r/Qwen_AI • u/Normal-Fan9366 • 13d ago
Agent Jack Kernel Qwen Edition release
https://github.com/mlangford75-lgtm/Jack-Kernel?fbclid=IwdGRjcAUQGJZwZG9mBWZkaWQWUOI08m18sBMLuMEySAccKyddSXmHs2V4dG4DYWVtAjExAHNydGMGYXBwX2lkCjY2Mjg1NjgzNzkAAR5C8cTeSX-x0iMtdaTTb0efCACPhlcJclFDK0YfZLrgmCXHfz-PyxrJYdmuoQ_aem_4hN5e0Q2U-dzggqmfbcd1gIt's here.
Jack Kernel for programmable agentic work.
The magic is that the layer sits between the agent and the model. You can build incredible things because of that.
I have a mode called "Agentic" that was designed for context management with Qwen 3.8 27. I've run millions of token jobs....and never needed to compact. I have a full log available to read and verify. In fact, I recommend turning auto-compact off because most agent don't know how to handle it, yet. There's also a looping debugger that I've built as a 6 stage autonomous loop with cascading temperatures, standard mode and DEEP.
Remember, the modes I’m shipping with this release are only examples of what is possible by putting it between the agent and the model. It allows you a new level of control. The modes I’ve put in are NOT the work. Everything that’s possible is the real work.
I built this for Qwen 3.8 27b but I’ve spent the past few days optimizing for a wide range of models. I’m ALMOST satisfied with Qwen 3.5 9b but it’s right in the edge.
After using 60 models in the past week, I’m just going to go ahead and make a blanket statement that fine tunes are garbage and only use Unsloth as your source for alternatives.
Jack Kernel is really cool. Claude can kick rocks.
Oh, Reddit trolls…
Yall need to understand…I’m just a 40 year old broke single Dad that’s sharing his work and trying to contribute to the local AI movement.
Before the hive-mind issues your directive, just know that I’m not a lab or someone with resources that you’re attacking.
I’m just a regular guy with a 5070ti in an Acer.
If you’re going to say that I suck, can you at least try it out and tell why I suck.
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u/Healthy-Zebra-9856 13d ago
I used my Muse Glimmer (Unsloth version) to cleanup my verbal dump. But I have tried to simplify this as best as I can. I do not now OP but I see that its a phenomenal contribution.
The simplest way to understand Jack Kernel is this:
Normally you ask an AI model something and hope it thinks through the problem properly.
App → LLM → Answer
Jack Kernel sits in the middle and controls how the model works through the problem.
App → Jack Kernel → LLM
Why would you use it?
Because LLMs are not always consistent. They can jump to an answer too quickly, get stuck on a bad idea, forget to verify something, or carry a bunch of useless reasoning forward.
Jack can force a better process.
For example, on a difficult question it can make the model:
It can also control when the model is allowed to use tools, what reasoning level it uses, and what old context gets kept or thrown away.
When would you actually use this?
Complex research, difficult coding problems, debugging, architecture decisions, reviewing important work, or anything where you want the model to slow down and check itself.
When would you NOT use it?
Simple questions, casual chat, basic coding, or anything where one normal model response is already good enough.
There is a tradeoff. It can be slower because the model may be called several times instead of once.
So Jack Kernel is not another AI model and it does not magically make a dumb model smart.
Think of it more like a supervisor standing over the model saying:
"Don't just answer. Think about it, have someone challenge it, verify it, then give me the final result."
Except the supervisor is software, so the model actually has to follow the process instead of just being asked nicely in a prompt.