GOTO - The Brightest Minds in Tech
The GOTO podcast seeks out the brightest and boldest ideas from language creators and the world's leading experts in software development in the form of interviews and conference talks. Tune in to get the inspiration you need to bring in new technologies or gain extra evidence to support your software development plan.
GOTO - The Brightest Minds in Tech
Continuous Delivery in a World of Constant Change • Abby Bangser & Dave Farley
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This presentation was recorded at GOTO Copenhagen 2025.
https://gotocph.com
Abby Bangser - Principal Engineer at Syntasso & Team Topologies Advocate
Dave Farley - Bestselling Author, Founder & Director of Continuous Delivery Ltd.
RESOURCES
Abby
https://bsky.app/profile/abangser.bsky.social
https://twitter.com/a_bangser
https://github.com/abangser
https://www.linkedin.com/in/abbybangser
https://www.syntasso.io/members-area/abby/profile
Dave
https://bsky.app/profile/davefarley77.bsky.social
https://www.continuous-delivery.co.uk
https://linkedin.com/in/dave-farley-a67927
https://twitter.com/davefarley77
http://www.davefarley.net
DESCRIPTION
Dave Farley and Abby Bangser open with a clear statement: Continuous Delivery isn't a relic of the pre-AI era — it's the foundation that makes the AI era survivable. Dave's definition is simple but consequential: software should always be in a releasable state, verified after every small change. That's not just a workflow preference; it's the same incremental, hypothesis-driven approach that underpins science and engineering. In an AI-assisted world where code can be generated far faster than humans can reason about it, the discipline of small, safe, verifiable steps becomes more critical, not less. The danger isn't AI writing bad code — it's AI writing a lot of code very fast that nobody is properly checking.
The conversation turns to a genuinely alarming DORA report statistic: 70% of developers using AI tools don't distrust the output. Abby draws a parallel to the long-running debate over whether developers can be trusted to test their own code — they usually can't, without a deliberate change in perspective. The same challenge applies to AI-generated code: you need to consciously shift from "prompter" mode to "verifier" mode, and most developers aren't making that switch. Dave closes with a surprising note of optimism: AI may be the industry's best-ever opportunity to finally get XP practices — small increments, automated tests, continuous feedback — embedded into how teams actually work. Not because anyone chose to adopt them ideologically, but because working without them while using AI is visibly, measurably risky.
Read the full abstract here:
https://gotocph.com/2025/sessions/3779
RECOMMENDED BOOKS
Kief Morris • Infrastructure as Code • https://amzn.to/4e6EBQc
Matthew Skelton & Manuel Pais • Team Topologies • http://amzn.to/3sVLyLQ
Dave Thomas • simplicity • https://amzn.to/43FghBJ
Dave Farley & Jez Humble • Continuous Delivery • https://amzn.to/3ocIHwd
David Farley • Modern Software Engineering • https://amzn.to/3GI468M
Dave Farley • Continuous Delivery Pipelines • https://amzn.to/3rjetdi
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