Why would a game development pedigree correlate with rejecting AI? As Carmack said:
> AI tools will allow the best to reach even greater heights, while enabling smaller teams to accomplish more, and bring in some completely new creator demographics.
Carmack isn't exactly a neutral observer here, his main gig since quitting VR has been as the founder of a VC-backed AI startup. He has a clear financial interest in joining the chorus of AI boosters.
A less cynical interpretation of his actions would be that he's never shown to be motivated by money and is working on technology that interests him and that he can make an important contribution to
I don't use AI for the sake of it, I use it where and when it is useful. For example:
1. advanced autocomplete -- if you have or paste the structure of a JSON or other format, or a class fields, it is good at autocompleting things like serialization, case statements, or other repetitive/boilerplate code;
2. questions -- it can often be difficult to find an answer on Google/etc. (esp. if you don't know exactly what you are looking for, or if Google decides to ignore a key term such as the programming language), but can be better via an AI.
Like all tools, you need to read, check, and verify its output.
Personally I find this workflow is jarring. I get into flow typing code and then the AI autocompletes the next four lines on a tab input. Now my flow is screeching to a halt because I have to switch from flow mode to review mode to make sure it actually autocompleted what I wanted
Text editors/IDEs have simple autocomplete and the ability to do some expansion, e.g. a for loop with placeholders to fill in. Those work and are still useful.
JetBrains also has local line-based LLM models for various languages.
With the LLM-based autocomplete it a) generally autocompletes more code at once, and b) will often pick up on patterns in the existing code. E.g. if you have a similar method, list of print/string buffer write statements, or other repetitive code in the file it will often use that as a model for the generated code.
The JetBrains local autocomplete is hilarious but occasionally useful. I find it really hit and miss in terms of when it will decide to autocomplete and whether it will exhastively complete all elements, miss some out or get itself into a loop over several.
Won’t you get much better results trying to maximize utilization of some sort of LLM? For many people, you’d get faster and better results trying to optimize for LLMs than for any standard word processor or music composition tool.
Speaking for myself (who can program and all that), AI solves some of the tedium in my day job (building UI components). Most of that work nowadays is boilerplate.
But at the moment it's also helping me solve more complex issues with building applications - it's JS, so you can imagine how complex it can be.
I yearn for a simpler workflow to be honest, I don't want to rely on SO or LLMs to solve build issues. I want to work in Go but there's only a handful of companies using it in my country, plus my CV basically says I mainly did front-end in the past ~15 years.
> AI tools will allow the best to reach even greater heights, while enabling smaller teams to accomplish more, and bring in some completely new creator demographics.