Our engineering organisation had no AI capability, no machine learning engineers, and a roadmap that had started to assume both. We did not go and hire an AI team. We turned the team we had into one.

This is an honest account of how that went: what worked, what wasted a quarter, and what I would refuse to repeat.

We will spend the time on mechanics rather than motivation. How to find who in your organisation actually wants this, which is rarely who you expect. How much delivery capacity you have to give up, and where to take it from without lying to yourself about it. Why handing everyone a training budget produces nothing. How to sequence the first three projects so the organisation learns something, instead of shipping one impressive thing that only its author understands.

Then the harder parts. The senior engineer who quietly thinks it is all hype, and is sometimes right. The prototype that demos beautifully and cannot be operated. The governance conversation you will lose if you start it late. The moment leadership assumes the second AI feature will take a tenth of the time the first one did.

Presented from the seat where those tradeoffs land. I am a VP of Engineering who still reads the pull requests, so this is decisions, costs and outcomes rather than maturity models and transformation frameworks.

Takeaways

- A sequencing model for the first AI projects that builds capability instead of debt
- How to find and fund internal capacity honestly, including what you stop doing
- The recognisable patterns of resistance, and which of them are legitimate signal
- Where to put governance, security and legal so they accelerate you rather than block you
- Realistic timelines from first experiment to something on-call can actually support

Preferred duration: 45 minutes including Q&A. Can be delivered in 30 or 60 minutes on request.

Target audience: engineering leaders, engineering managers, architects and tech leads. Also useful for senior individual contributors who are being asked to lead an AI initiative. No machine learning background required.

Level: leadership and organisational. Very little code in this session.

Technical requirements: my own laptop (USB-C / HDMI).

First public delivery: not yet delivered.