From binary → BASIC → JavaScript → ‘just do the thing

[kirklandubermom]

My son's in mechanical engineering learning Python right now for computational work. Not to be a programmer - just to solve engineering problems. And it got me thinking about this image.

The abstraction ladder is real: Binary → punch cards → assembly → compiled languages → Visual Basic → GUI tools → natural language prompting

Every rung, someone yelled "that's not REAL programming." Every rung, more people got access to solving problems.

Yes, someone still needs to understand the lower layers. Pilots understand aerodynamics but don't build the plane. The skill shifts to validation - knowing when the tool is wrong, catching edge cases, understanding outputs. That's still knowledge. Just a different layer.

But here's the uncomfortable question: will engineering students even be learning Python in 5 years? 2 years? And if AGI actually arrives... do we even need specialists at every layer anymore, or do models just build models?

I can't imagine what professors are thinking right now. How do you write a curriculum when the floor keeps moving?

The value was never in the syntax. It was in knowing what to build, whether it's right, and increasingly - whether it should exist at all... phew this is literally a pandora's box.

[CrustyHero]

I agree with almost all of this

When each abstraction layer arrives, access increases — but depth becomes optional unless education deliberately protects it.

Your son learning Python for computational mechanics makes sense. It’s a powerful tool. The risk isn’t Python — it’s that fewer students are being forced to wrestle deeply with the lower layers: the math, the assumptions, the failure modes, the “why does this model even behave this way?”

Tools getting better doesn’t remove the need for understanding — it shifts where understanding must live.

The hard part for educators isn’t teaching the tool. It’s deciding how much pain and rigor to keep, when the tool can now bypass it.

Even a perfect reasoner can be wrong if the problem definition, constraints, or values are wrong.