Add reinforcement learning to figure out which skills are actually useful, and you're really cooking.

DSPy with GEPA should work nicely, yeah. Haven't tried yet but I'll add it to my list. I think a way to share within teams is also low-hanging fruit in this space (outside of just adding them to the repo). Something more org-generic.

> DSPy with GEPA should work nicely

I think that would be a really really interesting thing to do on a bunch of different tasks involving developer tooling (e.g. git, jj, linters, etc.)

Combine that with retrying the same task again but with the improved skills in some sort of train loop that learns to bake in the skills natively to obviate the need for them.

The path to recursive self-improvement seems to be emerging.

This isn't about income.

What is it about if not income?

Income is what you earn from your labor (the things robots will do in the future). Capital is setting money to make more money (e.g., by buying robots to get rid of labor that earns income).

Wealth. You can be fabulously wealthy without an income.

Capital ≠ income

- The hard part of a compiler is the parser. Find an existing parser, then emit using that language's web templates.

- Your DB query is better in an inverted index.

- Consider your data locality carefully.

The goal of post-modern society is to create wealth without additional energy costs.

If I write software that schedules health care more efficiently, I've created value and therefore wealth. If I make a video game that's more fun than the previous generation of games, likewise.

That is, IMO, arguable. Entertainment has always been valued by humans. It is just the non-physical equivalent of fancy clothing or jewelry. And clothing/jewelry is most certainly a form of wealth. So, it can be argued that things that you can buy that make you feel better emotionally or increase your social status are forms of wealth.

That some forms of entertainment may be detrimental if abused in the long-term is an orthogonal topic.

I tend to look at consciousness as a spectrum. And when we reduce it to a binary (is it conscious?), we're actually asking whether it meets some minimum threshold of whatever the smallest creature you have empathy for is.

So yeah, Claude Code is more conscious than raw GPT. And both probably less than my dog.

Quickjs will do this.

Definitely, iff you have to provide the context with every task. If agent memory worked better and across your whole team, then providing context might be much easier

I read the article, and I'm struggling to see what ideas it brings beyond CodeAct (tool use is python) or the "task" tool in Claude code (spinning off sub-agents to preserve context).

Cursor when not in "MAX" mode does its own silent context pruning in the background.

Also, your function needs to be very careful on closures. Date.toLocaleString and many other js functions will be different on client and server, which will also cause silent corruption.

If you invoke `Date.toLocaleString()` in a map callback, it will consistently always run on the client.

I don't see how this very contrived example pipelines:

    client.getAll({userIds}).map((user) => user.updatedAt == new Date().toLocaleString() ? client.photosFor(user.id) : {})

or without the conditional,

    client.getAll({userIds}).map((user) => client.photos({userId: user.id, since: new Date(user.updatedAt).toLocaleString()})

Like it has to call toLocaleString on the server, no?

Neither of these will type check.

You can't perform computation on a promise. The only thing you can do is pipeline on it.

`user.updatedAt == date` is trying to compare a promise against a date. It won't type check.

`new Date(user.updatedAt)` is passing a promise to the Date constructor. It won't type check.