Since the dawn of software development, we've struggled with a huge disconnect between the management world and the engineering world. We try to explain our problems in terms of "technical debt", but somehow the message seems to get lost in translation, and we drive our projects into the ground, over and over again.

What if we could detect the earliest indicators of a project going off the rails, and had data to convince management to take action? What if we could bridge this communication gap once and for all?

In this session, we’ll focus on a key paradigm shift on what to measure — rather than measuring the code itself, you’ll learn a technique for measuring the developers’ *experience* with the code, and how to build explicit risk models for project decision-making.