Practical AI Engineering
34 Articles / Updated AUG 2026 / RSS
Complex data APIs work better when query tools require a current guide receipt, then return errors that show the model exactly how to recover.
As AI makes implementation cheap, code becomes process output. Durable value comes from customer understanding, operations, data, distribution, and trust.
AI products should meet users where work begins, while durable state and detailed controls stay in the application.
Claude 101 starts with a real job, source material, and a result you can judge. Three first workflows for work already waiting on your desk this week.
AI systems get expensive when the model owns every branch. Deterministic orchestration keeps reasoning bounded, testable, and worth its token bill.
AI makes software cheaper to produce. The value was always in the problem it solved, and the old scarcity premium is shrinking.
A rules file moves the odds. It does not bind anything. HANDBOOK.md measures the gap between policy and compliance.
The control group quit and the benchmarks broke. There is no shared instrument for what AI does to engineering work, so carry your own.
Every field that solved delegated work solved it with a name on a line and a license that can be taken. AI governance is a hunt for a way to skip that step.
A demo proves a thing is possible. It says nothing about how often it works, and production runs entirely on how often. Possibility is not reliability.