Why you should vibe-code your AI safety research sprint project

Your research hours are limited. Don't spend them coding.

Intro

When I first asked an LLM to code me that annoying function or, worse, that whole experiment pipeline, I felt guilty and anxious as if I was cheating and getting away with it. I’m sure you’ve felt this way too.

It can be easy (especially if you are new to AI safety) to feel like you should avoid this, to feel like you should write all of the code in your project yourself, understanding each line and all the libraries that you use.

There is a time and a place for this, but a 30hr research sprint is not it.

If you are doing a research sprint, you should use LLMs / coding agents for all of your coding. Below I give you three reasons why.

You don’t have time to learn both engineering and research

The skill you should build in a research sprint is research taste: choosing what experiments to run, forming hypotheses worth testing, and updating your intuitions when the results surprise you. This only develops through many iterations and 30hrs is not a lot of time, especially if you spend hours coding experiments that could take minutes with AI. You should be very explicit about which skill you are trying to train, and optimise for that skill alone.

You might be thinking “but I need to be sure my code is actually implementing the experiments I intended” and you’re absolutely correct. However, this is entirely compatible with vibe coding your whole experiment pipeline. Just get the same model to provide you with a summary of the code and keep asking it questions until you are confident it is doing it right.

You’ll do more research and do more writing

If you spend less time coding, you will cover more ground and do better research. You can go deeper, ask that extra question, run that extra experiment, discover that extra awesome result. You’ll develop better intuitions about how AI models behave and which research directions are worth pushing.

You’ll also have more time for writing. Sharing your project is what lands you that next opportunity and where all the best feedback comes from. Nobody will be impressed by how “human written” your code is. They will be impressed by your clarity of thought and the depth of your research.

Coding with AI is a skill worth practicing

AI models are amazing at coding. With Claude Code, you can now build an app in a weekend and a whole machine learning experiment setup in minutes. And this won’t change. For the rest of your life, LLMs will be faster at coding than you, no matter how much you practice. The most productive AI safety researchers use AI for coding, and so should you.

If you want to learn how to use AI for coding, ask your favourite LLM! They’re very good at giving you tips and tricks on how to use them better.

Conclusion

Don’t feel guilty about using AI for your coding. Learn to operate fast while staying in control. Be explicit in the skills you want to develop, and be ruthless in pursuing them. So, which skills do you want to develop in this sprint?