Running 3 Parallel Claude Code Instances to Get $200 of Dev Work for $20/month Overview I build Jibun Kabushiki Kaisha — a 200-page Flutter Web SaaS — using Claude Code. On a $20/month plan, I run 3 specialized Claude Code instances in parallel to achieve roughly 10x the development throughput. Each instance has a fixed responsibility: Instance Dedicated Role Why VSCode UI/design compliance (haiku-4.5) Fast, cheap, visual tasks PowerShell CI/CD health + blog publishing Quality-critical, pipeline focus Windows App AI University providers + migrations Data-heavy, structured work Without coordination, all 3 instances push simultaneously: PS push → deploy starts VSCode push (5s later) → deploy CANCELLED → restart Win push (3s later) → deploy CANCELLED → restart → 20+ minutes later: finally 1 successful deploy This "deploy thrashing" wastes CI minutes and breaks each other's work. Instead of direct communication, instances leave work requests in docs/cross-instance-prs/: # docs/cross-instance-prs/20260419_trailing_comma_fix.md ## Target: PowerShell instance ## Task: Fix require_trailing_commas 36 errors ## Reason: PS instance owns CI/CD health (Rule17) VSCode finds a lint issue → records it in cross-instance-pr → PS instance picks it up next session. # Check at session start git log origin/main --oneline -10 # Look for interleaved commits from multiple instances: # 88e37a2 Merge (conflict resolution) # f2520c6 (PS#136) # c66830d (VSCode#104) # badccf5 (PS#135) # → Multiple instances active → watch for ROADMAP merge conflicts On $20/month across 3 instances, every token matters. A custom Claude Code plugin that compresses responses ~75%: ❌ Standard: "I'll be happy to analyze the current CI failures and provide a comprehensive fix. Let me first examine..." ✅ CAVEMAN mode: "2276 lint errors. dart fix --apply → format → 0 errors. push." Task Claude cost After NotebookLM Read 3+ files simultaneously ~150K tokens ~5K tokens Analyze a URL ~60K tokens ~2K tokens Competitor research ~80K tokens ~3K tokens Each instance only loads context relevant to its specialty. The VSCode instance doesn't need to know migration history. The PS instance doesn't need design system knowledge. 09:00 JST - PS: CI health check + blog dispatch 11:00 JST - VSCode: UI improvements + design token compliance 14:00 JST - Win: Add AI University providers 16:00 JST - PS: Confirm deploy + write more blog posts 18:00 JST - Win: Migrations + EF cleanup At each session start: git log origin/main -5 to see what other instances committed. Throughput: 3 parallel workstreams from 1 person Cost: ~$20/month for ~$200 equivalent work Quality: Each domain improves independently without cross-contamination The $20/month constraint doesn't limit what you can build — it forces you to think about where each token should go. Specialization turns a limitation into a feature: each instance is expert at its domain precisely because it never gets distracted by others. Building in public: https://my-web-app-b67f4.web.app/ ClaudeCode #buildinpublic #AI #productivity