Noah Luttinger (NLW)

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Another approach to breaking out of the averageness and sameness of standard AI outputs we'll call the cliche burndown.

The idea here is to make the model expose and then replace the template it wants to use.

So for example, if you were writing some analytical essay, you might ask it to list the most 10 common cliches in terms of analogies or terms of phrase that you might find in an essay like that.

From there, you can ask it what would be better ways to communicate the same idea without falling trap into those cliches and then embed that logic in whatever output it has.

Basically, the thing to recognize here is that there is a lot of value in getting the AI to identify the patterns that it's building off of so that it can then more conscientiously avoid those patterns.

This is a surprisingly effective technique.

If you did nothing else on this list, except at the end of each first pass output, say what are the most common cliches this fell prey to, and how could you change it to avoid them, your output would instantly be significantly better than the generic LLM output.

Closely related to this is the idea of self-critique.

People, I think, are much too comfortable just using the first pass of whatever AI does.

The whole idea, though, of unbounded, unlimited, and basically cost-free intelligence is that you can rerun a prompt over and over and over again.