Even if ChatGPT gets far in advance of the way it is now in terms of writing code, at the very least you’re still going to need people to go over the code as a redundancy. Who is going to trust an AI so much that they will be willing to risk it making coding errors? I think that the job of at the very least understanding how code works will be safe for a very long time, and I don’t think ChatGPT will get that advanced for a very long time either, if ever.
There’s more to it than that, even. It takes a developer’s level of knowledge to even begin to tell ChatGPT to make something sensible.
Sit an MBA down in front of a ChatGPT window and tell them to make an application. The application has to save state, it has to use the company’s OAuth login system, it has to store data in a PostgreSQL database, and it has to have granular, roles-based access control.
Then watch the MBA struggle because they don’t understand that…
- Saving state is going to vary depending on the front-end. Are we writing a browser application, a desktop application, or a mobile application? The MBA doesn’t know and doesn’t understand what to ask ChatGPT to do.
- OAuth is a service running separately to the application, and requires integration steps that the MBA doesn’t know how to do, or ask ChatGPT to do. Even if they figure out what OAuth is, ChatGPT isn’t trained on their particular corporate flavor for integration.
- They’re actually writing two different applications, a front-end and a back-end. The back-end is going to handle communication with PostgreSQL services. The MBA has no idea what any of that means, let alone know how to ask ChatGPT to produce the right code for separate front-end and back-end features.
- RBAC is also probably a separate service, requiring separate integration steps. Neither the MBA nor ChatGPT will have any idea what those integration steps are.
The level of knowledge and detail required to make ChatGPT produce something useful on a large scale is beyond an MBA’s skillset. They literally don’t know what they don’t know.
I use an LLM in my job now, and it’s helpful. I can tell it to produce snippets of code for a specific purpose that I know how to describe accurately, and it’ll do it. Saves me time having to do it manually.
But if my company ever decided it didn’t need developers anymore because ChatGPT can do it all, it would collapse inside six months, and everything would be broken due to bad pull requests from non-developers who don’t know how badly they’re fucking up. They’d have to rehire me… And I’d be asking for a lot more money to clean up after the poor MBA who’d been stuck trying to do my job.
Who is going to trust an AI so much that they won’t risk it making coding errors?
Sadly, too many
I don’t believe it. If it’s good enough then they will ship and make money, and those who put people on it will be so slow that they will be just outperformed by those who don’t.
That’s a fuckin bleak outcome for a lot of people if the job transition goes from \ to \
That’s like being an artist and being told your job now is simply to fix the shitty hands Midjourney draws. And your job will only last as long as that remains a problem.
It isn’t surprising that this is the way we conceptualize the potential impact of AI, but it’s frustrating to see it tossed around as if AI disruption is a forgone conclusion.
AI will start re-defining the problems that code is written to solve long before we get anywhere close to GPT models replacing human workers, and that’s a big enough problem by itself.
It used to be that before code could even be employed to solve a problem, it had to be understood procedurally. That’s increasingly not the case, given that ML is routinely employed to decode things that were previously thought to be too chaotic to be understood, like brain waves and image pixel data. I don’t know why we’re so sure of ourselves that machine learning is just a gimmick and poses no real threat, just because anthropomorphizing it seems silly.
