Control Tower Blueprint: From AI Chaos to Factory
Published: July 20, 2024 (retrospective)
By mid-2024 I was juggling Claude, Copilot, Perplexity, and local Ollama instances simultaneously. Great results—but token burn, context loss, and manual coordination killed efficiency. Control Tower v1.0 was my answer: a GitHub-orchestrated system that turned ideas into production code with minimal human input.
The Workflow
Idea → GitHub Issue → Claude researches
→ Copilot codes → I approve PR → deployed
Key design decisions:
– Priority + budget fields on every issue halt overspend automatically
– Human gate on every PR—AI proposes, I approve
– Nightly decision cycle—agents run overnight, I review at breakfast
The Numbers
| Metric | Before Control Tower | After | Gain |
|---|---|---|---|
| Code hours/week | 20h | 4h | 80% reduction |
| Token cost/week | £120 | £12 | 90% reduction |
| Projects shipped/month | 1 | 4 | 4x |
| GitHub commits/month | 45 | 200+ | 4.4x |
What Made It Work
- Local-first routing: Proxmox + Ollama handled 70% of queries free.
- Scoped permissions: AI never had write access without explicit approval.
- Repo as truth: Every decision documented in GitHub—zero tribal knowledge.
Control Tower didn’t just code; it scaled my fractional CISO practice and laid the foundation for SentinelForge.
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Next: CrewAI launch transforms agent security (Oct 2024).
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