Official Session Summary
Pulled from the live conference page.
AI is a force multiplier that turns weak standards into architectural chaos. As code review becomes the ultimate bottleneck, engineering teams must bridge the gap between human intuition and machine output. This talk introduces a holistic framework for designing quality-driven systems around AI coding. We'll explore how to codify development best practices into machine-readable guardrails. We'll walk through how to leverage context engineering at scale to ensure your AI code tools respect your system’s design, preserving long-term maintainability without sacrificing the speed of the AI era. Attendees will learn how to embed code quality into the SDLC from AI-generated output. They will leave with a practical methodology for encoding best practices into their workflow, where developers already operate (CLI, IDE, and Git).
Speaker Background
Quick context on the person or people on stage.
AI Principal Developer Advocate at Qodo, working at the intersection of AI-assisted coding, workflow quality, and developer education.
Why This Slot Matters
A compact framing layer for navigating the conference.
This is one of the more substantive abstract-backed sessions on the schedule; worth opening when you need enough context to decide whether to stay in the room.