Garlef

Because they use resources (tests, etc) and once you have a few running it impacts you.

if (you love me):

  give me up

else:

  I shall begin to hate you
  # i feel it

> Thanks for the poem, the feedback and the interest.

It's a paraphrasing of bowies "Life on Mars"

> pneumatic

Interesting! Will check out.

> ... that in a few minutes I can load the context in my working memory and be forever satisfied once I'm done that this decision will never have to be made again

Okay this is an aspect I've not considered enough maybe. But this then applies mostly to decisions that can be phrased project-agnostic.

> My understanding of your implication is that this isn't worthwhile

No. I actually think it is worthwhile!

But I don't think it differs substantially from just having an ad-hoc project harness that's just a bunch of markdown and is maintained by the agents based on the discussions.

And this post is a saddening bore,

'cause I wrote it ten times or more

It's about to be writ again

As I ask you to focus on

phrases spilled out by an LLM

...

---

On a more serious note:

I've built similar things ad-hoc when creating my project harnesses.

These decision lists kinda work but also they don't: The real challenge for me is fighting decoherence and keeping the orientation in a generated project.

So:

- I guess this works if you review and reshape the agents outputs manually.

- It does not help you a lot building a software factory.

OpenAI also doubled the price of their subscription in the same time, right?

The top comment is right.

> The sort of obvious answer is the same reason McKinsey hasn't taken over the Fortune 500

The other perspective is:

In a sense, OpenAI is creating 1000s of companies. They're just not incorporated and they let these companies clients run the company: It's in every every vibecoded app that replaces someone's SaaS subscription.

What's changing here is that not only does labor get replaced by AI, it's also the relationship between software companies and their clients.

yes ~ one perspective is "a monad is an monoid in the (...) category of endofunctors"; the other perspective is "a monad is a kleisli category"

Gold is worth much more per kilogram than water... But it's also much more expensive.

Interesting. I come from a math background and for me, monads capture a notion of "things that depend on a type". So for every type X you can think about Lists/Records/Trees/... of X. And if you're lucky this gadget let's you do two things: 1. You can turn every instance x of X into a primitive List/Record/Tree/... of Xs. 2. You can flatten Lists of Lists of Xs into plain Lists of Xs, etc.

This is something you see a lot once you know what you're looking for.

And if you're really lucky, these two are nicely compatible:

For example there are two ways to get from L(L(L(X))) to L(X): By either flattening first in the inside or first on the outside.

And for a monad, you get the same result either way.

And the computational part is then really more of a consequence: If you've got some function of type X->L(Y) and another one of type Y->L(Z) then you can compose them to a function of type X->L(Z).

I think the main example on the landing page is a bit counterintuitive?

Rock Paper Scissors but the graph presents the reveal as a reaction to the observation? In a loop? And somewhere there's a min-delay of a magical 1 sec? Why 1 sec and not 0.1 sec? Can this build up and the players get out of sync? (A bit strange to 'just wait, lol' if the language aims at solving problems in distributed systems).

Overall the example would be better if it separated the game from the players and also split out the repeat loop.

Maybe let both player reveal to a host and then receive a result (and the choices) ~ This way both players can be sure that the choice of the other player is independent of the observation.

(I know that the example is 'correct' in that the choice is made independent of the observation but I think the example could be improved if it solved some of the coordination problems involved in the scenario more cleanly through code architecture).

Overall I quite like the idea of having this polyglot meta language!

... and even if you formalize it, it could still be false due to an error in the theorem prover itself.

Probably not part of the respective SLA

ah... so this is why my agents all made a signal noise when i used chatgpt on my phone?

I don't see how simply raising the income would change anything long term.

The main issue is that the affordability crisis is also a result of the market. And without changing the preconditions or mechanics we'd get the same outcome just with different numbers.

So:

- Build housing

- Make housing more affordable by allowing homeowners (= not renting out) to write off and/or write off-faster

- Give newly built housing better write-off conditions

- Prevent cartels that operate via "pricing as a service"