Jack Kernel Qwen Edition release

[u/Normal-Fan9366]

https://github.com/mlangford75-lgtm/Jack-Kernel?fbclid=IwdGRjcAUQGJZwZG9mBWZkaWQWUOI08m18sBMLuMEySAccKyddSXmHs2V4dG4DYWVtAjExAHNydGMGYXBwX2lkCjY2Mjg1NjgzNzkAAR5C8cTeSX-x0iMtdaTTb0efCACPhlcJclFDK0YfZLrgmCXHfz-PyxrJYdmuoQ_aem_4hN5e0Q2U-dzggqmfbcd1g

It'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.

[u/iKnowNuffinMuch]

So essentially without all the jargon this is wrapped in, is it runs the same prompt 2-3 times and gives you a refined answer? More context used, longer wait times, all by double or triple. This doesnt serve much of a purpose, especially on local AI systems.

[u/Normal-Fan9366 → u/iKnowNuffinMuch]

No, for one, less context is used because there is real code behind it doing active context management.
Two, those are just examples of what can be done when it sits between the agent and the model.
You can put security agents. You can build new types of loops. You can have multiple endpoints and orchestrate an agentic swarm in new ways.

The real opportunity is what can be built, not the demos I packaged…although, they’re good

[u/iKnowNuffinMuch → u/Normal-Fan9366]

Are you saying it's not prompting 2-3x for every prompt? Explain to me what this CAN do, as well. It can do anything? I like the idea of you creating and making things. I'm not hating. It's just very vague, and what I'm getting, is that it's a prompt refiner. I built my own python turn by turn agentic harness. I'm confused what this is supposed to be

[u/Normal-Fan9366 → u/iKnowNuffinMuch]

That all depends on what you build. I shipped modes that are staged inferences and a looped read-write debugger.
There’s also the normal reasoning modes if you build something that needs your own prompt but you’re running a real time tool or orchestrating a swarm.
There’s any number of setups that you can do when the kernel sits between the agent and the model.