Did a migration myself last week from using playwright mcp towards playwright-cli instead. Which has been playing much nicer so far. I guess you would run into the same issues you've already mentioned about running chrome headless in one of these sandboxes.

I'll for sure keep an eye out for updates.

Kudos to the project!

I've been trying to get microsandbox to play nicely. But this is much closer to what I actually need.

I glimpsed through the site and the script. But couldn't really see any obvious gotchas.

Any you've found so far which hasn't been documented yet?

For me, I would say speed (not just time to first token, but a complete generation) is more important then going for a larger context size.

I've been experimenting with a similar setup. And I'll probably implement some of the things you've been doing.

For the proxy part I've been running https://www.mitmproxy.org/ It's not fully working for all workflows yet. But it's getting close

Codex models tend to be extremely good at following instructions, to the point that it won't do any additional work unless you ask it to. GPT-5.1 and GPT-5.2 on the other hand is a little bit more creative.

Models from Anthropics on the other hand is a lot more loosy goosy on the instructions, and you need to keep an eye on it much more often.

I'm using models interchangeably from both providers all the time depending on the task at hand. No real preference if one is better then the other, they're just specialized on different things

His rant about CS historians is also a fun subject

I very much share your experience. As for the time being I like the experience with codex over claude, just because I find my self in a position where I know much sooner when to step in and just doing it manually.

With claude I find my self in a typing exercise much more often, I could probably get better of knowing when to stop ofc.

Either way, a more fine grained control over the GC is probably preferred over something like this.

Some of the qwen models are too, but they seem to need a bit more handholding.

This is of course just anecdotal from my end. And I've been slacking on keeping up with evals while testing at home

All of these alternatives means different things when you say it takes +20 seconds for a full response.

But anti-cheat hasn't been about blocking every possible way of cheating for some time now. It's been about making it as in convenient as possible, thus reducing the amount of cheaters.

Is the current fad of using kernel level anti-cheats what we want? hell nah.

The responsibility of keeping a multi-player session clean of cheaters, was previously shared between the developers and server owners. While today this responsibility has fallen mostly on developers (or rather game studios) since they want to own the whole experience.

Kinda hope they revisit this idea in a near future again

I've been experimenting with having a rules.md file within each directory where I want a certain behavior. Example, let us say I have a directory with different kind of services like realtime-service.ts and queue-service.ts, I then have a rules.md file on the same level as they are.

This lets me scaffold things pretty fast when prompting by just referencing that file. The name is probably not the best tho.

Arma usually gets the more complex and janky stuff (in a fun way). While the others are more modified experiences.

Like Squad, we're they've re-created star wars battlefront

Larger titles swapped over to more control in order to extract more money from the players, but also control the experience.

There is however some AAA titles every now and then which support hosting your own servers. But they're quite few these days

I would say this isn't exclusive to the smaller OSS models. But rather a trait of Openai's models all together now.

This becomes especially apparent with the introduction of GPT-5 in ChatGPT. Their focus on routing your request to different modes and searching the web automatically (relying on an Agentic workflows in the background) is probably key to the overall quality of the output.

So far, it's quite easy to get their OSS models to follow instructions reliably. Qwen models has been pretty decent at this too for some time now.

I think if we give it another generation or two, we're at the point of having compotent enough models to start running more advanced agentic workflows. On modest hardware. We're almost there now, but not quite yet

Quote we're talking about: > To work with ChatGPT Connectors or deep research (in ChatGPT or via API), your MCP server must implement two tools - search and fetch.

Reference links:

- Using remote MCP servers with the API: https://platform.openai.com/docs/guides/tools-remote-mcp

- Which account types can setup custom connectors in ChatGPT: https://help.openai.com/en/articles/11487775-connectors-in-c...