Jujutsu VCS Integration: PoC Plan

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Jujutsu VCS Integration Proof of Concept Plan

🚀 Executive Summary

Goal: Guys, let's figure out if Jujutsu VCS integration can actually make things better for our Agentic QE Fleet before we jump in headfirst.

Approach: We're going to use evidence, manage risks, and take things one step at a time. Timeline: 2 weeks for the PoC, then a decision point. If it's a go, we're looking at a 12-week full implementation. Budget: 80 hours (one engineer for two weeks).

📊 Baseline Metrics (Current System)

System State (as of 2025-11-15)

  • Total Test Files: 1,256
  • QE Agents: 102 agent definitions
  • Monthly Commits: 142 commits (last 30 days)
  • Version Control: Git (the usual)
  • No VCS abstraction layer
  • No concurrent agent workspace isolation

Current Pain Points (TO BE VALIDATED)

  • ❓ Agent workspace conflicts (how often?)
  • ❓ Git staging overhead (how long does it take?)
  • ❓ Concurrent execution bottlenecks (do they even happen?)
  • ❓ Conflict resolution time (what's the baseline? We need to know!)

IMPORTANT: We absolutely need to measure these things before we can say anything is better.

🎯 Phase 1: Proof of Concept (2 Weeks)

Week 1: Installation & Validation

Day 1-2: Environment Setup

Goal: Get Jujutsu working in our world.

Tasks:

[ ] Install Jujutsu via package manager
[ ] Test basic jj commands in DevPod
[ ] Install agentic-jujutsu crate
[ ] Verify WASM bindings compile
[ ] Test basic WASM operations

Success Criteria:

  • ✅ Jujutsu CLI works in DevPod
  • ✅ WASM bindings compile without errors
  • ✅ Can create/commit/query changes via WASM

Failure Exit: If the WASM bindings don't work, we stop, document the problems, and report what we found.

Day 3-5: Performance Baseline

Goal: Compare how fast Git is versus Jujutsu.

Benchmark Tests:

// Test 1: Create workspace
measure(() => git.clone(repo))
measure(() => jj.init(repo))

// Test 2: Commit changes
measure(() => {
  git.add('.');
  git.commit('message');
})
measure(() => {
  jj.commit('message'); // Auto-staging
})

// Test 3: Concurrent operations
measure(() => {
  // 3 agents editing simultaneously
  git.branch('agent-1'); git.checkout('agent-1');
  git.branch('agent-2'); git.checkout('agent-2');
  git.branch('agent-3'); git.checkout('agent-3');
})
measure(() => {
  // 3 Jujutsu workspaces
  jj.workspace.create('agent-1');
  jj.workspace.create('agent-2');
  jj.workspace.create('agent-3');
})

// Test 4: Conflict scenarios
// Create intentional conflicts, measure resolution time

Deliverable: A performance report with REAL numbers.

Example Output:

## Performance Benchmark Results

| Operation         | Git (ms) | Jujutsu (ms) | Improvement | 
| ----------------- | -------- | ------------ | ----------- | 
| Create workspace  | 450ms    | 120ms        | 3.75x faster | 
| Commit changes    | 85ms     | 15ms         | 5.67x faster | 
| 3 concurrent workspaces | 1,200ms  | 180ms        | 6.67x faster | 
| Resolve conflict (auto) | N/A      | 450ms        | New capability | 

**Overall**: 4-7x performance improvement in tested scenarios
**Caveat**: Tested on DevPod with sample repo (50MB)

Week 2: Integration Prototype

Day 6-8: Minimal VCS Adapter

Goal: Build the simplest abstraction layer possible.

Code:

// /src/vcs/base-adapter.ts
interface VCSAdapter {
  commit(message: string): Promise<void>;
  createWorkspace(name: string): Promise<Workspace>;
  getCurrentChanges(): Promise<Change[]>;
}

// /src/vcs/jujutsu-adapter.ts
class JujutsuAdapter implements VCSAdapter {
  // Minimal implementation using agentic-jujutsu
}

// /src/vcs/git-adapter.ts
class GitAdapter implements VCSAdapter {
  // Wrapper around existing Git calls
}

Success Criteria:

  • ✅ Both adapters implement the same interface.
  • ✅ Tests pass for both implementations.
  • ✅ Can swap adapters via config.

Day 9-10: Single Agent Integration

Goal: Test with ONE agent (qe-test-generator).

Integration:

// Modify qe-test-generator to use VCS adapter
const adapter = VCSAdapterFactory.create(); // Auto-detect
await adapter.createWorkspace('test-gen-workspace');
await generateTests();
await adapter.commit('Generated tests for UserService');

Test Scenarios:

  1. Generate tests with Git adapter → measure time.
  2. Generate tests with Jujutsu adapter → measure time.
  3. Run 3 concurrent test generations → measure conflicts.

Success Criteria:

  • ✅ Agent works with both adapters.
  • ✅ Jujutsu shows measurable performance improvement.
  • ✅ No breaking changes to the existing workflow.

📈 Success Metrics (Evidence-Based)

Minimum Viable Success (PoC)

We need these to move to Phase 2:

Metric Target Measurement
WASM Bindings Work 100% Can execute jj commands via WASM
Performance Improvement ≥2x Benchmarked commit/workspace operations
No Breaking Changes 0 Existing tests still pass
Single Agent Integration Works qe-test-generator uses adapter

Decision Rule:

  • ✅ ALL metrics met → Proceed to Phase 2 (full implementation).
  • ⚠️ Performance <2x → Re-evaluate: Is it worth it?
  • ❌ WASM doesn't work → Stop, document, and close the issue.

Stretch Goals (Nice to Have)

  • Concurrent workspace isolation working.
  • Auto-commit reducing overhead by >50%.
  • Conflict detection API functional.

⚠️ Risk Assessment (Data-Driven)

Risk Matrix

Risk Probability Impact Mitigation
WASM bindings fail in DevPod Medium High Test in Week 1 Day 1, exit early if fails
Performance <2x improvement Medium Medium Measure in Week 1, decide if worth continuing
Jujutsu API changes (pre-1.0) High Medium Pin version, document API used
Integration complexity Low Low Start with 1 agent, keep it simple
Team learning curve Low Low Optional feature, comprehensive docs

Mitigation Strategies

Technical Risks:

  • Pin agentic-jujutsu version in package.json.
  • Feature flag to disable if issues arise.
  • Git fallback always available.
  • Minimal changes to existing code.

Adoption Risks:

  • Make it opt-in via .aqe-ci.yml.
  • Document both Git and Jujutsu workflows.
  • Internal dogfooding before external release.

📋 Deliverables (Evidence Required)

Week 1 Deliverables

[ ] Installation report (works/doesn't work)
[ ] Performance benchmarks (with real numbers)
[ ] WASM compatibility report
[ ] Go/No-Go decision document

Week 2 Deliverables

[ ] VCS adapter code (base + 2 implementations)
[ ] Single agent integration (qe-test-generator)
[ ] Test results (adapter tests + integration tests)
[ ] Final recommendation report

Final PoC Report Template

## Jujutsu VCS PoC - Final Report

### Executive Summary

*   PoC Goal: Validate Jujutsu performance and feasibility
*   Outcome: [Success / Partial Success / Failure]
*   Recommendation: [Proceed / Revisit / Abandon]

### Measured Results

| Claim                  | Actual Result | Evidence                     | 
| ---------------------- | ------------- | ---------------------------- | 
| "23x faster"          | X.Xx faster   | Benchmark: tests/vcs-benchmark.ts | 
| "95% conflict reduction" | Not tested    | N/A                          | 
| "WASM works in DevPod" | [Yes/No]      | Installation log             | 

### Blockers Encountered

1.  [Issue description + resolution/workaround]

### Lessons Learned

1.  [What worked well]
2.  [What didn't work]
3.  [Unexpected findings]

### Recommendation

[Detailed reasoning for proceed/stop decision]

### Next Steps (if proceeding)

[Specific actions for Phase 2]

🚀 Phase 2: Full Implementation (IF PoC Succeeds)

Timeline: 12 weeks (not 4 weeks - a realistic estimate). Scope: Extend to all 18 QE agents.

Week 3-6: Adapter Layer (4 weeks)

  • Complete VCS abstraction layer.
  • Implement all operations (commit, merge, rebase, log).
  • Add operation logging to AgentDB.
  • 90%+ test coverage.
  • Documentation.

Week 7-10: Agent Integration (4 weeks)

  • Extend to all 18 QE agents (1-2 agents/week).
  • Add workspace isolation per agent.
  • Implement concurrent execution tests.
  • Performance validation across all agents.

Week 11-12: Configuration & Rollout (2 weeks)

  • Add .aqe-ci.yml VCS configuration.
  • Feature flags for gradual rollout.
  • Documentation (setup, migration, troubleshooting).
  • Internal dogfooding.
  • Beta release announcement.

Week 13-14: Monitoring & Iteration (2 weeks)

  • Monitor production usage.
  • Collect feedback.
  • Fix bugs.
  • Performance tuning.
  • Case study documentation.

Total: 14 weeks (PoC + Implementation)

💰 Cost-Benefit Analysis

Investment

  • PoC: 80 hours (2 weeks × 1 engineer)
  • Full Implementation (if approved): 480 hours (12 weeks × 1 engineer)
  • Total: 560 hours

Expected Benefits (IF claims are validated)

Measured after PoC:

  • Performance improvement: X.Xx faster (TBD).
  • Workspace isolation: Yes/No (TBD).
  • Auto-commit savings: Y% overhead reduction (TBD).

Theoretical benefits (cannot validate until full implementation):

  • Conflict reduction: Unknown (requires AI conflict resolution).
  • Cost savings: Unknown (requires learning system).
  • Audit trail: Yes (Jujutsu operation log exists).

Break-Even Analysis

If PoC shows 2x improvement:

  • Time saved per pipeline: ~5 seconds (estimated).
  • Pipelines per day: ~20 (estimated).
  • Time saved per day: 100 seconds = 1.67 minutes.
  • Time saved per week: 8.35 minutes.
  • Break-even: ~670 weeks (12+ years).

If PoC shows 5x improvement:

  • Time saved per pipeline: ~15 seconds.
  • Break-even: ~250 weeks (5 years).

If PoC shows 10x improvement:

  • Time saved per pipeline: ~35 seconds.
  • Break-even: ~110 weeks (2 years).

Conclusion: This is a long-term investment, not a quick win.

🎯 Decision Framework

After Week 1 (Go/No-Go Decision Point)

Proceed to Week 2 if:

  • ✅ WASM bindings work in DevPod.
  • ✅ Performance improvement ≥2x.
  • ✅ No major blockers discovered.

Stop if:

  • ❌ WASM bindings don't work.
  • ❌ Performance <1.5x (marginal gain, high effort).
  • ❌ Major blocker (API instability, compatibility).

After Week 2 (Full Implementation Decision)

Proceed to Phase 2 if:

  • ✅ PoC fully successful (all success criteria met).
  • ✅ Performance improvement ≥4x (justifies 12-week investment).
  • ✅ Single agent integration works flawlessly.
  • ✅ Team capacity available (1 engineer for 12 weeks).

Defer if:

  • ⚠️ Performance 2-4x (good but not great).
  • ⚠️ Higher priority features exist.
  • ⚠️ Team capacity constrained.

Abandon if:

  • ❌ PoC failed to meet minimum criteria.
  • ❌ Performance <2x.
  • ❌ Integration too complex.

📚 Research & References

Jujutsu VCS

agentic-jujutsu

Comparison with Original Proposal (Issue #47)

Aspect Original Claim This Plan
Timeline 4 weeks 2 weeks PoC + 12 weeks implementation
Performance "23x faster" Measure in PoC, don't promise
Scope 18 agents + AI + learning 1 agent in PoC, expand if successful
Success criteria Vague ("learning improves") Measurable (≥2x perf, WASM works)
Risk assessment Underestimated Realistic with exit points

🚦 Next Steps

Immediate (This Week)

  1. Review this plan with stakeholders.
  2. Approve 2-week PoC budget (80 hours).
  3. Assign engineer to PoC work.
  4. Set up tracking (PoC kanban board).

Week 1 PoC Kickoff

  1. Install Jujutsu in DevPod.
  2. Test WASM bindings.
  3. Run performance benchmarks.
  4. Document findings.

Decision Points

  • End of Week 1: Go/No-Go for Week 2
  • End of Week 2: Proceed/Defer/Abandon Phase 2

📞 Contact & Questions

PoC Lead: TBD Stakeholders: Product, Engineering, QE Escalation: If blockers arise, escalate immediately (don't wait 2 weeks).

Created: 2025-11-15 Status: Awaiting Approval Next Review: End of Week 1 (PoC)