Simon Willison’s Weblog

An underestimated challenge in making productive use of LLMs is that it can feel like cheating.

One trick I've found that helps is to make sure that I am putting in way more text than the LLM is spitting out .

This goes for code: I'll pipe in a previous project for it to modify, or ask it to combine two, or paste in my research notes.

It also goes for writing. I hardly ever publish material that was written by an LLM, but I feel least icky about content where I had an extensive voice conversation with the model and then asked it to turn that into notes.

I have a hunch that overcoming the feeling of guilt associated with using LLMs is one of the most important skills required to make effective use of them!

My gold standard for LLM usage remains this: would I be proud to stake my own credibility on the quality of the end result?

Related, this excellent advice from Laurie Voss:

Is what you're doing taking a large amount of text and asking the LLM to convert it into a smaller amount of text? Then it's probably going to be great at it. If you're asking it to convert into a roughly equal amount of text it will be so-so. If you're asking it to create more text than you gave it, forget about it.