Six weeks of silent relevance regression
A retrieval change degrades answer quality without breaking a single test, because nothing compares today ranking against yesterday ranking. Users absorb the loss quietly.
Case Studies
How real teams shipped AI: architecture, cost, failure modes and results.
Tools in this category
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Notes in this category
The pilot worked and the rollout did not
A pilot succeeds because everyone involved knows it is a pilot. The properties that make it work — a tolerant audience, a small corpus, manual fixes at the edges — are exactly the…
The data owner nobody assigned
AI features fail on the organisational boundary between the team that builds the system and the team that owns the data. That boundary is rarely named in the project plan, and it…
The on-prem box that ran out of VRAM at month two
Capacity planning for self-hosted inference usually counts the weights and forgets everything else that has to live on the same card. The gap between those two numbers is what run…
Why most enterprise RAG pilots stall in week three
The demo works on a handful of clean PDFs, the room is impressed, and then the real document set arrives: scans, merged cells, ten-year-old contracts and three languages. This is…
Permission models: the part of enterprise RAG nobody budgets for
Retrieval quality is a solved-enough problem. Permissions are the reason enterprise RAG projects stop: not because they are hard, but because they arrive late and force a rewrite.