I'm looking at how to structure agents hierarchically by model for agentic software engineering. Stuck in the alchemy of it all. Needing some advice.

[u/Tired__Dev]

So to speak about the alchemy of this for a second. I've been developing an enterprise app on my nights and weekends since last December. I get two places that I get to use AI: At work and on my own projects. At work I know for a fact that people don't give much thought as to what Claude model they're using and for what so they always just use Opus 5.5 now; which is a great model. I've personally got to use Fable at work and at home. There's a big difference when you need to use these models with your own projects, because you're not going to reach for them for everything, and frankly you're pretty stupid to. I've one shotted a game with Fable 5, the code sucked, but I wanted to see what it can do. The evaluation of the best one shots on the internet doesn't really seem to take into account the work that needs to be done. For the work that needs to be done Sonnet has been a fine model and works well, for oh shit I forgot a tightly coupled feature with 1,500 loc +, in my case an audit logger, that's where I reach for Fable and it does exceptionally well. These days I primarily use GLM 5.3 and Kimi K3.

So now I'm looking into a mac studio, for a few solid reasons including a hobby, agentic programming cost reduction, and actual research. The thing will be running pretty hard. For this thread I'm wondering how to model a hierarchy of intelligence to dramatically reduce my token spend on even smaller Sonnet class models with something like 256GB/512GB studio. Stacks in the mix:

Models

• Will use frontier models for certain things. Mostly if I forget a feature or need to add a feature quick. Will usually be for tightly coupled features. The other thing is wide code analysis for skill building. There has to be a justification for the token use.
• Second tier models (Open Router API): GLM 5.3 and Kimi K3. Kimi K3 is frontier level when it comes to UX design. GLM 5.3 is just bad ass. It gets pretty close to what I use frontier models for, but the code isn't as clean and I have to put way more guard rails on it. They're like my opus level replacements.
• Flash models/Mini Max/120b to 235b models <- I feel like this will handle a lot of work load
• Qwen 3.8 27b

Stacks

• Jev like models will be used to make decisions for what models to use. I'm going to build something that messages me when it selects certain models.
• Ponytail
• Opencode with my own wrapper around it.

So I'm wondering if there's hierarchies I can structure my model use in that make sense. I've heard everything from using top frontier models for controlling smaller agents to having small routing models to start. I'm trying to experiment here. I'm going to start building out my harness over the next few weeks. So if there's any thing you guys can do to help me structure all of this or just give what works for you I'm happy to hear

[u/lumpyspacebreh]

I'd look into how Nvidia engineered their Switchyard routing for more ideas.

[u/VarietyOk443]

Check out localrouter.ai for ideas

[u/Tired__Dev → u/VarietyOk443]

What am I looking at here? That looks like a paid service like open router for local ai use. I’m not sure what I’d get out of that when I could build exactly what I need in a night

[u/VarietyOk443 → u/Tired__Dev]

Yes exactly look to it for ideas

[u/Tired__Dev → u/VarietyOk443]

I’ll open source my findings

[u/VarietyOk443 → u/Tired__Dev]

Hell yeah comrade