Supreme Leader Wiggum

If I were to stream… and it was mostly just me doing my day to day work, while talking to chat, would anyone watch? Setup isn’t going to be anything stellar, no real agenda - I’d pretty much just go do stuff across 5 or 6 repos in parallel & talk through what I’m thinking

Works quite well

You can just make gpt pro return a git patch. Download it and apply it

I saw a lot of people saying Module Federation doesn't work with Angular. Felt like there was a lack of examples out there. So here's two: one with @vite_js 8 and another with @rspack_dev Rsbuild.

@yagiznizipli @X I’ll help you guys move off webpack

We're slowly getting there with the performance of @X web (lower means better)

@oliver_bauer @nstlopez No discord. Just DMs in discord

@ScriptedAlchemy @nstlopez Can I also join the discord ? Currently building my second trading after a first on trend / news follower strategy

Going full quant and training financial model. Stealing some ideas from TikToks recommendation engine around realtime adaptive training of the model.

@Tylopilus @nstlopez No just DMs

@ScriptedAlchemy @nstlopez Wait you have your own discord channel?

@jeffscottward Yeah I use them a lot. What would be nice is if this were “stacked” worktrees since usually work has dependencies on other agents. So restacking and rebasing a worktree stack would be quite useful

Is there anyone out there who uses git worktrees really aggressively or agent orchestrators? Like creating multiple branches within a work tree off of a base repo? ———— We are potentially cooking up something really crazy in Maestro and wondering if more than one branch per work tree makes any sense realistically? Typically it’s one feature branch per Work tree right? @ScriptedAlchemy @theo @kenwheeler @elonmusk @jbrukh @Jason Please Retweet! #git #worktree #ai #ui #agent #orchestration #claude #codex

@nstlopez Check discord message. I sent you the “master plan” that contains the system end to end. From project creation to deployment

@ScriptedAlchemy I need to up my game and get into training myself

@derekdamko Can likely get another 1tb vram if necessary.

@ScriptedAlchemy You do not have enough VRAM for any of the large open weight models. Example GLM 5 is 1.5 TB on disk which will 1.7 loaded into ram. Then you will need a large context window so you are probably looking at close to 2TB of ram needed for fine tuning.

I have a B200 cluster. Looking to fine tune a model. What’s the best OSS model that’s near GPT 5.4 or opus 4.7

@omniwired Cost. I wanna fine tune a new tokenizer encoder/decoder. Only have enough burn for 1 or 2 runs.

@ScriptedAlchemy Is it coding? Then GLM 5.1 But why only try one, do Kimi and deepseek pro next. Fine-tune to do what

@HOARK_ Turboquant for inference tho, not training. But yes.

@ScriptedAlchemy i would do 5.1 with turbo quant

@ptremblay Want a big 16fp model. Like GLM or kimi

@ScriptedAlchemy what about a 1.58-bit distill of Qwen 3.6 27B? (BitNet Distillation) arxiv.org/abs/2510.13998

@julianharris 1tb of ram, can get more if needed tho.

@ScriptedAlchemy Not sure how much RAM you have or whether you are ok with open weights but Deepseekv4 is killer.

@kentcdodds @MichaelThiessen @ZephyrCloudIO Token burn makes it hard progress. But, I do believe 80% of the concept can be created with Claude code or codex plugin, just use a LLM do perform the dependency linking and frontmatter. Plan to rewrite superpowers plugin and add a MCP, which should mostly recreate it.

@MichaelThiessen @ZephyrCloudIO @ScriptedAlchemy Nope, something else. Still curious where that tool is going Zack!

I figured out how I'm going to teach Product Engineering and it's going to use @ZephyrCloudIO to do it. So jazzed about this! Stay tuned for the first cohort announcement!

@yolaplace GLM on par with GPT 5.2 - perfectly acceptable. Especially with 5.4 as reviewer and team lead over GLM subagent

@ScriptedAlchemy How do you rate GLM vs 5.3-codex?

Chinese models to the rescue! GLM has been pretty good

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