Speaker
Abstract
AI is changing software development faster than our engineering practices are evolving, and yet many teams are facing growing pressure to ship features faster. But moving faster can create three related threats to software health: technical debt, cognitive debt, and intent debt.
The core question is: what can we do about these consequences of moving fast? In this talk, I’ll explore new approaches for helping humans and AI maintain understanding as software systems evolve: understanding how the system works, why it was built in a certain way, and whether it still meets the intended user goals and design constraints. I’ll share some practical ideas for measuring, managing, and mitigating these three types of debt in software created by humans and AI agents working together.
I’ll conclude by asking a broader question: as we delegate more work and decisions to agents, how do we make sure humans still understand what is happening and stay in control?
Topics
$2,995, Conference (3 days). Current pricing ends November 10th. All pass options.
QCon San Francisco 2026 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.
Part of the track
Engineering the Developer Experience Hosted by Ankit Jain Co-Founder & CEO @AviatorFrom the same track
Wednesday 18 November
10:35 Ballroom A Session Features vs Futures Kent Beck Original Signer of the Agile Manifesto, Author of the Extreme Programming Book Series, Rediscoverer of Test-Driven Development Details coming soon. 11:45 Ballroom A Session Software Engineering No More Small Systems, How AI May Bring Large System Problems to Everyone Adam Bender Technical Lead for Enterprise Engineering @Google Once you figure out how to use AI to make your organization productive, you will soon find you have a whole new set of problems. While some of those problems will be novel thanks to LLMs, many of them are just the result of there being "more stuff". 13:35 Ballroom A Session Growing Engineers in the Era of Agentic Coding Adam Berry Staff Engineer @Netflix Early-career engineers are learning the craft in an environment where the surface they touch is often an agent, not a codebase. The instinct is to treat this as a rupture in how engineers grow. It isn't. 14:45 Ballroom A Session Software Understanding Shipping Faster, Understanding Less Margaret-Anne Storey Professor of Computer Science @University of Victoria, Co-Creator of the SPACE Framework and the Triple Debt Model for Software Health, a Canada Research Chair in Human and Social Aspects of Software Engineering AI is changing software development faster than our engineering practices are evolving, and yet many teams are facing growing pressure to ship features faster. But moving faster can create three related threats to software health: technical debt, cognitive debt, and intent debt. 15:55 Ballroom A Session The Diary of an AI Adopter: How I Went From Skeptical to Enthusiastic in Our Organization’s AI Migration Efforts Tara Hernandez Vice President @MongoDB & Lecturer at the UC Santa Cruz Center for Innovation and Entrepreneurial Development From market research reporting questionable success of AI adoption in enterprise, to CEOs announcing layoffs due to AI, to companies announcing they’re cutting back or eliminating AI due to prohibitive costs or technical missteps, it can be hard to know what the path to success should look like.