Ask HN: What are your thoughts on ChatGPT as a professional?

I think it depends where you end up, but where I currently work we almost mandated that devs at least get familiar with how to use it, if not necessarily use it in everyday work. It's just too useful and valuable to omit.

What I've also found is it's incredibly useful for domain knowledge too. I've been working on a project around electrical grids, and when I had to go deep into how AC grid electrical engineering stuff, it was very very helpful. It's useful for business related stuff too.

At the end of the day, I think it's a powerful tool that shouldn't become a crutch, and any company saying otherwise is sabotaging themselves. But that's not to say they wouldn't be a good place to work for, companies sabotage themselves in all sorts of ways :)

I work in biotech and at my company, specifically our CEO, for over a decade has constantly asked all of us, "How are you leveraging AI in your job?". So much so that we used to joke about it. Well, when ChatGPT arrived, something happened. Everyone at the company (now about 5000 people) were already primed, looking for how they could finally answer "Yes" to our obsessive CEO. We have a deep roster of professional software engineers, and one dev in particular hacked out an internal site that leveraged the OpenAI API and deployed it company wide. Last count, a majority of the company uses it daily. What my team specifically has found is that building custom GPTs and working out detailed, two-way prompts, has allowed us (and specifically my part-time employee) to deliver detailed technical reports commensurate to an FTE. The key is to force the output to "show it's work" and to expect to review similar to how you would work with a first year graduate student. If you do the math, this puts the company above it's FTE cost in terms of per employee output. That's the real ticket right now. It's not inventing the next drug, but it sure as hell is making me more productive without causing burn-out. It works really well also at meeting minutes, a huge source of time-waste for project managers who should be doing high-thought work instead of menial tasks.

So to answer your question: become reliant on it. This is the future of white-collar work. Local instances are catching up to the big ones. It's only going to get better!

I guess you mean code-generating LLMs in general, not specifically ChatGPT.

For programmers I think they're valuable tools and productivity enhancers. Knowing how to use one effectively to boost your productivity is important.

The "[thing] will kill software engineering" narrative is one we hear every time something new boosts productivity by hiding abstractions - high level programming languages, IDEs, garbage collection, etc. The end result is never less programmers, it's more code. More stuff gets made that otherwise would not be. Same will be true for LLMs.

Typical use, I need to write a script or bit of code for a language I'm not super familiar with. Examples: write a bash script that tests this and that. Write a unit tests in python for this function. How can you do this idiomatically using the C++ stdlib.

Less common: code transformation. I have this json output and I want to turn it to a different format without bothering writing a script. I give chatgpt a few examples of the transformation, and have it done for the rest. I'll still have to fix it but it can save me a bit of the time.

And finally, when I stumble on an API I don't know anything about, I can get a better grasp by asking ChatGPT some questions about it.

Again, not life changing or even a huge productivity booster, but it helps. Also, it's good to know when ChatGPT isn't going to help and avoid losing time.

No stigma. If it helps, use it. Don't discard a useful tool but know its limits. You are not paid to carry around trivia to be used in a vacuum. You are paid to solve problems that sometimes involve programming.

It serves me well for micro-programming. So problems between a single line of code and a function. Here I can control for all its weirdness and hallucinations. As soon as I need to compose these elements I found it somewhere between neutral and a nuisance. High-level changes across a domain or further are impossible.

Understanding problems inside-out or from first principles has been vastly more helpful than blindly copying around libraries/SO answers/Copilot ideas.

That said, I have been in this industry for over a decade, am jaded and bitter and up to my armpits in Stockholm Syndrome, and have learned how to keep computers happy. Starting out I would have loved Copilot and it would have absolutely made a huge difference.