The Hardware Bottleneck AI Can’t Fix

The Hardware Bottleneck AI Can’t Fix

Author: Software Engineering Daily June 2, 2026 Duration: 52:47

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 CTO 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.

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

The post The Hardware Bottleneck AI Can’t Fix appeared first on Software Engineering Daily.


Dive deep into the conversations shaping the future of artificial intelligence with the Machine Learning Archives-Software Engineering Daily. This curated collection pulls from the broader Software Engineering Daily library, focusing entirely on the intricate world of ML engineering. Each episode features a detailed, technical interview with engineers, researchers, and architects who are building the systems behind today's most advanced AI. You'll hear them break down complex topics like model deployment, data pipeline challenges, and the practical trade-offs involved in taking research from a notebook into production. The discussions are grounded in real-world implementation, moving beyond theoretical concepts to explore the tools, failures, and successes that define the field. For developers and technical leaders looking to understand the nuts and bolts of applied machine learning, this podcast offers a valuable archive of knowledge. It's a direct line to the practitioners who are solving hard problems every day, providing insights you can apply to your own work. Tune in to gain a clearer perspective on how machine learning is integrated into modern software, one detailed conversation at a time.
Author: Language: en-us Episodes: 50

Software Engineering Daily
Podcast Episodes
Scaling Agent Workloads at Vercel [not-audio_url] [/not-audio_url]

Duration: 51:25
Most AI agent setups today are built around a single session, where one user interacts with one agent at a time. However, that model breaks down when an agent has to serve a business, where thousands of requests can arri…
Inside Google’s Database Infrastructure for the AI Era [not-audio_url] [/not-audio_url]

Duration: 1:18:26
Historically, databases were responsible for storing data and returning exact results in response to queries. However, AI is now bending that contract in a new direction. Applications increasingly expect structured and u…
A Rust Framework to Simplify Distributed Systems [not-audio_url] [/not-audio_url]

Duration: 50:31
A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message…
Moving Beyond RAG with Precomputed Context [not-audio_url] [/not-audio_url]

Duration: 55:48
Retrieval has become one of the central problems in building useful AI systems. The standard approach to grounding a model in one’s own data has been retrieval augmented generation, or RAG, where an agent searches a vect…
The Death of Online Anonymity [not-audio_url] [/not-audio_url]

Duration: 52:42
Age verification is reshaping how people access the internet. An ever-growing patchwork of laws can now require government IDs, facial age estimation, or behavioral inference before you can enter digital spaces. Discord,…
TypeScript 7 and What Comes Next [not-audio_url] [/not-audio_url]

Duration: 57:15
TypeScript is a programming language that builds on JavaScript by adding a system of types. Those types let developers describe the shape of their data and catch mistakes before code ever runs, while also powering the au…
The Gap Between AI Spending and AI Value [not-audio_url] [/not-audio_url]

Duration: 54:42
It is widely reported that a gap has emerged between enterprise spending on AI and the durable value captured from that spend. Individual employees have enthusiastically adopted coding assistants and chatbots, yet those…
AI and the New Global Security Landscape [not-audio_url] [/not-audio_url]

Duration: 1:12:32
The conversation about AI often focuses on software, automation, and the race between attackers and defenders in code. However, some of the most consequential risks lie further afield, in domains where a mistake is measu…
How LLMs Are Reshaping Recommendation Systems [not-audio_url] [/not-audio_url]

Duration: 47:51
News feeds and recommendation systems have long relied on deep learning architectures that score each candidate item independently. As LLMs have matured, they have opened up a fundamentally different approach, where a sy…