Nick Nisi and Zack Proser from WorkOS explore how to move "Beyond Done" with AI agents, ensuring their work is truly complete and reliable. They demonstrate building robust verification loops using custom CLIs, browser tools, and LLM judges, allowing agents to self-check and self-correct, preventing costly mistakes and accelerating development velocity for a technical audience.
AI teams are deploying advanced agent systems without the fundamental safety mechanisms (feature flags, canaries, kill switches) that web teams adopted over a decade ago. This oversight leads to critical incidents like data deletion and financial loss. This talk introduces six agent-specific feature flag types—for prompts, tools, models, memory, autonomy, and sub-agents—and outlines a practical playbook for secure AI deployment, emphasizing the critical role of a pre-wired kill switch to manage the high blast radius of AI agents.
This talk explores the history of high-assurance software, from the near-perfect code of the NASA Space Shuttle to the Airbus A320. It argues that while these rigorous engineering and formal verification practices were once too expensive for mainstream use, the economic shift brought by AI and agentic coding can make aerospace-level reliability a practical reality for a wide range of applications, solving the key quality limitations of current AI-generated code.