CODITECT Development Studio - Implementation Roadmap v2.0
Version: 2.0.0
Date: 2026-01-31
Status: Draft
Estimated Duration: 14 weeks
Team Size: 8 engineers
1. Executive Summary
This roadmap details the implementation of CODITECT Development Studio v2.0, featuring unified persistent workspaces with multi-agent coordination. The architecture shifts from 4 ephemeral sandboxes to 1 persistent container with SQLite clustering and GCS FUSE storage.
Key Milestones
| Milestone | Date | Deliverable |
|---|
| M0: Foundation | Week 4 | GCS FUSE, SQLite cluster, basic workspace |
| M1: Agents | Week 7 | In-workspace orchestrator, 4 agent adapters |
| M2: Frontend | Week 9 | Multi-agent UI, agent activity panel |
| M3: Migration | Week 11 | v1.0 → v2.0 data migration |
| M4: GA | Week 14 | Production launch, optimization |
2. Phase Breakdown
Phase 1: Foundation (Weeks 1-4)
Goal: Core infrastructure for persistent workspaces
Week 1: Infrastructure & Storage
| Task | Owner | Deliverable |
|---|
| Set up GCS buckets | DevOps | coditect-workspaces bucket with lifecycle policies |
| Configure GCS FUSE | Platform | Working FUSE mount in test container |
| Terraform modules | DevOps | IaC for GCS, IAM, networking |
| R2 mirror setup | Platform | Cross-region hot cache |
Success Criteria:
- GCS FUSE mount: < 50ms read latency
- R2 mirror: 80% cache hit rate
- Terraform:
terraform apply creates full stack
Week 2: SQLite Cluster
| Task | Owner | Deliverable |
|---|
| SQLite initialization | Backend | 6-database schema creation |
| WAL mode configuration | Backend | WAL + checkpoint tuning |
| GCS sync daemon | Backend | 30s WAL sync to GCS |
| Connection pooling | Backend | 10-connection pool per DB |
Success Criteria:
- SQLite write: < 10ms
- GCS sync: Zero data loss on crash
- Concurrent connections: 10 without contention
Week 3: Workspace Container
| Task | Owner | Deliverable |
|---|
| Container image | Platform | coditect/workspace:v2.0 base image |
| Init scripts | Platform | Database initialization on startup |
| Health checks | Platform | /health endpoint with DB connectivity |
| Resource limits | Platform | 2 vCPU, 4GB RAM constraints |
Success Criteria:
- Container startup: < 30s
- Health check: Pass with all DBs connected
- Resource usage: Within limits under load
Week 4: Worker Integration
| Task | Owner | Deliverable |
|---|
| Workspace registry DO | Backend | Durable Object for workspace lifecycle |
| Provision API | Backend | /workspaces/provision endpoint |
| WebSocket gateway | Backend | Connection to workspace containers |
| Integration tests | QA | End-to-end workspace lifecycle |
Phase 1 Success Criteria:
- Workspace provision: < 30s
- SQLite cluster: 6 databases, WAL mode
- GCS FUSE: Files persist across restarts
- Zero data loss on container restart
Phase 2: Agent Orchestrator (Weeks 5-7)
Goal: In-workspace multi-agent coordination
Week 5: Agent Framework
| Task | Owner | Deliverable |
|---|
| Base agent class | Backend | Abstract agent with lifecycle |
| Agent state machine | Backend | idle → loading → executing → waiting |
| Task queue | Backend | Priority queue per agent |
| Message bus | Backend | Pub/sub between agents |
Success Criteria:
- Agent state transitions: Reliable
- Task queue: FIFO with priority
- Message latency: < 10ms
Week 6: Agent Adapters
| Task | Owner | Deliverable |
|---|
| Claude adapter | Backend | Anthropic SDK integration |
| Gemini adapter | Backend | Google AI SDK integration |
| Codex adapter | Backend | OpenAI SDK integration |
| Kimi adapter | Backend | Moonshot SDK integration |
Success Criteria:
- All 4 agents: Execute tasks end-to-end
- Token tracking: Accurate per-agent
- Error handling: Graceful degradation
Week 7: Coordination & Locks
| Task | Owner | Deliverable |
|---|
| File lock manager | Backend | Read/write lock implementation |
| Conflict resolution | Backend | Lock timeout and escalation |
| Shared context | Backend | Common codebase view |
| Agent metrics | Backend | Track tasks, latency, errors |
Phase 2 Success Criteria:
- 4 agents coexist: In same workspace
- File locks: Prevent concurrent edits
- Lock acquisition: < 100ms
- Agent failover: Auto-restart on crash
Phase 3: Frontend (Weeks 8-9)
Goal: Multi-agent user interface
Week 8: Core UI
| Task | Owner | Frontend |
|---|
| Workspace connection | Frontend | WebSocket to workspace |
| Agent activity panel | Frontend | Real-time status of 4 agents |
| File tree with locks | Frontend | Lock icons + agent names |
| SQLite query interface | Frontend | SQL editor for databases |
Success Criteria:
- WebSocket: < 100ms message latency
- Agent status: Real-time updates
- File locks: Visual indicators
Week 9: Advanced Features
| Task | Owner | Frontend |
|---|
| Session timeline | Frontend | Replay from SQLite + JSONL |
| Agent chat targeting | Frontend | Send to specific agent |
| Task queue viewer | Frontend | See queued and running tasks |
| Cost dashboard | Frontend | Real-time workspace cost |
Phase 3 Success Criteria:
- Session replay: < 1s seek time
- Agent targeting: Works correctly
- Cost tracking: Within 5% of actual
Phase 4: Migration (Weeks 10-11)
Goal: Zero-downtime v1.0 → v2.0 migration
| Task | Owner | Deliverable |
|---|
| Data export | Platform | v1.0 session → GCS |
| Schema migration | Backend | Convert R2 data to SQLite |
| Session log conversion | Backend | Logs → JSONL format |
| Dry-run testing | QA | Test migration on staging |
Week 11: Cutover
| Task | Owner | Deliverable |
|---|
| Blue-green deployment | DevOps | Parallel v1/v2 stacks |
| Traffic shifting | DevOps | Gradual cutover |
| Rollback plan | DevOps | Instant rollback capability |
| Monitoring | DevOps | Alert on migration issues |
Phase 4 Success Criteria:
- Zero data loss: 100% integrity
- Downtime: < 5 minutes
- Rollback time: < 10 minutes
Phase 5: Optimization (Weeks 12-14)
Goal: Production hardening and cost optimization
| Task | Owner | Target |
|---|
| GCS FUSE tuning | Platform | < 20ms read latency |
| SQLite optimization | Backend | Query optimization, indexing |
| Connection pooling | Backend | Reduce DB connection overhead |
| CDN optimization | Platform | Cache static assets |
Week 13: Cost Optimization
| Task | Owner | Target |
|---|
| Auto-sleep tuning | Platform | 70% cost reduction off-peak |
| GCS lifecycle | Platform | Auto-archive to Nearline |
| R2 cache efficiency | Platform | 85% hit rate |
| Resource right-sizing | Platform | Match quotas to usage |
Week 14: GA Preparation
| Task | Owner | Deliverable |
|---|
| Load testing | QA | 10K concurrent workspaces |
| Security audit | Security | Penetration test, review |
| Documentation | Docs | API docs, runbooks |
| Launch checklist | PM | Go/no-go decision |
Phase 5 Success Criteria:
- Load test: Pass at 10K users
- Cost target: <$7/user @ 1K users
- Security: Zero critical findings
- Availability: 99.9% uptime
3. Team Structure
| Role | Count | Responsibilities |
|---|
| Platform Lead | 1 | Infrastructure, GCS, containers |
| Backend Engineers | 3 | SQLite, agents, API, workers |
| Frontend Engineers | 2 | React, WebSocket, visualization |
| DevOps Engineer | 1 | Terraform, CI/CD, monitoring |
| QA Engineer | 1 | Testing, load testing, automation |
4. Dependencies & Risks
Critical Dependencies
| Dependency | Status | Mitigation |
|---|
| GCS FUSE stability | Risk | Test extensively, have GKE backup |
| SQLite WAL performance | Risk | Benchmark early, tune checkpointing |
| Cloudflare Containers GA | Dependency | Use GKE Autopilot if delayed |
| Anthropic API rate limits | External | Implement aggressive caching |
Risk Register
| Risk | Probability | Impact | Mitigation |
|---|
| GCS latency too high | Medium | High | R2 hot mirror, local caching |
| SQLite corruption | Low | Critical | WAL + GCS sync, automated backups |
| Cost overrun | Medium | Medium | Auto-sleep, aggressive optimization |
| Migration data loss | Low | Critical | Extensive testing, rollback plan |
| Agent contention | Medium | Medium | Resource limits, monitoring |
5. Success Metrics
Technical Metrics
| Metric | Target | Measurement |
|---|
| Workspace startup | < 30s | Provision API response time |
| Workspace reconnect | < 1s | WebSocket connection time |
| Agent task start | < 500ms | Queue to execution |
| File lock acquisition | < 100ms | Lock granted time |
| SQLite query | < 50ms | Simple SELECT |
| GCS read (cached) | < 20ms | FUSE read |
| Availability | 99.9% | Uptime excluding maintenance |
Business Metrics
| Metric | Target | Measurement |
|---|
| Cost per user @ 1K | <$7/month | Infrastructure spend |
| Migration downtime | < 5 min | Cutover window |
| Data durability | 99.999% | Zero unrecoverable losses |
| User satisfaction | > 4.0/5 | Post-launch survey |
6. Budget Estimate
Infrastructure Costs (Monthly @ 1K Users)
| Component | v1.0 Cost | v2.0 Cost | Change |
|---|
| Compute | $1,200 | $4,200 | +250% |
| Storage (GCS) | $200 | $1,460 | +630% |
| Storage (R2) | $150 | $355 | +137% |
| Database | $0 | $0 | - |
| Network | $300 | $500 | +67% |
| LLM APIs | $300 | $323 | +8% |
| Observability | $150 | $1,800 | +1100% |
| Other | $900 | $862 | -4% |
| TOTAL | $3,200 | $9,500 | +197% |
Note: v2.0 target is $6,500 after optimizations (Phase 5)
Team Costs (14 weeks)
| Role | Rate | Hours | Cost |
|---|
| 8 Engineers | $150/hr | 4,480 | $672,000 |
| Infrastructure | - | - | $35,000 |
| TOTAL | | | $707,000 |
7. Appendices
A. Technology Choices
| Component | Choice | Rationale |
|---|
| Container Platform | Cloudflare Containers | Edge deployment, low latency |
| Alternative | GKE Autopilot | Fallback if CF delayed |
| Storage | GCS + FUSE | POSIX compatibility, durability |
| Cache | R2 | Cloudflare edge, cost-effective |
| Database | SQLite | Single-node, zero config, fast |
| Archive | JSONL | Human-readable, streamable |
B. Document References
Status: Draft - Ready for review
Next Steps: Architecture review, team assignment, Week 1 kickoff