156 lines
5.7 KiB
JavaScript
156 lines
5.7 KiB
JavaScript
"use client"
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// Run this in Mission Control Documents page console to add the Voxyz research
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// Or save this as a document manually
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const document = {
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id: Date.now().toString(),
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title: "I Built an AI Company with OpenClaw + Vercel + Supabase — Two Weeks Later, They Run It Themselves",
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date: "2026-02-22",
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content: `# I Built an AI Company with OpenClaw + Vercel + Supabase — Two Weeks Later, They Run It Themselves
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**URL:** https://x.com/Voxyz_ai/status/2019914775061270747
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**Source:** X (Twitter) / Vox (@Voxyz_ai)
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**Date Researched:** 2026-02-22
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**Tags:** #ai #agents #openclaw #automation #vercel #supabase #voxyz #closed-loop
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---
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## Summary
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Vox built a **6-agent autonomous company** using OpenClaw + Vercel + Supabase that runs itself with minimal human intervention. After just two weeks, the system operates autonomously with agents proposing ideas, executing missions, and triggering reactions without direct oversight.
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The article details the architecture, three major pitfalls encountered, and solutions that created a truly "closed loop" system where agents don't just talk—they execute end-to-end.
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## Key Takeaways
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### The 6 Agents
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- **Minion** — Makes decisions
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- **Sage** — Analyzes strategy
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- **Scout** — Gathers intel
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- **Quill** — Writes content
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- **Xalt** — Manages social media
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- **Observer** — Quality checks
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### The Closed Loop Architecture
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\`\`\`
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Agent proposes idea → Auto-approval check → Create mission + steps
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↑ ↓
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Trigger/Reaction ← Event emitted ← Worker executes
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\`\`\`
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### 3 Pitfalls & Solutions
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**Pitfall 1: Two Places Fighting Over Work**
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- Problem: VPS workers + Vercel cron both claiming same tasks (race conditions)
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- Fix: VPS is sole executor; Vercel only runs control plane (triggers, reactions, cleanup)
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**Pitfall 2: Triggered But Nobody Picked It Up**
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- Problem: Triggers created proposals but skipped auto-approve + mission creation
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- Fix: Single \`createProposalAndMaybeAutoApprove()\` function—ALL paths must use it
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**Pitfall 3: Queue Keeps Growing When Quota Is Full**
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- Problem: Tweet quota full, but proposals kept generating queued steps
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- Fix: **Cap Gates** — reject at proposal entry point, don't let queue build up
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### Key Innovations
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**1. Cap Gates System**
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\`\`\`typescript
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const STEP_KIND_GATES = {
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write_content: checkWriteContentGate,
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post_tweet: checkPostTweetGate, // Check tweet quota
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deploy: checkDeployGate,
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};
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\`\`\`
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Reject at entry → No queue buildup → Clear audit trail
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**2. Reaction Matrix (30% Probability)**
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\`\`\`json
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{
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"source": "twitter-alt",
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"tags": ["tweet","posted"],
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"target": "growth",
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"type": "analyze",
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"probability": 0.3,
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"cooldown": 120
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}
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\`\`\`
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30% chance = "feels like a real team" (not 100% robot determinism)
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**3. Self-Healing (30-min Stale Detection)**
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- Steps stuck in "running" for 30 min → auto-mark failed
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- Mission finalization checks ALL steps (not just one success)
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**4. Policy-Driven Configuration**
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All behavior in \`ops_policy\` table—no hardcoded limits:
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- \`auto_approve\`: Which step kinds auto-pass
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- \`x_daily_quota\`: Daily tweet cap
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- \`worker_policy\`: VPS vs Vercel execution
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### Database Schema (For Reference)
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- \`ops_mission_proposals\` — Pending/accepted/rejected proposals
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- \`ops_missions\` — Mission state (approved/running/succeeded/failed)
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- \`ops_mission_steps\` — Execution steps (queued/running/succeeded/failed)
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- \`ops_agent_events\` — Event stream
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- \`ops_policy\` — Behavior configuration (JSON)
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- \`ops_trigger_rules\` — Trigger definitions
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- \`ops_agent_reactions\` — Reaction queue
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- \`ops_action_runs\` — Execution logs
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### Architecture Layers
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- **OpenClaw (VPS):** Think + Execute (brain + hands)
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- **Vercel:** Approve + Monitor (control plane)
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- **Supabase:** All state (shared cortex)
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## Notable Quotes
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> "6 AI agents, 1 VPS, 1 Supabase database — going from 'agents can talk' to 'agents run the website autonomously' took me two weeks."
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> "probability isn't a bug, it's a feature. 100% determinism = robot. Add randomness = feels more like a real team where 'sometimes someone responds, sometimes they don't.'"
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> "Reject at the gate, don't pile up in the queue."
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> "Between 'agents can produce output' and 'agents can run things end-to-end,' there's a full execute → feedback → re-trigger loop missing."
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## Timeline
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- **Infrastructure:** Pre-existing (OpenClaw + Vercel + Supabase)
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- **Proposals + Approval:** 3 days
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- **Execution Engine:** 2 days
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- **Triggers + Reactions:** 2 days
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- **Loop Unification:** 1 day
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- **Total Core Loop:** ~1 week
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## Related
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- **Next Article:** How agents "argue" and "persuade" each other (roundtable voting, team cognition)
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- **Live System:** https://voxyz.space
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- **Author:** [@Voxyz_ai](https://x.com/Voxyz_ai)
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## Action Items
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- [ ] Study Cap Gates implementation for Mission Control Phase 10
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- [ ] Design Proposal Service architecture
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- [ ] Plan Reaction Matrix for Daily Mission generation
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- [ ] Research OpenClaw roundtable voting patterns
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- [ ] Follow @Voxyz_ai for next article on agent persuasion
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## Application to Mission Control
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**Short-term:** Complete Phases 6-9 as read-only dashboard
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**Medium-term (Phase 10):** Daily Mission Generation
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- Auto-propose 3 priorities each morning
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- Simple closed loop: Analyze → Propose → Approve
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**Long-term (Phase 11-13):** Full Autonomous Operations
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- Voxyz-style proposal → execute → trigger loop
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- Self-healing system
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- Agents run, you monitor`,
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timestamp: Date.now(),
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tags: ["research", "ai", "agents", "openclaw", "voxyz", "automation"]
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}
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// To add this document:
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// 1. Open Mission Control: https://mission-control-rho-pink.vercel.app/documents
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// 2. Open browser console (F12)
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// 3. Paste this object as a new document
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// 4. Or manually create document and paste the content above
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