It’s a lot less in my opinion, because you can just ask it a question rather than having to read and interpret things. Every programming tutorial in every language is going to waste my time explaining how loops and conditionals work, when all I want is how this language does them.
Right, but you can’t give it the variable names you’re using and have it fill them in, and if you want to do something inside that loop with
I can ask ChatGPT “Write me a loop in C# that will add the variable value_increase to the variable current_value and exit when current_value is equal to or greater than the variable limit_value, with all the variables being floats”
You won’t find that answer immediately on the Internet, and you’re more likely to make errors synthesizing the new syntax.
But you do you, I’ll keep using ChatGPT and looking like a miracle worker.
It’s not that writing loops does it, it’s that I can ask ChatGPT to hand me pre-assembled parts that I can snap together instead of typing them out with my squishy human fingers. And I can do it for pretty much any language without too many syntax errors.
I’m a senior software developer (Currently .NET backend with DevOps). Writing code is probably less than 10% of my work day. And in that 10% Visual Studio autocomplete does most of the typing. It’s frequently wrong, but it’s good enough plenty of the times.
Actually working on software consists of writing specifications, security concerns, architecture, talking management out of dumb decisions, having meetings with stakeholders or other companies, working on automatic deployments, writing unit and integration tests, refactoring, performance optimizations, database migrations, bugfixing, …
Green field writing new code is rare and that’s mainly what AI can do (80% correct, maybe). Most of real programming work happens on existing code.
I’m not saying AI will write entire applications, but it is really useful at writing small bits of code for a human being to assemble which can greatly improve productivity.
Though if we could get it to handle stakeholder meetings I’ll never use it for programming again.
It’s a lot less in my opinion, because you can just ask it a question rather than having to read and interpret things. Every programming tutorial in every language is going to waste my time explaining how loops and conditionals work, when all I want is how this language does them.
Seriously?
If I google for example:
The first result is https://www.w3schools.com/cs/cs_for_loop.php
In the time it took me to get to that ChatGPT would still be writing its reply.
Right, but you can’t give it the variable names you’re using and have it fill them in, and if you want to do something inside that loop with
I can ask ChatGPT “Write me a loop in C# that will add the variable value_increase to the variable current_value and exit when current_value is equal to or greater than the variable limit_value, with all the variables being floats”
You won’t find that answer immediately on the Internet, and you’re more likely to make errors synthesizing the new syntax.
But you do you, I’ll keep using ChatGPT and looking like a miracle worker.
If writing simple loops with ChatGPT makes you a miracle worker then you might have other problems than AI.
And even simple things break down when you ask it about using library functions (it likes to hallucinate heavily there).
It’s not that writing loops does it, it’s that I can ask ChatGPT to hand me pre-assembled parts that I can snap together instead of typing them out with my squishy human fingers. And I can do it for pretty much any language without too many syntax errors.
I’m a senior software developer (Currently .NET backend with DevOps). Writing code is probably less than 10% of my work day. And in that 10% Visual Studio autocomplete does most of the typing. It’s frequently wrong, but it’s good enough plenty of the times.
Actually working on software consists of writing specifications, security concerns, architecture, talking management out of dumb decisions, having meetings with stakeholders or other companies, working on automatic deployments, writing unit and integration tests, refactoring, performance optimizations, database migrations, bugfixing, …
Green field writing new code is rare and that’s mainly what AI can do (80% correct, maybe). Most of real programming work happens on existing code.
I’m not saying AI will write entire applications, but it is really useful at writing small bits of code for a human being to assemble which can greatly improve productivity.
Though if we could get it to handle stakeholder meetings I’ll never use it for programming again.