AI Engineering in a Minute
Specific answers to questions engineers and technical leaders search while trying to put an AI system into production. Not generic SEO filler.
Each guide ends with a path into an offering if you want the same work done in your environment. The guides stand on their own either way.
6 of 6 guides
Why do AI proofs of concept stall before production?
Why AI PoCs fail to reach production
The usual failure is not the model. It is everything the demo was allowed to ignore.
production · architecture · evaluation
How do I evaluate an AI agent before production?
How to evaluate an AI agent before production
Evaluate the system around the model: tasks, tools, permissions, and failure — not a handful of happy-path chats.
evaluation · agents · production
What belongs in an AI production-readiness review?
What belongs in an AI production-readiness review?
A review checklist for evaluation, access, observability, cost, and operations — the parts demos skip.
production · evaluation · security
How do I estimate inference cost before production?
How to estimate inference cost before production
Price the workflow, not the token. Volume, retries, tools, and human review dominate the bill.
cost · production · architecture
When should I not use an LLM?
When not to use an LLM
If the output must be exact, the rules are known, or the action is irreversible, start somewhere else.
architecture · production · cost
What does an AI FDE actually do?
What does an AI FDE actually do?
A forward-deployed engineer embeds with your team and moves the highest-value AI work toward production.
fde · production · architecture