Sachin Gupta

This talk argues that AI agents, capable of performing high-impact actions like sending money or modifying databases, are being deployed without the safety infrastructure common in traditional web development. It introduces six specific types of feature flags—prompt variants, tool access, model routing, memory policy, autonomy level, and kill switches—that are necessary to manage the unique behavior surfaces of agents and prevent incidents. The core thesis is that applying established web development disciplines, particularly robust kill switches and phased rollouts, is crucial for controlling and safely iterating on AI agent functionality.

This talk introduces ReviewDebt, a framework for quantifying the accumulating gap between code generated by AI agents and the human review, trust, and understanding applied to it. It argues that while AI agents increase code production speed, they also create a form of debt that compounds and impacts human attention, architectural consistency, and velocity expectations. The framework aims to provide a measurable number for this debt, enabling teams to manage it effectively.