Note / 2026-09-15

AI in engineering teams, the people on call see the cost and the enthusiasts see the wins

Charity Majors, cofounder of Honeycomb, on why every engineering team has two camps about AI, why both are right, and why the line between them follows the on call rotation. What closed the gap in one client team was one page of shared numbers.

For CTOs and engineering leads whose team is split on AIViaro Networks1 min read
AI in engineering teams, the people on call see the cost and the enthusiasts see the wins

A leader who spent 2025 skeptical about AI in software now says the question is no longer whether engineers will "ship code we have never read", in the podcast's own words. It is what it would take.

Charity Majors, cofounder of Honeycomb, on The Pragmatic Engineer podcast, August 12, 2026. Her frame is a trust account: if you debit trust when the code is created, because an agent wrote it and no human read it, that trust has to be built back somewhere else, in tests, evals and conformance checks that prove the new code behaves within the bounds of the old. Our reading, not hers: that comparison needs an old behavior to check against. For new functionality there is none, so the confidence has to come from acceptance criteria written before the code and tests that run against them. She also describes the two camps in every company: the enthusiasts who see rewrites and toil disappearing, and the people on call who see incidents rising, and says neither is making it up.

What we see inside client teams, SaaS companies and IT departments with 10 to 200 engineers, confirms the frame. The teams that hold are not the ones that read every line. They are the ones that moved the proof in front of the human: checks that run before a reviewer is assigned.

Simon Willison, creator of Datasette, put the bar on X: production code written by an agent should be held to a higher standard than code written by a person. That is what the trust account pays for.

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