rickette

Some guy named Claude screwed up.

This is the successor of https://github.com/JetBrains/xodus, but with quite some differences.

Interesting but how is an "autoresearch loop" different than creating a spec and X number of testcases and letting an agent run against these testcases and the spec?

LLMs.txt is also nonsense since it isn't adopted by any of the major AI players.

Thanks for the insight, changes my perspective.

Easy to criticize this, but I rather see GitHub survive than fail under its own success. So thanks for acting on this MS!

Does any of the LLM providers actually use llms.txt?

If I remember correctly this "standard" was setup by someone but without involvement of any of the major AI players.

Still Go/Rust/Typescript is on a whole other level of adoption compared to Zig

And Azure Flexible server please

Curious on what (how much) hardware your running this.

Really? I'm daily driving JetBrains IDEs on Apple M3 and don't recognize any if this. Just give it a bunch of extra heap memory (eg 4g instead if 1gb) and it's fast!

Well the docs say the old way (no Kafka) is on its way out:

"However, this architecture is set to be deprecated in a future release."

So it doesn't stay optional unfortunately. It quite a heavy dependency to include...

Couple of years ago us-east was considered the least stable region here on HN due to its age. Is that still a thing?

Adobe Flex with Adobe Catalyst. Design a GUI in Photoshop, export it to Flex/Flash to add interactivity.

Looked cool during demos. Got killed when Flash died.

Exactly, also requires authentication. How can this be 10/10?

Only the higher/highest tier Google Workspace users can send these kind of emails. Anyone can read them.

Only available for Google Workspace: Enterprise Plus with the Assured Controls add-on.

There's a clear text password in one of your GitHub Action workflows: https://github.com/dbos-inc/dbos-transact-golang/blob/main/....

JetBrains native AI assistant supports Ollama out of the box. No need for a 3rd party plugin anymore.

See https://www.jetbrains.com/help/ai-assistant/use-custom-model...

https://github.com/authelia/authelia?

Shindig https://shindig.apache.org/ was the reference implementation of this spec. Was pretty novel at the time.

Well to be fair: this doesn't happen very often. It's quite a stable service in my experience.

GitHub Actions originally supported HCL (Hashicorp Configuration Language) instead of YAML. But the YAML force was too strong: https://github.blog/changelog/2019-09-17-github-actions-will....

Thanks for the insight!

Would that kind of data not compress like crazy? Or would they need to keep all that data hot and fast.

Cool. Also https://github.com/deepseek-ai/3FS by DeepSeek which came out of High-Flyer a Chinese HFT firm.

Over 500PB of data, wow. Would love to know how and why "statistical models that produce price forecasts for over 50,000 financial instruments worldwide" require that much storage.

Radix Trees are (often?) used for this purpose, for example in Chi: https://github.com/go-chi/chi. Coincidentally FSTs and Radix trees share some similarities.

Lots of comments here remind me of the time GitHub was purchased by Microsoft. It would be the dead of GitHub. While in fact it got better: GitHub Actions (pretty neat CI system) happend under Microsoft. Free private repos happend under Microsoft.

Now this time it could be different. But last time wasn't that bad imho.

Would Postgres FTS (ts_vector) benefit from this storage engine?