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Deep engineering writing on production AI systems, distributed systems, failure modes, and architecture judgment.
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Designing the Context Layer for Production AI Agents
Production AI agents need a context layer that assembles evidence, preserves authority and freshness, and separates model reasoning from durable workflow state.
Read essayDesigning a Production RAG System for 50 Million Documents
A production RAG system at 50 million documents is not only a retrieval problem. The hard parts are ingestion, freshness, permissions, evaluation, observability, cost, and operational control.
Read essayThe Truth Is Not in the Docs
Production knowledge is not only in documentation. It is spread across code, tickets, incidents, ownership, permissions, dashboards, and the decisions engineers make under pressure.
Read essayYour RAG Evals Are Measuring the Wrong Thing
Most RAG evals measure answer quality at the end. Production failures usually begin much earlier: ingestion, freshness, permissions, retrieval boundaries and generation control.
Read essayRAG in Production Is Mostly Not About Retrieval
Most RAG discussions obsess over retrieval. In production, the harder problems are ingestion, data lifecycle, generation control and evaluation.
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