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
There is a point in many serverless platforms where a Step Functions workflow that once felt elegant starts to feel like a mini application platform of its own. I have seen this happen in teams that are doing many things correctly: they standardized orchestration, they improved visibility, and they moved fragile glue logic out of Lambdas. Then six months later, the workflow has 100+ states, a maze
Overview Let's get our hands dirty. This part covers the full setup and the actual demo: deploy PayLedger to both regions, wire up Route 53 failover, configure the Agent Space, inject three simultaneous faults, and walk through exactly what the agent found. Quick recap from Part 1: PayLedger is a demo payment ledger deployed to ap-southeast-1 (primary) and ap-northeast-1 (secondary) with Route 5
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 —