AI can generate a function in seconds. It can scaffold an API, write tests, refactor a module and even explain its own code. But when that code reaches production, who is responsible for deciding whether it is actually correct?

This session looks beyond the “AI makes developers faster” story and into what happens when AI becomes a real part of the software development lifecycle. We’ll explore where AI-assisted development genuinely helps, where it creates new failure modes, and why engineering judgement becomes more important - not less, as AI writes more of the code.

Through practical examples and real-world development scenarios, we’ll examine AI-generated code, testing, debugging, architecture, security, code review and the decisions that still need a human owner. We’ll also look at the uncomfortable gap between generating code quickly and being able to trust it.

The goal isn't to convince developers to use AI - or to avoid it. It is to develop a better engineering workflow for a world where writing code is increasingly easy, but owning the consequences of that code is still very human.