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Built, then measured
Engineering write-ups on building with AI, every number from a run committed beside it.
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EvalsAsk the book
What a golden set found in my book's chatbot
Thirty-two questions, three runs and under two dollars. The book's index had never built, code questions never got their code, and my scorer was older than my rules.
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Tuning the demo
The typewriter effect, with a fact-checker in the way
The demo checks every answer against its sources, so I taught it to type one checked sentence at a time. The eval set caught a version losing 8 of 26 answers.
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Running the shop
Teaching my site to run the shop
Every five minutes my site works out what is due and does each thing it can, as me. It tells me only what needs my hands, one line with one button.
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Finding clients
Teaching my site to find its own prospects
One button on my admin page searches the web for companies that may need my services, checks each find in code, and learns from earlier finds.
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Tuning the demo
Giving the answer the rest of the point
Adding each passage's neighbours answered all 5 two-passage questions, up from 4, at 60% more a question, over my 50% limit. I switched it on anyway.
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Tuning the demo
“The passages don't list his job history.”
My demo chatbot said my résumé listed no jobs. How I fixed it test-first, then tuned the pipeline with a 25-question eval on live models, for $1.96.