samuell
1. LLM usage, in particular unsupervised, tends to build up "cognitive debt"
2. It tries to characterize the concept, including to propose a score for it
3. Notes that the level at which one can let the agents loose (and allow some CD) differs quite a lot between core business domains and more peripheral ones
Indeed. And those who knows how to implement this, might also be the ones with capabilities to deploy it on a large scale (via bot nets or whatever).
What about state actors, suddenly getting a possibility to plant backdoors in millions of websites, etc.
You don't have to be too imaginative to see the "economics" of this.
It succeeded to do what Drupal tried but never managed to do:
It is both extremely stable and extremely flexible at the same time.
By having an extremely generic and small core, combined with an extremely powerful programmatic API (basically jquery for data from the CMS, but better), you don't need fiftyeleven modules to achieve some basic tasks.
[1] https://processwire.com (don't get put off by the .com. It is open source).
> Now what are "IN" and "OUT" that our pseudocode receives IPs from and sends them to? They are not the names of connections, as this would tie a component's code to one place in the network, but are things called "ports". "Portae" means "gates" in Latin, and ports (like seaports) can be thought of as specific places in a wall or boundary where things or people go in or out. Weinberg (1975) describes a port as
"... a special place on the boundary through which input and output flow... Only within the location of the port can the dangerous processes of input and output take place, and by so localizing these processes, special mechanisms may be brought to bear on the special problems of input and output."
https://www.jpaulmorrison.com/fbp/concepts_book.shtml
Still, I'm amazed at how it took so long before they became mainstream in data flow oriented libraries and DSLs.
And it seems J.P. Morrison was also highlighting Named ports as particularly useful, which is also perhaps what I should have highlighted in my initial comment above.
It's gotten better lately it seems, but a lot of tools skipped that part, which now requires tons of specialized syntax just for routing of multiple parallel streams.
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Thank you for kind words!
I'm personally sitting on an extremely limited Geforce GTX 1660 6GB, and would like to see how far one could go even with such a crappy card.
At least it was quite amazing to see the difference between CPU-based and even this crappy GPU-based inference when trying out some tiny models in jan.ai. It's still like orders of magnitude faster at least.
player2.reveal -> player1.observe
player1.reveal -> player2.observe
That is, enabling data flow connections between individual inputs/outputs, and not just between components, which otherwise is too limiting, and typically causes a lot of extra syntax to handle that routing otherwise.Wrote about it in the context of workflow systems way back (https://livingsystems.cc/posts/workflows-dataflow-not-task-d...)
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Edit 11:12 CET: I realize that “named ports” better captures what I had in mind here, as elaborated in a comment below.
If you prefer to keep things local and open source, and your agents' notes do fit in issues, you might want to check out Epiq too, which is a local but distributable issue board synced via an event log mechanism to ensure consistency when syncing across repos:
"[...] he has given a law to which they must conform."
- Psalms 148:6 (CJB)
:)
The graph visualization in beads surely is a neat thing for showing things, but the replay feature in Epiq should provide a similar understanding of what happened.
But again, it seems to me Epiq is the tool that better allow the user to jump right in and collaborate with the agents on the board.
(Again, this is from a brief look, so I could be missing things).
This is btw why Epiq was developed, to keep the board as code, git-backed, distributed (via an event log mechanism), and with the ability to replay the board, to see what agents actually did:
Local TUI issue board for agentic workflows with time travel, backed by Git
To do your best work you need to work like a sculptor
Crafts(wo)manship
Ask HN: Best open source way to run local open-weight LLMs in 2026?
As we are lucky to have great open weight models these days, I was wondering what is the recommended way to run these models locally, while staying with open source software that doesn't track you etc?The only tool I've really tested is Ollama, but learned recently that it is pivoting into a less open direction, I'm not so sure about using it anymore, and was interested to hear your opinions...
The Cost of Cognitive Debt
I'm Done Coding with AI
For me, XFCE (On Linux Mint currently) turned out to be the answer. Has configurable keyboard shortcuts for pretty much anything you need, like tiling to top/right/bottom/left, corners, moving or resizing windows etc.
To me, that is the best of both worlds - a normal window manager with keyboard shortcuts for tiling the windows when you want.