AI has raised the baseline for writing code, but it has also raised the ceiling for real engineering. In this talk, I’ll show why senior engineers are more needed than ever and how their role shifts from producing code to owning systems, risks, and outcomes. We’ll explore what to delegate to AI, what must stay human, and how to work with AI without losing judgment or responsibility.

AI can now draft code, tests, and documentation in minutes. This has created excitement and fear at the same time. Many developers wonder what their role will look like when machines can already produce so much output. In practice, however, building real systems with AI reveals a different reality: ambiguity, integration, and accountability still belong to humans.

In this talk, I’ll share lessons from building AI-powered features in production and explain why technical skills alone are no longer enough. The leverage of senior engineers comes from system thinking, product judgment, and risk ownership. We’ll look at where AI is genuinely helpful, where it consistently fails, and how hidden failure modes appear when AI is placed inside real workflows.

You’ll learn a practical framework for deciding what to delegate to AI and what must remain human-owned. We’ll discuss how to design constraints, feedback loops, and evaluation strategies so AI becomes a useful teammate instead of a source of silent bugs. Finally, we’ll connect these ideas to career growth and show how senior engineers can increase their value by shifting focus from output to outcomes.