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Talk · 25 min

Migration or migraine: What no one tells you about using LLMs

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Time and room for this session are published in October. when the timetable goes live.

We had a task stuck forever in our backlog. A task so simple, yet so tedious that our team just kept postponing it. Even our bored intern didn't want to do it. The task: upgrade each framework used in our managed authentication solution to the latest version, without ruining our test coverage or breaking production. A task perfect for AI. Or so we thought...

As it turns out, some coding tasks lend themselves to AI application better than others. Is a one-time migration involving ~100 components of a system actively used in production a good use case? How does the hype compare to the reality?

In this talk, I'll share our experience using LLMs to perform a seemingly simple but surprisingly challenging migration. I'll discuss what went as expected, what surprised us, share the takeaways related to developer experience, efficiency, and quality, and go over what both skeptics and optimists get wrong about AI.

Main tools & technology
Research reviews, not limited to specific LLMs or technloogy.
Topics
Lessons Learned & Anti-PatternsSpec-Driven & Agentic SDLC
Sponsors & Partners
Main Sponsor
copebit — Main Sponsor
Gold
AWS
Silver & Featured Partners
Atlassian Flagsmith namespace re:cinq OpenAI — Workshop Partner Migros Online — End User Partner FHNW Hochschule für Informatik — Educational Partner
Bronze & Partners
BI Concepts Noser Engineering Puzzle ITC Team Extension Your Sidekicks AG AI & ML Events CH Open dev.events Java User Group Switzerland Rocket Engineers SwissDevJobs ZurichJS Conference