# Context: Multi-Tiered AI Subagent Framework I am building...

Prompt

# Context: Multi-Tiered AI Subagent Framework I am building a multi-tiered, autonomous AI subagent framework optimized for deep-context coding and architectural tasks. ### 🛑 HARD BUDGET CONSTRAINT: I cannot afford standard pay-as-you-go API billing. I am strictly using FLAT-RATE, CAPPED, or SUBSCRIPTION-BASED systems. My current tech stack and assets are strictly limited to: 1. **$20/Month Cash Budget** (Open to spending this on a single subscription like ChatGPT Plus, DevPass, Claude Pro, or keeping it unspent). 2. **Google AI Studio / Google One AI Premium** (Gives me access to Gemini 1.5/2.0/3.8 Pro and Flash models). 3. **OpenCode Go Subscription** ($10/mo bundled open-weight model environment). ### 🏗️ The Framework Architecture Layout My architectural logic is split into the following operational nodes: 1. **Orchestrator Node:** Claude Opus 5.5 (Handles high-level intent, system design, global state, and complex edge logic). 2. **Decision/Routing Node ("Jev"):** A dedicated routing layer that judges "thinking efficiency", monitors credit/token limits, and decides which worker subagent executes a task. 3. **High-Volume Context Worker Slot:** [ EMPTY / NEED SUGGESTION ] (Needs a model or setup that can handle massive repository reading, context chunking, and boilerplate generation without draining a pay-per-token API key). 4. **Intermediate High-Speed Worker Slot:** [ EMPTY / NEED SUGGESTION ] (Needs a model or setup that can execute rapid, high-speed scripts, formatting fixes, and low-tier execution loops). --- ### 🎯 What I Need From You: Based on my assets ($20 cash, Google AI Pro, and OpenCode Go) and the structure above, please help me optimize and fill in the missing pieces of this framework: 1. **Fill the Slots:** Suggest the absolute best models to fill Slot 3 (High-Volume Context) and Slot 4 (Intermediate High-Speed) using *only* my current assets or a smart recommendation for that $20 cash budget. 2. **The Jev Routing Logic:** Write a Python conditional logic pseudo-function demonstrating how Jev should efficiently route code tasks across these nodes based on file size, complexity, and our flat-rate/subscription constraints. 3. **Failure Escalation Path:** How should Jev handle it when a cheaper model fails a linting check or hits a loop? Show the exact escalation path back up to the Claude Opus 5.5 Orchestrator. 4. **Ecosystem & Tool Integration:** What is the cleanest developer harness or extension framework (e.g., Cline, Aider, OpenHands) to run this exact multi-model configuration using browser-session tokens or flat-rate bundles instead of raw API billing?