I'm curious about the best ways to leverage AI when coding to truly enhance my productivity. I've seen a lot of discussions that end up being pretty vague, with comments like "GPT-5 is better" or "Claude Code feels more intuitive," but I want more than just subjective opinions. I've tried out various models myself and honestly, I don't see significant differences between them.
I usually assign specific tasks with detailed prompts telling the model what to do, which files to work with, and sometimes even how to do it, and I often get decent results. However, there are moments when the standard models fall short, and I switch to the higher-end options.
I genuinely want to maximize the utility of AI in coding, yet I feel like I might be missing something important. Perhaps people have techniques or tools I'm not aware of, or maybe I'm just using these AI models incorrectly. So, how does everyone else use AI in their coding processes to improve productivity?
5 Answers
Things change so quickly in tech. If you're getting good results with your current method, stick with it and keep experimenting with different models when needed. Even if someone claims there's a 'best' model today, that's bound to change soon anyway.
I usually have AI generate a docker-compose stub for me to edit later or ask for the best ways to achieve a specific function. But honestly, to maintain productivity in the long run, you really need to know your codebase well—just generating code without understanding can be a trap.
When I'm stuck, I like to chat with an LLM for guidance, and then I'll do my own research to verify things. After that, I dive into coding myself. Balancing AI help with my own coding is key for me.
I sometimes have AI post responses to questions on forums so I can stay focused on what I’m learning without getting sidetracked. It's a little unconventional, but it helps!
Honestly, I think you should try to do the hard work yourself when you're learning to program. Relying too much on AI tools can hinder your understanding of how to structure your code and debug it effectively. If you do use AI, keep it separate from your actual projects to get clearer, more useful feedback.
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