Part 1Retrieval & RAG
Designing a RAG System for 10 Million Documents
How to size, build and measure retrieval-augmented generation over 10M documents: ingestion, hybrid retrieval, reranking, ACLs, cost and evals.
7 articles.
Part 1Retrieval & RAG
How to size, build and measure retrieval-augmented generation over 10M documents: ingestion, hybrid retrieval, reranking, ACLs, cost and evals.
Part 17Security & Privacy
Why model-level filters can't stop prompt injection, and how control/data separation, taint tracking and sink policies make attacks harmless.
Part 18Security & Privacy
A layered design for detecting, pseudonymizing and re-identifying PII before it reaches a model, and how to measure the leak rate honestly.
Part 19Fine-tuning & Adaptation
Diagnose whether your gap is knowledge or behavior, then climb from prompting to RAG to fine-tuning only when the cheaper rung plateaus.
Part 22Production Engineering
Stream tokens with server-sent events, decouple generation from the connection, resume with Last-Event-ID, and cancel cleanly so GPUs are freed.
Part 24Production Engineering
Make prompt rollback a sub-minute alias flip, catch regressions with canaries and guardrail metrics, and clean up what the bad prompt left behind.
Part 25Production Engineering
Back-of-envelope sizing, architecture and overload strategy for an LLM chat product at 1M DAU, where GPUs set both the cost and the latency.