1. Core reasoning layer → Claude + GPT
This is your thinking engine.
Claude handles deep analysis, long documents, structured reasoning
GPT handles execution, coding help, formatting, and fast iteration
How it plays out:
“What is this argument really saying?” → Claude
“Turn this into a blog, script, or code” → GPT
This split avoids the most common failure mode: one model trying to do everything and doing none of it well.
2. Research + long context → Gemini
Gemini sits underneath your reasoning layer when you’re dealing with large inputs.
Big documents
Multi-file analysis
Long transcripts
Mixed media context
Think of it as your high-bandwidth reader, not your final writer.
3. Coding layer → Cursor + GPT/Claude
Cursor becomes your control center.
Inside Cursor:
GPT → fast coding + scaffolding
Claude → debugging + architecture clarity
This combo is where most modern dev workflows are quietly converging.
4. Open-source layer → Ollama / local models
Ollama gives you local control.
Use it for:
Private data
Offline experiments
Cheap batch tasks
Model testing before scaling to APIs
This layer is less about “best output” and more about freedom and control.
5. Model routing layer → OpenRouter
OpenRouter is your traffic controller.
Instead of choosing one model, you route tasks:
Claude for reasoning
GPT for production output
Gemini for long context
Open models for cost efficiency
This is where the stack stops being “tools” and becomes a system.
6. Knowledge layer → AnythingLLM / Notion-style memory
AnythingLLM sits on top of your documents.
Purpose:
Turn files into queryable memory
Build project-specific AI brains
Stop re-explaining context every time
This is where AI becomes persistent instead of stateless.