charlieflowers

Resolved it was on my end

Edit: Resolved now it was on my end. > fyi not working for me

Surprised it is not "Super Intelligence of America"

That tension is doing real work.

I still remember how hard I was struck by the scene in The Orville, where someone from another planet hears a Dolly Parton song playing and asks who it is. He goes on to say, "She speaks with the might of a hundred soldiers!"

She did. She is one of our species' great poets.

But do we really need a paradigm shift in how we express the concept of a paradigm shift? It's not like the meaning of the words expired.

But inference costs scale per task whereas platform services like postgres typically amortize across tasks. If you are selling tasks done by inference, then compute is part of your COGS and it scales per task.

Originally I replied here that I thought you were both missing the point (but I was wrong).

I wrote: It has a garbage collector and goroutines, so clearly it is not trying to be a systems programming language.

Then ... I saw that it does indeed pitch itself as a systems programming language. So, I guess you both are right.

If Gossamer were to drop that claim, then I'd say it looks impressive to me. I have often wanted this particular mix of language features.

The language choices demonstrate excellent taste though.

I interpreted it as referring to a table named "FROM" and fields named "SELECT", "WHERE" and "AND".

BTW, columnar is very similar to struct of arrays (SOA) and some of the reasons it works well overlap with SOA.

But shhhhh! Iran might read this!

I’m not advocating this, but it is worth observing that it is yet another problem one could attempt to address with dependency injection, similar to io and allocators.

Help me understand why not? I know solar power generation in space, and "beaming" the power back, was a naive idea. But this would actually use the power up there, mostly for training, but also for inference.

That claim seems reasonable. I have zero knowledge of the economics of launching and maintaining satellites though.

Not a merger, right, unless I missed something (admittedly skimming).

I have been thinking about this a lot lately. How do you capture key factors succinctly, and even harder, keep it succinct as it evolves?

The shrinking that property based testing does when it finds an issue is kind of what we need for specs/context.

The simplest example is that you can easily be wasteful in your use of threads. If you just write blocking code, you will block the thread while waiting on io, and threads are a finite resource.

So avoiding that would mean a server can handle more traffic before running into limits based on thread count.

Can you monomorphize the injected effect handlers using comptime, for io and allocators (and potentially more)?

You mean cell notes? If so, perfectly well, yes.

I do something similar with Claude Code. I say, "I ate a single serving of that Toasted Beef Ravioli that Aldi sells." Claude web searches, finds it, gets its nutrition info, then uses gspread to add it to the daily food log tab of my spreadsheet.

So much less hassle, lower activation energy needed than with MyFitnessPal.

I'm having great luck having Claude Code generate, read, and update spreadsheets by writing Python code that uses gspread.

But if you are saying that a human can instruct ai agents to refactor to prevent the big ball of mud, then you are saying that clean code *is* important.

It is an interesting possibility that must be considered. Only time will tell. However I disagree.

I think complex systems will still turn into a big ball of mud and AI agents will get just as bogged down as humans when dealing with it. And even though re-build from scratch is cheaper than ever, it can't possibly be done cheaply while also remembering the millions+ of specific characteristics that users will have come to rely on.

Maybe if you pushed spec-driven development to the absolute extreme, but i don't think pushing it that far is easy/cheap. Just as the effort to go from 90% unit test coverage to 100% is hard and possibly not worth it, I expect a similar barrier around extreme spec-driven.

Clarification: I'm advocating clean code in the generic sense, not Uncle Bob's definition.

AI detectors don't work.

Tell me if I'm understanding you correctly. I summarize this in my head as, "This person loves NixOS because it gave him GitOps for his OS."

He's about to have the most compute. Wonder if he can do anything noteworthy with it.

This list reads like, "AIs are not your typical braindead person on the street. They actually use a decent but not crazily advanced vocabulary."

I mean, "tapestry" is a great word for something that is interconnected. Why not use it?

We are going to start seeing that be the primary selection criterion. Pick a stack that agents are good at.

No i get the clarke reference. But how is an agent a dsl?

> "any sufficiently advanced agent is indistinguishable from a DSL."

I don't quite follow but I'd love to hear more about that.