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AI-Friendly Code: The Missing Link for Speed with Quality • Adam Tornhill • GOTO Copenhagen 2026
Chapters
- 0:00Intro
- 0:34The more things change - The more we realize that software engineering is hard
- 1:20Coding might be dead. Why code with a Agents?
- 4:06The core Challenges for AI Agent
- 6:20Code Health - How easy code is to understand
- 10:14Research on AI - What we have found
- 12:49Questioning The Relevance
- 16:00The Illusion of Instant Software
- 18:57Success Criteria - Safeguard any AI generated or edited code
- 21:27Success Criteria - Make Buisness critical code AI-ready
- 23:15Make code healt uplift agents
- 25:43Case Study - Refactoring at scale with agents
- 34:48The Foundation - Adapt to the local problems at hand
- 37:17Success Criteria - Software design is more important than ever
- 42:52Refactoring code - The next challenge
- 43:34Summary - Wrap up and resources
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This presentation was recorded at GOTO Copenhagen 2026. #GOTOcon #GOTOcph Join us at GOTO Copenhagen 2027, October 4–8. https://gotocph.com/2027?utm_source=youtube&utm_medium=video&utm_campaign=cph26-talks Adam Tornhill - Founder and CTO at CodeScene Programmer, psychologist, Lisp hacker, speaker and author of several books including "Your Code as a Crime Scene" @adamtornhill2546 RESOURCES https://x.com/AdamTornhill https://www.linkedin.com/in/adam-tornhill-71759b48 https://www.adamtornhill.com/ https://github.com/adamtornhill https://gotopia.tech/experts/3/adam-tornhill ABSTRACT Have you seen early productivity gains from AI, only to watch them disappear under growing complexity and production incidents? You're not alone. There's a common reason: many production systems already struggle with technical debt. When AI agents enter the development loop, that debt becomes a multiplier. Poor-quality code not only increases defects and costs. It dramatically raises AI risk by driving high breakage rates, turning promising AI agents into legacy code generators rather than genuine help. Fortunately, there's hope on the horizon. In this talk, Adam Tornhill shows how organizations can achieve both speed and quality with AI. Backed by large-scale empirical studies on AI coding and developer productivity, we separate what works from what doesn't in real-world systems. Building on these findings, we then look at a practical framework for driving and sustaining AI-friendly code at scale. The AI revolution is here. Is your code ready? TIMECODES 0:00 Intro 0:34 The more things change - The more we realize that software engineering is hard 1:20 Coding might be dead. Why code with a Agents? 4:06 The core Challenges for AI Agent 6:20 Code Health - How easy code is to understand 10:14 Research on AI - What we have found 12:49 Questioning The Relevance 16:00 The Illusion of Instant Software 18:57 Success Criteria - Safeguard any AI generated or edited code 21:27 Success Criteria - Make Buisness critical code AI-ready 23:15 - Make code healt uplift agents 25:43 Case Study - Refactoring at scale with agents Case study - The code quality improvement 34:48 The Foundation - Adapt to the local problems at hand 37:17 Success Criteria - Software design is more important than ever 42:52 Refactoring code - The next challenge 43:34 Summary - Wrap up and resources Download slides and read the full abstract here: https://gotocph.com/2026/sessions/3981 https://bsky.app/profile/g
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