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title: "DO's and DOnt's with Vibe Coding" date: 2024-01-31

DO's and DOnt's with Vibe Coding

Summary notes of https://www.infoworld.com/article/4029093/9-habits-of-the-highly-ineffective-vibe-coder.html

  • Do's Do experiment with different models. Different LLMs have varying strengths and weaknesses, and you might need to try a few to find the right one for your specific coding problem.

  • Do treat the AI as a search tool. LLMs excel at finding and recalling information from their vast training data, such as obscure documentation or code snippets.

  • Do use the AI for simple, repetitive tasks. The article suggests AI can be helpful for basic programming chores.

  • Don'ts Don't trust the LLM completely. The article warns that LLMs can provide incorrect information and even "hallucinate" non-existent code or URLs.

  • Don't treat the LLM like a "dumpster." Avoid dumping large blocks of code on the AI, as this can be inefficient, costly, and even confuse the model.

  • Don't assume all models are the same. Each LLM has a unique internal structure, parameter count, and training data, which can significantly affect its performance.

  • Don't ignore the costs. AI tools charge by the token, and repetitive requests or large inputs can lead to surprisingly high costs.

  • Don't hand over full control. The article highlights the risk of trusting an LLM with critical tasks, as their inherent randomness can lead to unpredictable and destructive outcomes.

  • Don't expect the AI to "think" like a human. LLMs are clever mimics and excellent at information retrieval, but they are not always good at deep synthesis or providing novel insights.

  • Don't create inconsistent code. The randomness in LLM output can lead to a "patchwork quilt" of different coding styles, making the codebase messy and hard to maintain.