Building AI Agents by Removing Features

The goal is not to do less. It is to give agents the flexibility to handle more of the work customers actually need.Henry Hopcroft, Chief Product Officer at Gradial, joins The Tech Trek to discuss how building AI products is changing traditional approaches to product development, engineering, and customer delivery.Henry explains why his team has moved away from building individual agent features toward a smaller set of core capabilities. He also shares how Gradial tests agents against difficult enterprise environments, uses forward deployed engineers to learn directly from customers, and approaches product planning when AI capabilities are improving so quickly.What You'll LearnWhy adding more features can limit an AI agent's flexibility.How real customer failures shape Gradial's agent evaluations.Why forward deployed engineers play a central role in product development.How coding agents are bringing product and engineering roles closer together.Episode Highlights03:59 Why Gradial started deleting agent features.07:31 Why traditional software testing falls short for enterprise AI agents.08:35 Building a nightmare marketing stack to test agents.12:03 How forward deployed engineers improve the core product.15:56 Why great engineers increasingly need product judgment.21:55 Why long term roadmaps are becoming harder for AI companies.A Moment Worth Pulling Out"Features can be something of an anti-pattern, I think, for agentic software."Follow The Tech Trek for more conversations about AI, engineering, product strategy, and building technology companies.