"This will never work as a currency, because of the max number of bitcoins it will inherently be deflationary, and the value will go up, which means that there will be a disincentive to spend it, because the value will just go up..."

Yep... Did not buy any.

Thanks!

So this means that every node in the graph has to be a fully fledged agent runtime with the smarts to handle an arbitrary filesystem.

I guess there is some sort of tool call that the agent has to tell the runtime 'I am done, and I succeeded go to the success node in the parent state machine'

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I think I have been trying to approach a slightly different problem where you have a mostly deterministic control flow of steps/ nodes in the graph, but individual nodes can be pretty stupid/ small models, so having a more constrained universe should be more reliable. (My intuition)

My example is a citation checker for an essay -

1. generate a list of claims in a paragraph, For each claim: Read the attached citation, validate that it backs up that claim.

The output is a nested json structure with a list of claims with a explanation+binary classification of whether each one is supported.

This is not really agentic, and the nodes would be claim identification > validate claims (in parallel) > deterministically merge the validated claims into a unified module.

It should be very token efficient, and since it is so constrained I think I can get away with tiny models, and small context.

At least that is my hope... But I think I need typed IO/state so that the llm that writes the graph can deterministically say that the individual nodes complete the problem wholly.

It may not be clear to a non-english first language person, but when I read Claudes documentation, my brain immediately picks up claude-speak. Therefore, I expect the code to be generally correct, maybe, depending on how specific I was during my prompting. In no way shape or form do I really trust it, at least until i dig into the code and validate my mental model. And query the review for edge cases etc...

By writing your documentation with Claude, my brain immediately associates the quality of the project with the quality of unreviewed Claude output.

To a degree this is unfair, as it is like judging the quality of someone's work based on their accent.

But Claudes accent, has a high correlation with Claude, so unlike with people, where an accent has no bearing on technical ability, Claude being Claude does.

I would much rather read a typo ridden sentence than claudism, even just as a forward, explaining what you did vs the ai, and telling the users how much we should trust it.

Also, If you really insist on using AI to write, have another model rewrite docs/comments into regular English (opus 4.6 for example is much better than 4.7, 4.8, or 5.

It is open source so you can do whatever you like, but people (especially native English speakers) will discount your work, because Claude, especially opus 5 writes very very badly.

The people who say they would rather see a typo infested mess of a readme are serious. Or even just write in your native language and then have Claude translate.

Both of those are better indications of proof of effort than a Claude readme.

Is it a actual Linux kernel + filesystem under the hood?

Or did you just use the standard utilities compiled for wasm,

how does network access work (assume it doesn't because of coors)

Can you run non-wasm programs? How do entry points work - what about ctrl-c and interrupts for long running programs.

You do not discuss any of this and it seems half baked.

(This coming from someone who has explored how to do this for a vscode in browser editor playground)

I think Facebook would need to do a lot more to balance the scales.

Additionally:

Live graph reconfiguration Timed events Easy simd support Support for non-mmu based architectures Imperitive configuration management and querying at the single runtime level. Can be compiled to wasm, and run in the browser (w/ coors headers). IO/user interface and any GUI is done via typescript.

Like there is no explicit goal aside from each 'expert' getting roughly equal weight?

And it happens that when you train the router you do end up passing certain classes of problem to each expert - just as a training result nothing as clean as a python expert. But math vs creative writing will tend to rely on different experts over the majority of the inference?

I do not know what I am talking about, this is my limited understanding...