When I was at Cal (requisite “Go Bears!” inserted here, no matter how terrible the football team may be now), there were two species of tech-focused students: CS majors and EECS majors. CS (computer science) majors learned how to program and think about computer systems. EECS (electrical engineering and computer science) majors learned all that stuff, but they went deeper, into the dark heart of chips and circuit boards and a bunch of fancy machine-level languages mere CS majors would only glimpse.
To give you an idea of the intellectual hierarchy, my roommate was an aspiring EECS major. His family had decreed that he would become a highly-paid engineer, and this was the obvious path. It was a sad day when his addiction to DoTA (an ’00s video game) forced him to downgrade his ambitions to being a lowly CS major — there was a hard conversation with his parents when it became clear his grades weren’t cutting it.
Can A Software Engineer Become an Embedded Systems Engineer?
The barrier between embedded systems engineers (programmers that work with physical devices) and software engineers (us slackers that build apps) was previously a firm one. Working in C, Assembly, or other arcane languages was difficult and required greater discipline than making web apps using whatever the hot framework of the day happened to be.
As a result, whenever a business problem involved creating a physical device, I threw up my hands: that wasn’t my specialty, and I wasn’t going to be able to afford the requisite embedded systems engineer.
You’re an Embedded Systems Engineer, Harry!
In 2026, I have a new thesis: just as AI is helping non-technical people write software, it can help software engineers become embedded systems engineers.
And boy can Claude help me prove that thesis! “Vibe coding” an ESP32 board quickly showed me that, nearly exclusively with natural language prompting, I could develop a PoC product. Like all things with AI, this is huge. We’re likely to see an explosion of physical device-oriented startups whose ideas have been freed by AI. Expect more solutions at lower price points in more niche markets.
But How Much of an Embedded Systems Engineer Are You?
What I still don’t know is how far Claude can take me from lowly software engineer to deep neck-beard systems engineer.
I often hear early stage founders questioning whether their “vibe coded” software product will scale beyond the proof-of-concept level. They talk of AI as an accelerator to their first dollar of revenue, but assume that VC money will still be required to get them beyond their first customers.
Standing On Top of the AI “Stool”
By reaching beyond my competencies as a software engineer, working with embedded systems has given me a deep empathy with these founders.
We’re all trying to get as far as possible with lean teams fueled by cheap tokens before we need to hire specialists. It doesn’t matter whether you’re building software, hardware, or even opening a new brick-and-mortar business: everyone wants to leverage AI to go faster and further for less.
If you’re on this same journey, reach out! I’m happy to share my experiences, both within my core competencies of software and infrastructure, and also in areas like embedded systems engineering where I’m standing on the AI stool. We’re all reaching higher than before — but sometimes that stool does feel a bit wobbly, and that’s when it’s nice to have a reassuring, steadying hand.