AI for Tech Teams
Most teams have added AI to the process they already had. A copilot here, an agent there, the same workflow underneath. That gets you faster typing. It does not get you a different way of building software.
The next step is harder and more valuable: redesigning the development process itself around what AI can now do.
That means treating delivery as a set of goals and loops rather than a fixed sequence of handoffs. It means dynamic workflows that adapt to the task instead of one pipeline for everything. And it means agent swarms doing the work that used to sit in a single developer's queue, with humans steering and reviewing.
This is the road to a code factory: a system where specs go in, working software comes out, and the team spends its time on direction and judgment rather than mechanical steps. We'll show what we've built so far, what works in production, and what is still on the edge.
We're redesigning development processes inside live engineering teams right now, including our own. The loops, dynamic workflows, and agent swarms we'll show are how we build, not a concept deck.
We'll show what runs in production today next to what we're still testing. The difference in polish is the point: it proves we operate in production and stay on the edge.
If you're deciding how much to invest in changing how your engineering organisation works, this session gives you a working model to judge against before you commit.
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