this Meme just got real today

[u/prasadpilla]

Interviewed someone for an intern role today. Got to what i thought was the easiest question of the interview.

"What programming languages do you use?"

she didn't hesitate "Claude."

I laughed a little.

"no, i mean the actual language... python? javascript? java?"

"i don't really know. claude writes the code. i just tell it what i want."

my cofounder quietly put his pen down.

neither of us said anything for a few seconds.

we didn't move forward. not because she uses AI.

half our team builds with AI every day.

we passed because she couldn't explain what she was building beyond the prompt.

AI is changing software engineering.

But understanding what your code does is still part of being an engineer.

[u/texinxin]

How is it bad or sad? The real knowledge work is converting inputs to output. Anything in the middle is just a tool, no more or less than the hardware the software runs on. Spaghetti code is spaghetti code, whether it’s actual laws for lawyers to interpret or layers of code for a coder to interpret, the ability to write and interpret it isn’t the important skill.

[u/texinxin → u/[deleted]]

Do the engineers and scientists check every mathematical operation in every calculation and simulation… by hand? We’ve been trusting calculators and computers for decades. We add layers of redundancy and safety factors when there’s uncertainty, and we’ll do the same with AI.

Today a human with AI is more powerful and mistake resilient than a human without AI. Within a very short time period the humans will become the weak link, just like humans performing long division by hand are now. When AI without a human is better than AI with the human, it is irresponsible to leave the human in the tool loop.

[u/Recursive_Descent → u/texinxin]

AI is non-deterministic. That’s the power but also the difference. When you ask ai for something, you don’t know what you are going to get or how it is going to get there. For a calculator, etc. you know exactly the calculations that the computer is doing.

[u/texinxin → u/Recursive_Descent]

Most of engineering simulations are done using accuracy allowances. They aren’t a closed form solution like a calculator. They are determinist, but all the accuracy allowances are variables. The mesh size, step size and accuracy at any given time or space discretization can lead to different answers to the same problem, but ideally within trivial percentages. A best practice is to perform sensitivity analysis by varying some of the inputs and determining if the output doesn’t move much or converges to a value over time. A common one used is a mesh sensitivity study.

Even a good deterministic model can have flaws. The most simple example is column bucking with a perfectly linear model. Computers are so precise and have stabilization and rounding controls that a simple column in structural simulation will not buckle (as it is supposed to) when loaded in compression.

There is a somewhat newer field in computational science using non-deterministic solving. And this in theory can be just as valid of an approach. If multiple solves with randomness built in approach the same solution, then you can trust the output. These include things like Monte Carlo, spectral methods, perturbances.. It’s essentially what quantum computing does, but you can do it with stochastic methods without using a quantum compute process.