded in recent years, but most platforms either lock you into their ecosystem or charge you per-token like it's liquid gold. Let's talk about building a real-time monitoring strategy that doe
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 —