The Hardware Bottleneck AI Can’t Fix
Software engineering has developed powerful tools for observability, data management, and continuous testing, but hardware engineering has largely not kept pace. The feedback loops, tooling, and infrastructure that software engineers take for granted simply do not exist in most hardware programs. Nominal is a data platform built to help hardware organizations move at the same speed as software teams. It manages the hardware data supply chain end to end, from ingesting high-frequency sensor data off physical assets to enabling real-time control room monitoring, post-test analysis, and simulation correlation. Jason Hoch is the co-founder and CEO of Nominal, and he has a background spanning distributed data systems at Palantir and cloud infrastructure at Vercel. In this episode, Jason joins Kevin Ball to discuss why hardware engineering has lagged so far behind software in tooling and observability, the unique data challenges of working with high-frequency time series sensor data, how Nominal handles both real-time control room workflows and post-test analysis, why AI agents are transforming software development but have not yet made the same leap in hardware, and what it would take to close that gap. Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space. Please click here to see the transcript of this episode. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post The Hardware Bottleneck AI Can’t Fix appeared first on Software Engineering Daily.