A conversation with The Secure Disclosure covering the full arc from DevOps to AI-native development — and why the engineering discipline hasn’t changed, even as everything around it has.
The developer as ops person
The central irony: developers using AI coding assistants have effectively become operations people. They receive code they didn’t write and must review, understand, and take accountability for it. This mirrors the historical DevOps challenge — ops teams receiving applications they didn’t build but had to run. All dev people have now become an ops person.
Trust calibration
How deeply should you review AI-generated code? It depends on context, like self-driving cars — some people trust it on highways but not in cities. Developers need to calibrate trust based on criticality and their ability to verify correctness. And there’s a recursion problem: if AI writes both the code and the tests, who verifies the tests?
Intent over implementation
The shift toward specifying what you want rather than writing how to do it. The fundamental skill changes — from writing code to clearly articulating intent and evaluating whether the output matches. The emerging metric: how many times do I have to wrench the AI before it gets what I mean.
Team Topologies for AI scaling
Three pillars for organizational AI adoption: a platform team providing AI tooling and infrastructure, an enablement team helping other teams adopt AI practices, and a governance function setting guardrails and risk frameworks. Without this structure, AI adoption stays ad hoc.
AI amplifies what’s already there
AI doesn’t create technical debt — it amplifies existing debt by making its consequences more visible and more costly. If your documentation is bad, AI agents produce bad results from it. This creates a forcing function for better knowledge management.
AI in incident response
Beyond suggesting possible causes — agents that spin up parallel instances, test hypotheses simultaneously, and narrow down root causes through active experimentation rather than passive analysis. Moving from AI as advisor to AI as active participant in operational work.
Watch on YouTube — on The Secure Disclosure channel
This summary was generated using AI based on the auto-generated transcript.