I'm rather surprised it took Meta this long in the wake of X introducing subscription plans quite long ago now.

Like the article mentioned, they already did fast-follow subscription when X did it with the Meta Verified subscription

"The api pricing for mimo-v2-pro and mimo-v2-omni remain unchanged" could we presume this means the discount isn't from hardware improvement or availability ?

There's also https://internetcomputer.org/

My opinion is that we're using the wrong paradigms for LLMs. We should be leaning more on declaratively specifying behaviour.

If there's any hope for reliability, auditability, predictability to be had it lies in contraining and LlMs grammar whilst delegating freeform behavior to a more passive substrate.

On a related note they opensourced an email client: https://github.com/cloudflare/agentic-inbox

For advice let me use my current product. https://fontofweb.com is essentially Pinterest for web design. It does semantic search against a database of UI screenshots and recordings.

The problem with products like this is that for search to be useful, you need, well... data. And when your data is crowdsourced, you need, well... a crowd. That was the chicken-and-egg situation I found myself in.

So the way I solved it was by painstakingly clipping and recording ~8500 websites myself.

But the great thing about that arduous process is that it forces you to put yourself in the shoes of your typical user. And really, the only way to make good products is to have a deep level of empathy for that user. In my case, that meant streamlining the data creation process itself, the act of pinning a screenshot or recording, because I had to do it over and over again. Making it easier for myself ended up making it better for everyone else too.

Of course, all that data-seeding effort goes to waste if search engines and potential users cannot discover it. So you have to go all in on SEO, especially sitemaps, and on programmatic socials where possible. This is especially true for a product like mine.

A lot of these marketplaces also have relatively homogenous data, which is actually useful, because it means you can present it through templates and publish pages at scale automatically.

Cool site, seems like a really useful tool!

Graphql introspection queries would be a really neat application for LLM calls

MCP server to give AI agents design taste - https://fontofweb.com/mcp

Agents can search for design inspiration from production websites using semantic search. Since this inspiration comes from live websites, their design tokens; colors, typography usage, layout data are also available.

This seems like it would have adversarial consequences. Wouldn't these list of tropes get longer over the years.

I've noticed a key quality signal with LLM coding is an LOC growth rate that tapers off or even turns negative.