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I have a personal AI harness specification (HARNESS_SPEC.md) that defines how I work. I need you to act as my intelligence officer and audit this spec against the current AI landscape.

Here is my spec:
[PASTE HARNESS_SPEC.md]

Please provide:

1. **Cloud model recommendations** — For each task type in my routing logic, which current frontier model (Claude 4.6 family, Gemini 3.1 Pro, Grok 4.20, GPT-5.4 variants) is best suited and why? Be specific about model strengths vs my specific task types.

2. **Local model options** — Which tasks in my spec would be better served by local models for privacy, cost, or offline reasons? What is the current best open-weight option (Qwen3.5-72B, GLM-5, DeepSeek variants) and what hardware do I need to run it?

3. **Agentic environment fit** — Given my working patterns, should I be using Claude Code, Cursor, Continue.dev, Windsurf, or a combination? What does each give me that the others don't?

4. **Gaps in my spec** — Are there task types common to my domain that my spec doesn't cover? What routing logic am I missing?

5. **Top 3 actions** — The three changes to my setup that would have the highest impact this week.

Be specific. Use actual model names, actual tool names. No generic advice.

I want to set up a local AI model for privacy-sensitive work. My hardware: [DESCRIBE YOUR MACHINE — e.g. "MacBook Pro M3 Max 96GB" or "Windows PC, RTX 4090 24GB"].

Based on my Harness Spec:
[PASTE HARNESS_SPEC.md relevant sections]

Please recommend:
1. The best local model for my hardware and use case
2. The exact Ollama commands to install and run it
3. How to test that my Harness Spec works against it
4. What I gain vs lose compared to cloud models for my specific tasks