AI-Native
engineering:
the machine does
the work. I judge it.
I'm Alpesh Nakrani, Chief Revenue Officer at Devlyn. I help companies go AI-Native: advising on which AI bets are real, building delivery pods that ship, and teaching teams the operating model behind it. Fourteen years building and selling software, ten as CTO and COO. I also write about all of it, 33 books and counting.
AI-Native is not AI-assisted. The machine does the whole job; the human's role narrows to one thing: judgment. Specifying intent, evaluating output, owning the call. Everything I write follows from that single shift.
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AI-Native
How the machine took the work and left us the judgment
For three years we called it AI-assisted and meant autocomplete with ambition. AI-Native is the harder claim: the model does the job, and the only thing left for us is judgment. This book draws the line precisely: where the machine is now doing real work, where it is not, and what an organization has to rebuild once the bottleneck moves from production to evaluation.
Selected books
What I write about
Latest writing
LLM Evaluation: Measuring What Will Break
LLM evaluation is the harness that gates a real deploy. Learn what to measure, which metrics lie, when to trust an LLM judge, and who should own it.
How to Build an LLM Evaluation Framework
A good LLM evaluation framework tests what will break in production: a golden set from real traffic, task metrics, blinded rubrics, and a drift cadence.
LLM Evaluation Metrics That Matter (and the Ones That Lie)
The LLM evaluation metrics that matter measure what breaks in production. The ones that lie measure what looks good in a deck. Here is how to tell them apart.





