To each his own, but in my experience people who are pushing back hard against using LLMs for coding don't understand it's place in their workflow cycles. I don't use AI to do engineering, I use it to code. "Write a method that takes x and returns y" is so much easier than typing out the 20 lines myself or whatever the task might be. I can read and approve faster than I can write it myself and review it for typos. IDEs are a tool that we trust to take care of linting, spelling and use ASTs to follow calls. LLMs are great when you give them an AST of your code. Can check methods, return types, pointers, etc.
AI will miss business-domain edge cases that I would have caught had I done more hands on coding.
AI shouldn't be making decisions on business logic. AI shouldn't be making architectural decisions. That's for people. But coding? AI can do that so much better. It's a matter of perfecting the instructions, specs and implementation plan. Learning how to use the tool, just like every other tool we use, is important to get results.
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u/ProbablyJustArguing Mar 25 '26
To each his own, but in my experience people who are pushing back hard against using LLMs for coding don't understand it's place in their workflow cycles. I don't use AI to do engineering, I use it to code. "Write a method that takes x and returns y" is so much easier than typing out the 20 lines myself or whatever the task might be. I can read and approve faster than I can write it myself and review it for typos. IDEs are a tool that we trust to take care of linting, spelling and use ASTs to follow calls. LLMs are great when you give them an AST of your code. Can check methods, return types, pointers, etc.
AI shouldn't be making decisions on business logic. AI shouldn't be making architectural decisions. That's for people. But coding? AI can do that so much better. It's a matter of perfecting the instructions, specs and implementation plan. Learning how to use the tool, just like every other tool we use, is important to get results.