Time will tell, if this PoV is valid. I can tell you that a flashy, sexy demo, is not the same thing as shipping code.
A number of comments state that the quality of the output is fairly sparse, and amateurish, but this was also a very fast, thirty-minute demo of a marketing workflow, subjected to basic AI tools.
This article was the equivalent of those "Write an app in two hours" seminar/bootcamps.
Valid, but also constrained by the need to teach, and to get done within a certain amount of time. Very strict guardrails, and keep your hands inside the car at all times.
I have taken many, many of these courses, and have given a few. I'm quite aware of the difference between what we produce in a class, and what I'd hand to a customer.
What I think we'll be seeing, quite soon, is "one-person shops," acting as studios/agencies that will take on jobs normally done by large shops.
Like bootcamp babes that go out, thinking that they can now deliver a full-fat app to customers, many will fail.
But some will succeed. Lots of smart, hungry people, out there.
We'll look at what can be done with these tools (which, I should add, are still very much in their infancy. You ain't seen nuthin', yet). I don't think they'll be able to write the deliverables, yet, but that's OK. I think we may be able to leverage them to make those deliverables much more polished and robust.
I mean if the work could get done without ChatGPT then it's not getting done with ChatGPT any magnitude faster but it may help reduce the intervallic brain farts by being able to ask more than stack overflow has db results for
Go create a “system” with GPT. You’re going to see a ton of, “I’m sorry, you’re right, the SQL statement is referencing a column that doesn’t exist.” Etc…
Right now, it’s amazing for getting some boilerplate very quickly (so is create-react-app, etc).
It’s bad at context as the problem grows and very bad at subtle nuances.
Working with GPT today is like having a super fast and somewhat sloppy developer sitting next to you.
“Shipping” anything it creates means a LOT of review to make sure no false assumptions are present.
I have been “writing code” with it nonstop for weeks now.
Yes, it’s incredible, but it also has serious limitations (at least for now).
I wonder if there is a way to get chatgpt to check its own work. It has been useful as a method to find new literature for science, but the occasional completely made up references can be frustrating.
> Go create a “system” with GPT. You’re going to see a ton of, “I’m sorry, you’re right, the SQL statement is referencing a column that doesn’t exist.” Etc…
So, you don’t mean “create a ‘system’”, you mean use the UI to talk with ChatGPT about creating a system, rather than using the API and connecting it to tools so it can build the system, verify its behavior, and get feedback that way rather than through conversation with a human user?
I don’t see a difference regarding the work required. If the results are coming from a chat interface or an API, the same problems exist.
There aren’t any tools that I know of that can validate that GPT has correctly interpreted the prompt without any problems related to subtle (or overt) misunderstandings.
This being the case, there’s a lot of back and forth and careful validation necessary before anything ships.
that was actually my point; it's not like you'd ask your CEO for permission to do work that was supplemented with StackOverflow; so just...do the thing that needs to get done, using the sources required to get'r'done
Some people have made a career out of being good at reading, debugging, and fixing complex incoherent code that was written by other people. I imagine those will thrive in the near future.
I suspect that AI will become fairly good at bug-testing and fixing.
I would not be surprised to see AI testing and diagnostics, integrated into IDEs.
For example, UI testing. Right now, it's next to worthless, as it's basically scripting and screengrab analysis.
An AI tester can do a much better job of simulating a user, and analyzing the behavior of the app. Of course, it will be a real skill to set up the boundaries and heuristics for the testing, but it could be very cool.
I suspect that AI will also find a place in security; both in hardening and red-team testing, and in blackhat probing.
Time will tell, if this PoV is valid. I can tell you that a flashy, sexy demo, is not the same thing as shipping code.
A number of comments state that the quality of the output is fairly sparse, and amateurish, but this was also a very fast, thirty-minute demo of a marketing workflow, subjected to basic AI tools.
This article was the equivalent of those "Write an app in two hours" seminar/bootcamps.
Valid, but also constrained by the need to teach, and to get done within a certain amount of time. Very strict guardrails, and keep your hands inside the car at all times.
I have taken many, many of these courses, and have given a few. I'm quite aware of the difference between what we produce in a class, and what I'd hand to a customer.
What I think we'll be seeing, quite soon, is "one-person shops," acting as studios/agencies that will take on jobs normally done by large shops.
Like bootcamp babes that go out, thinking that they can now deliver a full-fat app to customers, many will fail.
But some will succeed. Lots of smart, hungry people, out there.
We'll look at what can be done with these tools (which, I should add, are still very much in their infancy. You ain't seen nuthin', yet). I don't think they'll be able to write the deliverables, yet, but that's OK. I think we may be able to leverage them to make those deliverables much more polished and robust.