The podcast introduces a series of talks about evals, emphasizing their importance in agent development. It highlights a survey indicating that quality is the primary obstacle to deploying agents in production and introduces eval-driven development as a solution. The discussion covers three types of evals: offline, online, and in-the-loop, detailing their characteristics and benefits. It also discusses the two main components of evals: data and evaluators, and how LangSmith supports building datasets and running evaluations. The podcast also introduces open-source evaluators and tools for chat simulations, and it touches on the complexities of using LLMs as judges, including upcoming features in private preview to assist with this. The speaker emphasizes that evals are a continuous process, not a one-time task, and should be integrated throughout the agent lifecycle.
