How To Build AI Agents That Actually Work In Production ( EVALS 101)
AI Summary
In this video, the speaker discusses the concept of “evals” and their significance in building more reliable and functional AI agents. After returning from a week-long vacation in Greece, they share a pivot in their approach to agents, emphasizing that instead of viewing agentic workflows as a binary distinction, they should be considered a spectrum of capabilities, with flexibility being paramount. The video covers the importance of integrating various types of evaluations into workflows, including generic evals (like assertions and conditions) and specific evals tailored to use cases (like customer support or revenue operations). They argue that while agents may be perceived as unreliable, the key lies in enhancing output quality through effective evals. The discussion also touches on the differences between using binary pass/fail evaluations versus Likert scales, advocating for a structured approach to creating agents that can handle dynamic conversations and respond accurately without sacrificing reliability. The speaker concludes by encouraging viewers to subscribe for more insights and to reach out for assistance with automations in their businesses.