I built a very similar server myself [0] with a similar setup. I run different models for different purposes, but the primary one currently is kimi 2.6. I run kimi as the orchestrator model and then qwen, Gemma and others for specific tasks (sometimes loaded dynamically based on the task at hand), all exposed through the pi harness. I also use Hermes for some personal repeated tasks which connects to the same models, hosted on my local Mac Studio.

I am not even going to pretend that this is financially reasonable option. I simply wanted to have a local models. Maybe down the line, as cloud models become less subsidized, I might benefit from having a local setup, but for now, it wasn't the most prudent financial decision.

But one big benefit is that I never have worry about my account being randomly banned nor I have to worry about running out of quota. I still use codex and opus for some specific tasks, but as tools are improving, I need them less and less.

[0] https://x.com/synopsi/status/2024235558193811778?s=20

I have built something like this and in process of collecting the data.

Frontier users: 527,865 Light indexed: 527,865 Ready to queue: 9,083 Fast scores ready: 0 Activity events 24h: 30,266 Fast scores completed 24h: 19,123 Deep jobs completed 24h: 3,043 Fast-score ETA: n/a Deep-hydrate ETA: 69h Stale running jobs: 0 GitHub backpressure jobs: 19,113 High automation signals: 4,608 Medium automation signals: 1,327 Completed jobs: 74,714

Biggest challenge is Github's rate limits. At this pace it will take two more months to have 98% coverage. But after that the maintenance should be quite straight forward.

I don't want to defend LLM written code, but this is true regardless if code is written by a person or a machine. There are engineers that will put the time to learn and optimize their code for performance and focus on security and there are others that won't. That has nothing to do with AI writing code. There is a reason why most software is so buggy and all software has identified security vulnerabilities, regardless of who wrote it.

I remember how website security was before frameworks like Django and ROR added default security features. I think we will see something similar with coding agents, that just will run skills/checks/mcps/... that focus have performance, security, resource management, ... built in.

I have done this myself. For all apps I build I have linters, static code analyzers, etc running at the end of each session. It's cheapest default in a very strict mode. Cleans up most of the obvious stuff almost for free.

> For all apps I build I have linters, static code analyzers, etc running at the end of each session.

I think this is critically underrated. At least in the typescript world, linters are seen as kind of a joke (oh you used tabs instead of spaces) but it can definitely prevent bugs if you spend some time even vibe coding some basic code smell rules (exhaustive deps in React hooks is one such thing).

I am in SD and would love an invite. I am keep thinking about uniting more like minded people for a while. My email is r@seslu.com

Hear hear

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There are 27 countries in EU with different motives, morals, interests, etc. Just because you agree with the decision of one country in one instance it doesn't mean you would agree with them all. But once you give them the powers it's impossible to take them back. It's a bad slippery slope.

Just to be clear here, your issue is with the number of member states in the EU?

In other words you would be fine with Canada arresting employees of Clearview if they tried to enter the country after Canada deemed them profiting members of an organization that was breaking the law in Canada?

The courts are altering their views on scrapping. This [0] is a good paper that explored the last 20 years of rulings (although it hasn't been updated with the most recent cases).

[0] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3221625

Quick note for the osohq team: The "Read the docs" button leads to 404

Doh, fixing now. Thank you!