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Why We're Betting on Homegrown Engineers

AI and robotics are driving the biggest wave of electrical engineering demand in a generation. Meeting it starts with more people actually finishing their first build.

679,500 open US engineering positions vs. ~141,000 new engineering grads a year Source: Engineering Inc. / ACEC

AI and robotics are creating unprecedented demand

This isn't a shrinking field looking for a rescue — it's a field being pulled forward faster than the pipeline can staff it. The US Bureau of Labor Statistics projects roughly 17,500 additional electrical and electronics engineering jobs through 2033 tied directly to data center expansion alone. AI data center electricity demand could reach 106 gigawatts by 2035 — a 36% jump from projections made just seven months earlier — and every watt of that has to be designed, wired, and maintained by someone.

AI data center power demand: up to 106 GW by 2035 A 36% increase over estimates from just seven months prior. Source: IEEE Spectrum

Robotics is compounding the same curve. "Physical AI" — humanoid robots and autonomous systems — is moving from pilot projects to core industrial infrastructure, not staying a demo-day novelty. Electrical engineers with AI/ML chip-design skills already earn roughly 20% more than peers without them, and the CHIPS and Science Act has driven over $400 billion in new domestic fab investment. The World Economic Forum is now describing AI infrastructure itself as critical infrastructure — the same category as power grids and water systems. Electrical engineering has quietly become a matter of national competitiveness, not just a solid career choice.

The gap isn't where you'd expect

The instinct is to assume students still prefer software to hardware. That's no longer even true. Computer science enrollment just posted its steepest single-year drop of any field of study — down 11.2%, with graduate CS enrollment down 14% — as AI systems get visibly better at writing and debugging code on their own. Whether or not that fear turns out to be fully justified, the perception that AI has already automated the entry-level coding job is real, and it's pushing students toward fields that feel harder to automate — mechanical and electrical engineering among them.

That's not a coincidence. Today's AI is dramatically better at manipulating bits than atoms: it can write, refactor, and debug code because code is text, and text is exactly what these models were built to produce. Assembling a physical circuit is a different kind of problem — someone still has to seat the part, solder the joint, and figure out why the voltage on the bench doesn't match the simulation. That gap between digital and physical work won't stay this wide forever, but it's wide today, and it's a real part of why electrical engineering is getting more durable, not less, exactly as AI reshapes software work. What's still missing is a viable on-ramp into hardware specifically.

Software has an incredibly short feedback loop: open an editor, write a line, see it run. Electronics doesn't. Before a first-time builder ever gets to see an LED blink, they typically have to identify the right microcontroller, cross-reference a datasheet, figure out which resistor value won't let the magic smoke out, and track down five different parts across three supplier sites that may or may not be in stock. Most people don't fail at electronics. They quit during the research phase, before they ever pick up a soldering iron — right as the field needs them more than it has in decades.

The bottleneck isn't talent, and it isn't demand. It's everything that happens before the first solder joint.

What we're actually doing about it

EasyCircuit exists to remove that specific friction. You describe what you want to build in plain language; the copilot designs the circuit, explains the choices, and one-click sources every part from real suppliers into a single kit — no datasheet spelunking, no cross-referencing five supplier sites, no guessing whether a part will actually work with what you already have. Then it hands you a packed perfboard layout with real footprints, so what you ordered is exactly what you solder.

That's the entire bet: if the on-ramp is short enough, more people — students, weekend makers, career-changers — get past their first build instead of closing the laptop at 1am with a spreadsheet full of part numbers and nothing built. We're not claiming one tool staffs a data center buildout on its own. We're claiming the on-ramp is fixable, the demand is real and only growing, and that's the part of the pipeline we're building for.

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