The Only Question a “Pair” LLM Programmer Can Answer
Many have already begun to use Large Language Models (LLMs) and codegen tools in their daily workflow. And, as I’ve seen more and more developers turn to their chatbot first instead of another developer (🙋 myself included), this made me question: What place do these tools play in a pairing dynamic?
Using an LLM as an alternative to a pair programmer, at surface level doesn’t seem like a bad idea. It means an almost instantaneous turnaround on any question, with multiple ways to integrate these responses seamlessly into your workflow. It means never again having to worry if this next question will be my pair’s “last straw.”
However, pair programming isn’t just a solution to produce code quickly. A lot of the value comes from the shared knowledge of the codebase and domain between developers. Although LLMs continuously improve the amount of context they can process, there hasn’t been a replacement (yet) for a fellow programmer who knows more about your given problem than what you could craftily type up in a chatbot within a few minutes. So when do you reach for an LLM versus a pair programmer? For me, it boils down to a single question:
That’s it. For all different use cases when I find myself reaching for an LLM or codegen tool, it’s because I need some form of an example. It could be a test generated through Github Copilot, a SQL statement thought up through ChatGPT, or the citation of other people troubleshooting similar problems from Perplexity. All these tools can really do is bring you an example.
