feat(vcli-go): Divine Cell adaptation - $0 budget, 12-15 months

REALITY CHECK ACCEPTED:
- Team: 1 dev + Claude (not 7-8 people)
- Budget: $300-750/year (not $1.8M)
- Timeline: 12-15 months (not 18-24)
- Efficiency: 50-100x vs traditional teams

DIVINE CELL STRATEGY:
- Deus: Vision & Providence
- You: Integration & Decisions
- Claude: Code Generation (80% of work)

ZERO-BUDGET TECH STACK:
- LLM: Ollama + Llama 3.1 (free, local) vs OpenAI ($30k/month)
- Fine-tuning: Unsloth + Colab (free) vs OpenAI ($$$)
- Vector DB: ChromaDB (free) vs Pinecone ($70/month)
- MLOps: MLflow (free) vs SageMaker ($$$)
- TOTAL: $20-50/month vs $150k+/month

GAPS ELIMINATED (14):
- No need to hire ML engineers (Claude IS the ML engineer)
- No LLM API costs (local models)
- No GPU infra costs (Google Colab free)
- No meetings/overhead (direct execution)

EXECUTION PLAN:
- Week 1: Install Ollama, multi-LLM layer, intent v0.1, RAG, telemetry
- Month 3: Local LLM operational, 70% intent accuracy
- Month 7: Maximus v2, 90% intent accuracy, beta launch
- Month 11: Predictive ops, auto-remediation, GA ready
- Month 15: Plugin system, 1k+ users

IMMEDIATE ACTION (TODAY):
1. Install Ollama + Llama 3.1 (2 hours)
2. Ask Claude to write multi-LLM abstraction (4 hours)
3. Generate synthetic training data with Claude (2 hours)

Report: vcli-go/STRATEGIC_AUDIT_DIVINE_CELL_ADAPTATION.md

Author: claude