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Oh wow! This would've been so useful at my previous work place. I'll save this one for later. Looks pretty decent too for homelabs!

I wonder if there is any plans on extending it further? (just a bit)

Just me being curious about the results.

Were you using the same setup to call these models? was it pi/opencode or was it codex/claude etc etc.

Because I've started to see larger and larger drifts in the results depending on the agent it self rather then the model.

> All that keeps jumping out at me is how they've set it to refuse giving users thinking tokens and prompts for full reasoning in output

I keep seeing comments added to code, which reads like reasoning output instead of meaningful words. I see this behavior for both OpenAI and Anthropic models (for several harnesses as well).

But this is a sample of one. And I may be in a situation where I'm more negative to the output from LLMs in general.

The way I interpret this is:

After some inactivity it goes into some dormant mode. Where it will only consume some storage. The next time someone tries to access this artifact it just restores a snapshot from last working state.

I guess the public url part is working similar to how OpenAI and their Sites are. E.g: their personally only available to you, until you change the sharing options.

> My new suspicion is now that they didn’t got drastically smarter, but they got trained on the user input on the previous generations

I think this happened around Opus 4.5 or 4.5 and the same for GPT 5.4.

The more I use those models, harnesses, techniques for guidance etc etc. The more I land in going back to writing software by hand again. Maybe not all of it, but at least the crucial parts + foundations.

I used sublime text over so many years. Still find it to be a marvel when it comes to large text files, and how well it still handles them

Thank you for answering these questions. Looking forward for the next write up about this.

I had a similar issue with mine. But was able to reset it with Fn + z + j for a couple of seconds.

It took me way too many years before I set this as a default in my profile files.

The funny thing is. I kept missing this detail every time I read through git. Feels like I was blind to the whole concept of it

Super cool! how long did it take to generate all those custom images?

Yee I gotcha.

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!

Oh woah!

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?

I really don't have any numbers to back this up. But it feels like the sweet spot is around ~500k context size. Anything larger then that, you usually have scoping issues, trying to do too much at the same time, or having having issues with the quality of what's in the context at all.

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.