#LLM
5 pieces filed under “LLM”.
The context window is a product decision
The context window is a product decision: curating what the model sees, showing users what's in scope, and designing honest 'I don't know' moments.
How long should the answer be? Right-sizing LLM output
Answer length is a product decision, not a model default. Per-surface budgets, summary-detail layering, and evals that treat 'too long' as a failure.
Shipping LLM features: a production checklist
The pre-launch checklist we run before any LLM feature ships: evals, traces, cost ceilings, fallbacks, feedback loops and the metrics that catch quality drift.
When the model fails: fallback UX for LLM features
LLMs fail — slowly, confidently and at the worst times. How to design degradation tiers, honest error states and timeouts that keep users' trust intact.
RAG pitfalls we hit so you don't have to
Retrieval in production humbles everyone. The chunking trade-offs, citation bugs, stale knowledge and eval failures that taught us how RAG actually breaks.