LLM Coding Guidelines, AI Progress Predictions, and How to be a Scorpion?
Hey there! đź‘‹ Just dropping my weekly collection of cool reads. Hope you enjoy these gems as much as I did!
Here’s how I use LLMs to help me write code (Simon Willison)
A useful set of guidelines on how to use LLMs to write code. The current UX of IDE assistants is still somewhat broken because it just offers too much flexibility via the need to provide adequate context (i.e., one line of code to multiple files or the whole codebase) for a question and writing a good prompt (the result quality greatly varies depending on our prompts). So for now, we can document and follow a set of good guidelines around this. Here are some principles that I noted:
- Set clear, precise function signatures and requirements as context.
- Test and verify all generated code before using it.
- Treat conversations as iterative - refine results with follow-up requests.
- Provide existing code examples as context when available.
- Start with simple implementations then build complexity incrementally.
- Use LLMs that can run code for you in a sandbox.
- Ask for options when exploring potential approaches.
- Start new conversations when context becomes unhelpful.
- Request tests for any generated code.
- Be ready to take over when LLMs reach their limitations.
- Use LLMs to understand existing codebases by asking questions.
My Thoughts on the Future of “AI” (Nicholas Carlini)
Tries to argue both sides on the “future rate of AI progress” debate. I agree that prediction is difficult (If you want to know for sure, try to either place bets or simply logging and keep track of your predictions). It is wise to have wide margins of error around the expected progress in the next few years and keep an eye on prediction market outlooks.
Does A Software Engineer Have Scorpion Nature? (Ludic)
This article, or its associated talk, may take you into a rabbit hole well worth it! What I got from it is an awareness of how much “human dealings” exist in everything we do and experience. And if you are a technical person who just want to code, you may end up doing just that, and losing a lot. Humanities, communication, psychology, game theory, and economics ought to be studied and practiced in the real world.