Stripe

Walk through orchestrating a 500M-vector re-embedding backfill: rate limits, checkpoints, verification, and cutover readiness.

Two startups share the same base model yet feel different: explain the moat

Match each OWASP LLM Top 10 risk to the control that addresses it

Identify LLM01 in the OWASP LLM Top 10

Your new reranker looks better offline: prove it actually improves retrieval in production before full rollout

Design query routing for a RAG app serving several distinct knowledge sources

Match each 2026 framework or product to the workload it fits best

Why is a 4,000-token system prompt usually a code smell?

How many few-shot examples is the right number, and what tradeoff governs that count?

When does hybrid (dense + BM25) retrieval outperform pure dense for context engineering?