AI Agents Fail for 2 Reasons. Crowdsourcing Solved Both. | Julia Dalton, SVP Product (Capacity)

Long before “AI Agent” was the buzzword in every product discussion, Julia Dalton was already deep into solving the problems of coordinating thousands of worker agents, creating clear instruction prompts, and evaluating output quality. Julia is SVP of Product at the AI-support automation platform, Capacity. Previously, she helped scale workflow orchestration at OneSpace, formerly known as Crowdsource, where thousands of freelancers executed microtasks for major retailers. As it turns out, managing humans at scale and managing AI agents have a lot more in common than most people realize. In this episode, Julia shares: The two failure modes that kill every AI agent before the model ever runs Why running a crowdsourced work platform gave her incredible insights into building effective agentic AI products How Julia and her team built an AI system to triage and prioritize product feedback, automating low-complexity builds and helping make better decisions on high-stakes tradeoffs Links LinkedIn: https://www.linkedin.com/in/juliadalton/ Capacity: https://capacity.com/ Chapters 00:00 Intro 00:52 Julia's startup roots at OneSpace 02:00 Transitioning from the human API to AI agents 02:47 Microtasking workflow chains 06:54 Routing rules and AI orchestration 11:55 Validating prompts with simulations 15:08 Recursive prompting in practice 17:46 Data and knowledge orchestration 20:57 PRP triage app for product requests 26:56 Conclusion Follow LaunchPod on YouTube We have a new YouTube page! Watch full episodes of our interviews with PM leaders and subscribe! What does LogRocket do? LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com.