How we moved from a fragile loop-based payout system to a reliable, idempotent, and traceable architecture. On paper, payouts sound simple: Customer places an order Platform collects payment Platform pays the seller That's it. Until you try to do it at scale. In any marketplace or fintech system, money flows across multiple parties: Sellers / vendors Delivery partners Platform fees Discounts, vouc
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
I still remember where i was when the email came in. December 25th. Christmas morning. Phone in hand while having breakfast, and there is an email from our client's CTO. No greetings, Just "We're terminating the contract. Our legal team will be in touch" We lost a 120K a year contract. On a Christmas morning because of a date calculation bug that none of us, not a person on a team of 5 experienced
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 —