For whatever reason I've preferred, at least so far, Fable to 5.6. I've spent the time since Fable's return being very cautious about when and how I use it, whereas with 5.6 (especially given OpenAI's generous limit resets) I'm pretty liberal about using it for lots of things that in the long run I could do with a less capable model.
Psychologically, I think that approach has made me value the delicate, ephemeral creature that is Fable more than I otherwise might. I don't know if that was Anthropic's plan, but if it was it worked on me at least.
But there's a limit to how many times they can play this card. Eventually either Fable has to blow me away so much that it justifies the API spend (it hasn't yet), or I have to decide that I can't rely on it, and I develop an approach that leans on it less heavily.
I don't know when we hit the tipping point from scarcity increasing perceived value to uncertainty reducing real value, but it can't be that far away.
In general more eyes on a real product are good for the companies making it. There's still the same need as always to triage the input--the easier it is to demo a product, the farther the average demo user is from your ideal user or product vision.
But it's hard to hide things in a real product demo, and that's something companies should embrace! Learn early and often, rather than find out only at the end of a protracted sales process that the buyer and seller weren't on the same page.
I love Postgres, and I agree with the general sentiment. But I read the (growing) genre of "use Postgres for everything" articles and they imply a difficulty in running other software that I just don't see.
I'm thinking of Redis in particular. If you're using it as incredibly fast but not critical storage, it's trivial to set up and it ~never crashes or requires maintenance. It creates no headaches, and in exchange gives me a k/v store that I can thrash without worrying about performance (I know it's fast), downstream impact (am I slowing down critical-path SQL queries), etc. Especially in the age of LLMs, which I've found to be great at devops-type tasks, I feel slightly less compelled to simplify my stack.