Abstract
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.
Tara walks through her team’s journey to AI success and why it was both simple and satisfying, and at the end of the day she was again reminded that no matter what the technology, it’s the people that matter when it comes to transforming your business.
$2,955, Conference (3 days). Current pricing ends October 13th. 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 Navigating AI Panic in Software Engineering Details coming soon. 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 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.