The Age of Agentic Engineering for Hardware - by Marco

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The Age of Agentic Engineering for Hardware<br>How the jobs of engineers working on physical products are changing

Marco<br>Jul 28, 2026

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The first time all businesses changed

When Marc Andreessen wrote in 2011 that software was “eating the world”, he foresaw a worldwide substitution: innovative companies that used software replacing incumbents in industry after industry.<br>He saw early signs that companies that were providers or early adopters of Silicon Valley-developed software would outperform their peers. In his analysis, he extrapolated this trend to the world, and in 2026, it is obvious he was right.<br>Today, the question is no longer whether software would affect all industries (it did), but how AI will shape them this time around.<br>So let’s take the same approach of looking at the early trends and extrapolating from there.<br>Starting with the low-hanging fruit

When ChatGPT came out in late 2022, it quickly became clear to its early adopters that this was more than a toy, but rather another technology that had the potential to touch many industries.<br>In early 2023, I predicted that by the end of 2024 most knowledge workers would have a digital assistant. That happened: By October 2024 every Google search result included an AI summary, and ChatGPT reached 300 million weekly active users. Today, that number is well beyond 900 million.<br>While chatbot-like use of AI is already profoundly affecting private lives and the day-to-day tasks of people in many white-collar jobs, it is just the tip of the iceberg of a more profound change that is currently underway — so far mainly visible in a single industry.<br>What is happening in software engineering?

While pretty much every business software tool nowadays ships with a chatbot, most of them are just gadgets. You type a question, the chatbot answers, you close it. Nothing changes in your project. You get nothing you couldn’t get from ChatGPT. When people share “magical” workflows on LinkedIn, they are usually a concatenation of hopping between tools or automatic repetitive tasks.<br>However, since December 2025, there is one industry that has shifted far more profoundly than the other areas: Software Engineering.

The Anthropic Economic Index (Feb 2025) shows coding extremely over-represented<br>So, what is changing in that industry that is not happening anywhere else?<br>Agents that have access to and can modify actual work context.

Let me explain:<br>It was already clear early on that context-awareness, speed and computational abilities would be necessary properties of any useful “co-pilot” for real-world engineering.<br>Concretely, this means that the AI does not “wake up dumb” or need re-explaining every time it starts but can quickly pick up from existing work and that it can do work that is meaningful in a real-world work context instead of relying on the human to insert their knowledge and copy-paste data.<br>The distinction is simple: does the AI act on your data inside your work environment (Agent), or does it just talk about it (AI Chat)? When agents work and use tools on the user’s behalf, they turn question-answering machines like ChatGPT into actual collaborators.<br>The first place this happened at scale was coding agents: released only in February 2025 as “Claude Code”, and since then transforming the software world as adoption has gone through the roof.

Anthropic’s year-over-year revenue growth (Feb 2025)<br>Today, these agents code entire features, review and ship them while humans are asleep.<br>Software engineers are still in charge of deciding what to build, but more and more of the actual execution is shifting from humans to machines. These are not minor changes to the way people in that industry work. It has gone well beyond reformulating emails or writing memos; it has changed the entire way every software engineer works on Earth in the past nine months.<br>Why has all of this almost exclusively been happening in a single industry?<br>Why was coding the first frontier?

I believe there are three main reasons why software development has been the first (and for now arguably only) industry that the big AI labs focused on:<br>•The people building the AI models and the tooling around them are software engineers themselves. It’s the domain they know best, so they can iterate quickly and build great products for themselves first.<br>•Some AI labs believe that if they make coding better, they gain a major competitive advantage, since they can then build better AI faster using those same tools. Strong incentive.<br>•As Andrej Karpathy noted, when the correctness of a task is easy and cheap to verify (which is exactly what automated tests and compilers do for code), it is easy to optimize an AI to perform well at that task.<br>That last point especially drives home why software engineering has been such an easy target. Code is the only engineering artifact that is natively machine-addressable and...