# Teams, leadership & work — AI Engineer Sydney 2026

> Agents change roles, measures and handoffs as much as they change tooling. This collection looks at the leadership, craft, team design and human judgement required to make adoption productive rather than merely fast.

Canonical page: https://webdirections.org/ai-engineer/topics/teams-leadership/
Program status: The speaker lineup and talk descriptions are public. Session days, times, rooms and the full timetable have not yet been published.

## Published talks

- [Half our handoffs are the bot's idea](https://webdirections.org/ai-engineer/speakers/adeline-yaw/) — Adeline Yaw
  About one in four conversations with WordPress.com's AI support bot ends with a person. In about half of those, the bot suggested it. These are two different problems. In one, the user asks for a person. In the other, the bot decides on its own to stop. On paid plans, when a user asks for a person, we hand the conversation to our support team with as few…
- [Lessons from Economics for the Human / Agent Software Workforce](https://webdirections.org/ai-engineer/speakers/daniel-nadasi/) — Daniel Nadasi
  AI is reshaping software engineering, creating uncertainty about how engineering roles will change as increasingly capable systems take on work that was once performed by people. While no one can predict the future with certainty, history offers examples of how technical innovation has transformed work in other industries and provides useful ways to think…
- [The Model Wasn't the MOAT: How 10 Design System Engineers Turned Platform Knowledge into Enterprise AI](https://webdirections.org/ai-engineer/speakers/sudharsanam-narasimhan/) — Sudharsanam Narasimhan
  Most enterprise AI strategies begin with models, central AI teams, and a list of potential use cases. We started somewhere else: with a platform organisation that already shaped how more than 2,000 frontend engineers built software. A team of 10 engineers working across design systems, internationalisation, and accessibility had something a general-purpose…
- [Token usage is the new lines of code (and it's just as useless)](https://webdirections.org/ai-engineer/speakers/fawaz-ahmad/) — Fawaz Ahmad
  Canva hit mid-2026 with every AI metric a vendor could hand us and no answer to the only question the business actually cared about: is this working? Adoption flattened at around 85% of ~3,000 engineers, and the number stopped telling us anything. AI touched 43% of PRs, PR volume was up 44% year over year (and growing week-over-week), but none of us could…
- [The five stages of losing our craft](https://webdirections.org/ai-engineer/speakers/andrew-murphy/) — Andrew Murphy
  Your best engineer won't use AI tools. Your tech lead is using them but won't tell anyone. Your new grads don't understand what the fuss is about. And you, the leader, are supposed to have answers for all of them. I've had some version of this coaching conversation every week for the past year. What I've found is that teams aren't just "resistant to change."…
- [Management Is Dead, Leadership Is Not](https://webdirections.org/ai-engineer/speakers/inga-pflaumer/) — Inga Pflaumer
  Engineering teams are getting smaller. A team of four with strong AI tooling now ships what took twelve people two years ago, and the org chart has not caught up. The first layer to feel it is middle management - the coordination tier that existed largely to move information between people who were too numerous to talk to each other directly. When the team…
- [Shipping together in an AI native team](https://webdirections.org/ai-engineer/speakers/sandra-arato/) — Sandra Arato
  While building an AI agent for marketing workflows at Leonardo.Ai, we discovered that the traditional design-to-engineering handoff was failing. A static mock could describe a happy path, but not how an agent would group assets, select tools, recover from errors, or change behaviour when its underlying model changed. Engineering could implement the interface…
- [The AI year: how we work, hire and grow now](https://webdirections.org/ai-engineer/speakers/fiona-chan/) — Fiona Chan
  For a lot of teams, this was the year AI stopped being an experiment and started being part of the job. Shipping got faster, but so did the pace, the pressure and the pile of code waiting for review. Drawing on Lookahead's 2026 research with people across Australian tech community and interviews with over 20 tech leaders, Fiona will share what's really…

The timetable is not public. This page does not imply a day, time, room or track.

- [Explore the whole programme](https://webdirections.org/ai-engineer/program/)
- [Conference overview](https://webdirections.org/ai-engineer/index.md)