AI just wrote assembly code from plain English ➣ and it made me rethink what “building software” even means

I saw something wild this week.
Someone asked GitHub Copilot to “add 3 and 5.”
Instead of spitting out Python or C, it generated ARM64 assembly ➪ the native language of Apple’s M-series chips ➪ and verified that the result was 8.

If you’ve ever looked at assembly, you know how unforgiving it is.
One wrong register, one misplaced instruction, and it breaks.
Yet Copilot got it right.

That feels like more than “AI writing code.”
It’s AI starting to think like hardware.

I’m not a developer ➪ I write SaaS content for product teams ➪ but while working with founders lately, this shift hit me differently.
Most startups I’ve seen fail not because they can’t build, but because they can’t translate.

→ Users describe problems in plain language.
→ Founders interpret those into features.
→ Engineers implement what they understood.

And somewhere between those steps, clarity dies.

What if AI starts closing that gap?
If it can turn human intent into machine instructions, maybe it can help teams translate user language into product logic faster ➪ without layers of miscommunication.

That would change how we scope, test, and even write specs.
It might also redefine what a “technical founder” means.

Less syntax, more semantics.
Less “how to code,” more “what do we mean.”

Feels like a small moment ➪ but I think it points to something big.

Curious: if AI can reason at the hardware level, what parts of product building become more human as a result?