Coding agents like Claude Code barely write bad code anymore. They write good code that misses the point. The failure moved from code time, where the agent couldn't write the function, to intent time, where it wrote a perfectly fine function for a task that wasn't quite the one in your head. That's misalignment, not incompetence.
Our reflex is more review, more tests, more guardrails. All of it runs downstream of the failure. The miss already happened before any of those fire, so you're doing an autopsy instead of preventing anything.
This talk shows the fix: work backwards. Before your agent writes a single line, you and the agent together define concrete, measurable success criteria and the validation strategy that proves them. Only then does it implement. It's TDD repurposed for AI agents! The validation-first plan gives the AI agent an actual contract for the task at hand.
I'll walk through it live on a real codebase, in Claude Code, on an ordinary task: the naive version that passes every check and still does the wrong thing, the plan that makes "done" explicit, and the same task done validation-first. Then the part that compounds, which is that when a miss does slip through you don't just patch the bug, you evolve the system so the same class of mistakes goes away over time. You own the plan, the agent owns the typing.
Attendees leave with three things they can apply on their next ticket, with no new tooling required.
This talk has been presented at AI Coding Summit NYC, check out the latest edition of this Tech Conference.
