diff --git a/conductor/tracks/mma_implementation_20260224/proposal.md b/conductor/tracks/mma_implementation_20260224/proposal.md
index a04b4fd..b0a1d91 100644
--- a/conductor/tracks/mma_implementation_20260224/proposal.md
+++ b/conductor/tracks/mma_implementation_20260224/proposal.md
@@ -1,7 +1,7 @@
 # Conductor Self-Reflection & Upgrade Strategy Proposal
 
 ## 1. Executive Summary
-*To be drafted.*
+This proposal outlines a strategic path for upgrading the Gemini CLI `conductor` extension to fully embrace the 4-Tier Hierarchical Multi-Model Architecture principles. By migrating from a monolithic, context-heavy single-agent loop to a compartmentalized, multi-model delegation system, Conductor can drastically reduce token burn, mitigate hallucination loops, and grant developers surgical Human-In-The-Loop (HITL) control over execution tasks.
 
 ## 2. Memory Siloing & Token Firewalling
 
@@ -26,7 +26,15 @@ To enforce precise developer control, Conductor should natively embed a **Human-
 3. **Rollback Mutators:** Provide quick access commands (e.g., via `after_tool_call`) to reject the change, auto-restoring the last known file state, and feeding the error/feedback directly back to the model without breaking the run loop.
 
 ## 4. Multi-Model/Sub-Agent Delegation
-*To be drafted. Focus: Evaluating reliance on single models and proposing a design for delegating tasks via Gemini CLI Sub-agents and Skills.*
+
+### Current Evaluation
+Conductor heavily relies on the single primary LLM instantiated by the Gemini CLI session. When acting as a PM, Tech Lead, and Worker simultaneously, the model experiences extreme context exhaustion. Furthermore, handling minor formatting, syntax repairs, or summaries with expensive high-tier reasoning models results in suboptimal cost-efficiency.
+
+### Proposed Upgrade Strategy
+Conductor should leverage the native **Sub-Agent & Skill Routing capabilities**:
+1. **Dynamic Tier Routing:** Utilize specific Sub-agents (like `codebase_investigator` for planning/AST generation) and custom Skills for discrete tasks.
+2. **Stateless Utility Agents (Tier 4):** Hook into test runner commands via `after_tool_call`. If `pytest` fails with massive `stderr`, immediately invoke a cheap background utility sub-agent to parse the log and return a condensed 20-word summary back to the main Orchestrator, rather than feeding the main Orchestrator raw traceback tokens.
+3. **Contract Stubbers:** Embed `contract_stubber` skills that explicitly limit a sub-agent's action strictly to writing `class` or `def` definitions, ensuring cross-module dependency generation without full implementation drift.
 
 ## 5. Implementation Strategy
-*To be drafted. Focus: Alignment with 4-Tier Architecture philosophy and leveraging Gemini CLI's extension framework (manifests, hooks, sub-agents).*
+These upgrades can be realized by augmenting the `gemini-extension.json` manifest with designated MCP hooks, adding new custom Skills to `~/.gemini/skills/`, and overriding default CLI execution flows with `before_tool_call` and `after_tool_call` interception logic tailored explicitly for Token Firewalling and Execution Checkpoints.
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