The challenge

AI coding assistants are making headlines for generating new code—but what about the legacy code that dominates enterprise systems? Those billions of lines represent security risks, tech debt, and barriers to shipping software at scale.

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What you’ll learn in this on-demand webinar

Higher level topics

• How did you sell upper management on the investment (code migration work to business value)?
• What are the benchmarks for assessing AI based change? How do you measure success? Do you optimize for accuracy, correctness, or scale?
• Human reviews bottleneck: how to manage the influx of changes from AI? How do you build trust?

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Deeper technical topics and challenges

• Verification: suppose AI does a modification, how do I add verification steps to prove it's correct? For every iteration of proposed change for AI?
• Code search: How would you leverage code search to find the occurrences of certain types and APIs? How do you find every transitive use of Jackson for the case when that is important to a specific transformation?
• How do you identify and prioritize migrations based on what's in production vs customer facing, and how do you tie that back into source code: Do I care to update code that is not running anywhere?

Meet the panel

• Rui Abreu, Research Software Engineer, Meta
• Stoyan Nikolov, Principal Software Engineer, Google
• Laura Tacho, CTO, DX
• Jonathan Schneider, CEO & Co-founder, Moderne / OpenRewrite
• Moderator: Rooz Mohazzabi

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