Practical notes on making AI work.
How to test an AI feature, investigate a bad answer, and control cost after launch. Written for teams making real decisions.
How to Evaluate an AI Feature Before You Ship It
A pass rate is only useful when you know how many cases were tested. See how to build a repeatable baseline and report the uncertainty around it.
What to Log So You Can Debug an AI System Later
When an AI answer goes wrong, the answer alone may not show why. Record the inputs, versions, and outcome of each model call so your team can investigate.
Why Your AI Bill Keeps Climbing
Before changing vendors, find out what each AI request sends, repeats, and costs. These worked examples show where design choices can reduce spend.