This is broadly accurate, but if anyone feels like freaking out and quickly needs an antidote to the "high" class of sociopath grifters, perhaps could find some solitude in Wim Wenders' Perfect Days for a few hours.

While I mostly agree with the grim conclusion, I think there's an important aspect ignored that in every domain the very first and very best brands could leverage as good design and purpose: art and fun.

Remember winamp skins?

"The purpose of art is to impart the sensation of things as they are perceived and not as they are known. The technique of art is to make objects 'unfamiliar', to make forms difficult, to increase the difficulty and length of perception because the process of perception is an aesthetic end in itself and must be prolonged." - Shklovsky on defamiliarization

What pg is really writing about is enshittification, consumerism.

ppl are so sensitive. it's not impolite to be direct. why would you be wasting each other's time by "dear, sincerely etc" every single time.

y ask q u dunno answer 2?

To be fair, most questions are asked because the querent does not know the answer.

But [that's not what happened here.](https://en.wikipedia.org/wiki/Rhetorical_question)

Honestly this is the best way to learn about inverse problems and it's what made convolution click for me a few years ago.

:(){ :|:& };:

sub-agents that access (and manipulate) the SAME context (a file system or variables in the REPL)

File system access is a must tho, that's where half the power of coding agents come from: efficiently managing context files.

this makes sense, we should support a model where the code snippets can all be stored on the filesystem rather than in the context window from the MCP response

I 100% agree in the importance of the data model, and the examples show that it often makes more sense to start from the user's perspective of it rather than your db schema.

Interestingly AI Agents are all about disrupting the hard bounds of existing data and interaction models and it turns out the lowest common denominator is often the winner. Eg.: file system > database, grep > embeddings, markdown > pdf, generative ui > portals, computer use > api-s etc.

There simply is no need for all that abstraction / interface / infrastructure to eg. answer questions about documents or to keep track of todo lists, workflows or sending messages etc. when you have glue that can translate between the data models.

this would be useful outside of coding. could you release a benchmark so we can have more models tuned for this?

I would