Technical debt is something every technical professional has encountered, and most will tell you they know exactly what it is. But do they? Without a shared definition, it becomes the problem that never gets prioritised, the risk that never gets funded, and the silent drag on delivery that compounds over time.

In this session we'll establish what technical debt actually is, why organisations struggle to address it, and why treating it as a business liability rather than a technical inconvenience changes the conversation.

Then we'll get practical. Your Git repositories are a goldmine of behavioural data. We'll walk through how to mine them to surface the debt that matters most, hotspot analysis, change coupling, stale code, and commit message patterns. We'll also look at how observability, CI/CD tooling, and incident data can be combined with Git signals to build a complete picture.

Finally, we'll look at AI, both as a source of new technical debt and as a tool for managing it. You'll leave with a clear framework for defining, finding, and prioritising technical debt, and the practical tools to start making it visible to the people who need to act on it.