dmpyatyi

just a comment to support post :) Incredible work!!!

That's actually really cool! Didn't know that figma had use this 0.0

Last Augusts paper about AI-Agents buying stuff online.

It's seems interesting in the context of OpenClaw and rising popularity of agents itself.

Most interesting topics from article:

- Agents ignore most products and pile onto 1-2 "modal" picks

- Sponsored tags hurt selection. Agents penalize ads.

- Position bias flips direction between model versions

- Simple description rewrites moved market share +8–15 p.p.

Last one is the most interesting, i'm thinking that AI-custdevs era is near.

Be prepared - agenprobe.sarm.solutions

bruh

But new models are popping up every few months ->> means they trained every couple months.

I don't know if there a correlation between what LLM would choose now and how you product should look to most likely be in LLM data set.

In that YC video i mentioned in post body they discuss tool called ReSend - something like an email gateway for receiving/sending mails. What's interesting - there are a lot of tools like that, but LLM's would every time choose shiny new resend.

Seems like there are something more than just being in the internet for a long time :)

*Clean parameter names, sensible defaults, clear required vs optional. It's basically UX design for machines rather than humans.*

But it's the same points you should follow when designing a human readable docs(as zahlman said above). Isn't it?

That's actually interesting, thanks!

I wrote this post because of exactly those corner cases. If I'm building something agents would use - how do i understand which tool they'd actually choose?

For example you building an API provider for image generation. There are thousands of them in the internet.

I wonder if there are a tool that basically would simulate choosing between your product/service and your competitors one.