Agentic coding changes how code is produced. It doesn’t change who owns it. If an engineer checks in agent-generated code, that engineer is accountable for it. The agent doesn’t carry the production support burden. The model doesn’t explain the code 18 months later. The engineer and the team do.

This talk focuses on accountability in the AI coding era. Engineers must understand what they merge, explain why it was built that way, verify it against actual system behavior, document significant decisions, and ensure another engineer can safely modify it later. AI raises the consequences of weak ownership because agents can generate far more code than 1 engineer could manually produce.

The session gives engineering managers and teams language they can use to reset expectations around AI-generated code. It addresses a common failure mode: treating AI output as something external to the engineer’s craftsmanship. Agentic coding should make engineering professionalism more explicit.

Attendees will leave with a clear ownership standard for AI-generated code: if you merge it, you can explain what it does, why it was built that way, what it touches, how it was verified, and how it fits the system.

This talk directly references the author's Engineering Standards for Agentic Software Development, especially AC1, AC2, DN2, DN3, VT1, and AM4: https://www.linkedin.com/pulse/engineering-standards-agentic-software-development-edensoft-park-ki1se

Target audience:
Engineering managers, senior engineers, tech leads, directors, and organizations defining accountability standards for AI-generated code.

Preferred Session Duration:
50 mins including Q&A