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$2,955, Conference (3 days). Current pricing ends October 13th. All pass options.
76%
senior dev or higher
1:11
speaker ratio
60+
practitioners
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.
From the same track
Wednesday 18 November
10:35 Seacliff ABC Session Builder-Driven Development Jyothi Nookula Product Leader Director with 13+ Years Driving AI Product & Platform Innovation, Previously @Meta, @Amazon, and @Etsy Details coming soon. 11:45 Seacliff ABC Session Staff Plus Engineering Legacy as Leverage: How Brownfield Work Builds Technical Judgment Shine Garg Founder of Uncharted Path Breakthrough, Former Staff Software Engineer, 15+ Years Building and Scaling Backend, Data, Machine Learning, and Platform Systems Legacy systems are often treated as a necessary evil: work to be endured before moving on to more “real, strategic” projects. 13:35 Seacliff ABC Session AI/ML The Death of the Code Review Laurie Voss Head of Developer Relations @Arize AI, Co-Founder of npm, Inc., Developer for 30+ Years Code review was built for a world where humans wrote all the code. 14:45 Seacliff ABC Session AI You Can't Read the Code Anymore - Verifying Software in the Age of AI Omer van Kloeten Principal Engineer @Forter, 25+ Years in Software Engineering, Now Building an AI-Agent Framework to Tame Legacy Systems and Reduce KTLO AI writes most of the code now, so the hard part of engineering has moved from authoring to the part we’re worse at - verifying. With the incentives all pushing toward shipping faster and faster - the rational move is to skim the diff, click through a little manual QA, and ship on vibes. 15:55 Seacliff ABC Session When Everyone Can Code, Who Owns Production? Sanjay Singh Staff Software Engineer @LinkedIn Specializing in Large-Scale Distributed Systems, Traffic Infrastructure, Reliability, and Zero Trust Security AI is making it dramatically easier to create and change software, but writing code is only one part of the software lifecycle. Every change still needs to be deployed, observed, operated, diagnosed, and kept reliable in production.