Hacker Newsnew | past | comments | ask | show | jobs | submit | ramoz's commentslogin

> Think shared Claude Artifacts that don’t live @ Anthropic.

Shameless plug, I've built a self-hosted capability here with things like live collaboration for humans and agents. There is a native cloudflare deplyoment and integration with Cloudflare Artifacts. PR for tunnel would be appreciated.

https://github.com/plannotator/artifact-server


GLiClass is performant, and its zero-shot classification scores are in the same ballpark as the Terra-level results Jev points to.

https://github.com/knowledgator/gliclass


thanks, it's definetly relevant

Thanks!

Rereading some things and because there's no official benchmarks, I misspoke about the ballpark comparison., but the open model's still a useful foundation to work with

Guess I'm a bit less impressed seeing that for some of the more intelligent driven+action work -- splitting requests in the video -- they had to kick out to an anthropic model.

That's fair, but it highlights how this would actually be used. It doesn't really seem like a competitor to other models but instead a way to make these real systems more enjoyable to deal with.

Haiku, to rewrite a sentence as two discreet commands.

I agree that it was notable that they delegated to an existing LLM, but I don't think it detracts much from the value proposition (not yet proven) of their demo.


Agreed but is it much easier to deal with if you need to have all of these sub processes integrated? How does one know when you need to reword a request? What if Anthropic then has a type error, then debugging that just got harder.

Artifact Server is an open source alternative to Claude Code Artifacts; enabling teams to own, share, and collaborate on artifacts throughout the development lifecycle.

https://github.com/plannotator/artifact-server

https://artifactserver.com

It runs locally, deploys to Cloudflare, GCP, AWS, or anywhere Kubernetes. It also creates live feedback loops with agents like Pi and Claude via MCP channels.

Why

There are questions I don't like having to ask when using Claude:

  - Why am I going to a claude[dot]ai domain to look at my local development artifacts?
  - Why are contractors sending me paid work in a claude[dot]ai link on their account?
  - Why can I not easily persist, version, and share these artifacts with my team and other agents?
Anyway, artifacts are good (and the CC team has done a great job evangelizing HTML and cool workflows around it). They are becoming a substantial part of the development process and teams need more ownership & collaborative capabilities.

Artifact Server creates a collaboration surface for human-to-human review, integrated AI feedback, and versioning. I can tag Pi in an artifact comment and that comment will queue immediately in Pi (no polling!).

I also think Git is the right memory layer for artifacts. Having provenance of what changed and why is useful esp for multi-agent workflows. Versioned artifacts are a key feature along with the sharing/collaboration features.



I bought the game so I could study the code. Unfortunately it is wasm & obfuscated. I'm gonna see what my handy dandy big giant brain buddies can do with it.


What does this mean for Fable limits exclusively?



Why did you move from on-dev-machine coding to @claude in GitHub if it's a weaker capability?

Im not convinced of any of these cloud or tagging solutions where I get to the point of moving coding away from my dev's machines.


Two things: (1) models are far more autonomous and run for longer coherently, (2) visibility into the development process was lost in local development.

Because models run for a long time autonomously developers need to manage more agents simultaneously. At that point you basically need a tracker for tasks in flux, and compute for each agent. It also means that the interactive monitoring isn’t as helpful anymore.

Regarding visibility, developers now think in high level architecture rather than lines of code, but implementation details are still important to document. We also want to understand when agents are hitting pain points. Both of these basically require archiving agent outputs more deeply than just code changes and commits.


I see. What would the proper solution then look like for when we should consider moving our teams? Sounds like you you said they're all current ones are missing ergonomics. Do you think it's slack code?


I created /bro a couple model iterations prior. I use it everyday many times a day and it's getting worse. I was actually using it more with GPT models but they have been getting better.

https://github.com/backnotprop/bro/blob/main/skills/bro/SKIL...


Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: