Show notes
In this conversation, RedMonk's Kate Holterhoff talks to Mike Basios, CTO and Co-founder of TurinTech AI, about the new set of problems AI is introducing for engineering organisations, and what happens when you treat your entire stack—application code, data pipelines, inference systems, agent workflows, GPU and CPU kernels—as measurable artifacts that can be systematically validated and continuously improved. Mike explains how AI is fundamentally changing both how engineering gets done and what engineering is being asked to deliver. The conversation explores a central tension: while AI tools have made individual developers dramatically more productive, that velocity is creating a growing backlog of unreviewed, unoptimized code, and an infrastructure that was never designed to support the dozens of concurrent agents a single developer might now depend on. Mike argues that the engineering role is shifting from problem-solving to outcome-verification, and that teams who don't define what "good" looks like before they build will struggle to compete as the quality of the solution, not the speed of its creation, becomes the key differentiator. TurinTech's answer to this challenge is a measurement-first platform that applies evolutionary, self-improving techniques to continuously benchmark and optimize code across any domain where performance can be quantified.This RedMonk conversation is sponsored by TurinTech AI.Show notes: https://redmonk.com/videos/mike-basios-on-why-ai-era-engineering-needs-a-measurement-first-approachChapters:00:00 The Impact of AI on Software Engineering03:41 Shifting Roles: Engineers as AI Managers07:35 Infrastructure Challenges in AI Development11:10 Reliability and Performance of AI Systems19:09 Measuring Success in AI Optimization26:27 The Future of AI in Software Development