Moving fast in hardware: lessons from lab to $100M ARR

Fun read but a bit too much fluff? I was a design MechE for about a decade and I’m by no means as successful as the OP. But I have worked on a 5 person design team that had an annual net revenue of 30M and another job where I worked on 25M+ contract with just a team of 2, me and my mentor at the time. End of the day, hardware execution is hard and there’s a ton of product development cycle theories, you just need a culture with what I call good engineering discipline. Good communication, good documentation, and realistic milestones with accountability.

According to the draft Wikipedia article for this company that hasn't been published because it is not yet considered sufficiently noteworthy, this company has existed for 17 years, built their first production facility in 2023, and first delivered working units into real cars last March. That doesn't strike me as moving all that fast. It also says they acquired the Bose product they're shitting on in this article for doing things wrong.

If it works, it works, but I really wish companies and founders would just be honest about how and why they succeed when they do, instead of everything needing to be the constant projection of a desired image.

I think Clearmotion has a very interesting technology and product (ride stabilization), but let's paint a full picture here: the company was founded in 2009, took on $370 million in funding, and only recently landed large contracts (a $1 billion dollar deal in 2023 with Chinese auto manufacturer, Nio).

I'm sure they were in a constant struggle for survival and had to "move fast" to stay afloat, but their technology is more than a decade in the making.

Outsource the mature, insource the uncertain is very true. A lot of startups outsource precisely the part of the system they understand least, but that is oftentimes the worst possible decision.

Nice read but falls into a vast reductionist trap, a lot of survivorship bias dressed up as design philosophy or strategic bets. The context of decisions made decades ago != now, people were working under different constraints etc. Trying to frame the avionics example as the "subtractive" innovation is the most egregious, transistors were over 1000x times smaller, weight wasn't even a consideration.

I'm mostly curious how much of that revenue is actual ARR, which is to say contractually recurring. It is pretty dang rare for a hardware company to have nontrivial ARR.

Just when I think I cannot see more emdashes, there are more emdashes.

Optimizing for learning/iteration speed is a solid approach that applies just as much to software development.

Could anyone recommend the same for a software startup? (Lessons learned, mistakes to avoid etc)

Can someone in plain English please tell us what this company does? I just see one anecdote after another that’s scattered with feel-good whodathunkit babble. I was anticipating the airplane holes analogy, but maybe I got lucky and missed it.

Depends on how much funding you have, your target audience, target vertical, and how custom your hardware is, no? There can only be so many things you can cut and optimize.

The signature of claude is in the piece. “Same X, Same Y, Z later”.

Great piece but sometimes I wonder how much is human thought vs AI fluff.