Sustainable Software Engineering in the Age of AI

You'll walk away able to: keep shipping with AI without drowning in code review or burning out.

Register NowPresented bySiva Prasad Reddy Katamreddy

• ✓Decide what must always be reviewed and how much to trust AI-generated code
• ✓Use tests, static analysis and architecture rules as automated quality gates
• ✓Keep AI agents on a leash with specification-driven development and small, verifiable changes
• ✓Avoid review fatigue and cognitive overload as code volume grows

AI coding agents have fundamentally changed how we build software. We can generate code faster than ever, but faster coding doesn't necessarily mean sustainable software development. This session explores the less-discussed challenges of AI-assisted development: increasing code volume, context switching, comprehension debt, over-reliance on AI, inconsistent quality, and the pressure to continuously keep up with rapidly evolving tools.

Should we review AI-generated code? Absolutely! But reviewing everything line-by-line isn't sustainable either. We'll explore a pragmatic approach to maintaining quality without turning developers into full-time AI-code reviewers:

* What should always be reviewed? * How much trust should we place in AI-generated code? * How can tests, static analysis, architecture rules, and automated verification act as quality gates? * How can specification-driven development and smaller, verifiable changes keep AI agents under control?

Finally, we'll look beyond code quality at developer sustainability. If AI makes writing code cheaper, it can also make producing and reviewing more code the default. We'll discuss practical strategies for avoiding burnout, review fatigue, and AI-induced cognitive overload—so that AI becomes a force multiplier rather than another source of pressure.

Siva Prasad Reddy Katamreddy

Developer Advocate at JetBrains

Siva is a Developer Advocate at JetBrains with over 19 years of experience building scalable, distributed enterprise systems. His career spans hands-on software development, architecture, and cloud-native system design across domains such as banking and e-commerce.