Most teams treat AI as a new universe with its own rules. It is not. AI is a new workload, and the disciplines that made the rest of the software lifecycle reliable, observability, FinOps, and governance, are the same ones it needs.
This talk makes the case for putting LLMs and agents on the same Golden Paths your services already run on, and looks at the operational blind spots that open up when teams skip those disciplines in the rush to ship.
What the talk covers
Why AI gets treated as magic infrastructure, and the operational blind spots that creates at scale.
Putting AI on the Golden Paths you already have, instead of building a parallel, ungoverned stack beside them.
The three disciplines that make it real: observability so you know what it is doing, FinOps so you know what it costs, and governance so you know who owns the decisions.
Also at the summits
Across the two co-located events in London, I am also part of a roundtable on whether a platform is genuinely ready for AI, or just exposing the friction that was already there.
Who this is for
Engineering and platform leaders putting AI and agentic systems into production, and the teams responsible for keeping them observable, affordable, and accountable.