Comment by claytongulick

I think the (currently) intangible skill that we need to develop is when and how the LLMs are appropriate to use. I'm not sure that's possible- I agree with the author's drug analogy.

I generally don't use it for code - I've been writing code for 30 years, so I'm pretty quick, and it's more productive when I look at total time for me to just write things myself.

But not always.

For example, I was recently writing some firmware in MicroPython and needed to implement Bluetooth to control the device.

It's been years since I've written python, since before asyncio. I'd never written MicroPython and didn't really know anything about Bluetooth or BLE.

The AI taught me about how to do it, taught me about how asyncio works (I'm deeply familiar with the model, just not in python), taught me what how Bluetooth works, what GATT characteristics are and gave me some example code that I then took and rewrote to fit my architecture.

I tried to do the normal "find a tutorial on the internet thing" first, but it's filled with worthless AI slop, ads and examples that are so trivial they're only clickbait. It's incredibly frustrating.

Meanwhile, the LLM was succinct, helpful and able to iteratively answer each question I had as learned and got deeper into it, with links to source references I could use to verify the information.

So, basically, a better search engine.

I've been writing code professionally since the 90s, and struggled through learning new things more times than I can count. This was by far the best experience I've had. It was where LLMs really shine.

But, that being said, at the end of the day I wrote the actual code myself and structured it to fit in with the rest of the architecture for the firmware.

I understood everything and when I had to pass it off to another engineer, I was able to describe everything, how it works, and why it's structured the way it is.