Antigravity × Cursor × Claude Code — A Practical 3-Tool AI Development Workflow for 2026
Combining Antigravity (agent-first), Cursor (surgical edits), and Claude Code (automation) for real-world development. Phase-by-phase tool selection, AGENTS.md as a shared contract, measured cost analysis from an indie developer running a 50M-download app business across 4 sites.
The AI IDE landscape has shifted. Gone is the era of "one tool to rule them all." In 2026, sophistication means strategic portfolio selection—choosing the right tool for each phase.
Antigravity (agent-first, 1M context, spec-driven), Cursor (VS Code fork, model flexibility, surgical edits), and Claude Code (terminal-native, parallel worktrees, deep file understanding) each excel in different domains. Using all three strategically—not as a belt-and-suspenders compromise, but as a high-performance ensemble—unlocks capabilities unattainable with any single tool.
This guide distills real-world patterns from multi-month projects into a practical, cost-justified playbook.
Chapter 1: The Three Tools Compared
Antigravity: Agent-first Architecture
Core traits:
Multi-agent system design (16 specialized agents)
1M token context window
Spec-driven development (define requirements, agents execute)
Manager View orchestrates all agents
40+ skills, 11 commands
Excels at:
Large-scale architecture — Multiple expert agents weigh in on design simultaneously
Pricing: Claude 3.5 Sonnet API ($3-5/project typical usage)
Comparison Matrix
Dimension
Antigravity
Cursor
Claude Code
Best Phase
Design, large-scale
Implementation, tweaks
Automation, CI/CD, parallel
Context Size
1M tokens
100-300k tokens
200k tokens
Execution Speed
Slow (5-15 min)
Fast (seconds–1 min)
Medium (1-3 min)
IDE Integration
Web-based
VSCode, JetBrains
CLI only
Files per Task
20-30
5-10
Precision-targeted
Model Selection
Gemini 3.1 Pro only
8+ models
Claude 3.5 Sonnet
Offline
No (Web API)
Yes (Ollama)
No (API-required)
Multi-agent
Yes (16 agents)
No (single LLM)
Partial (scripts)
Monthly Est.
¥5k-300k
¥2k-4k
¥3-5k/project
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WHAT YOU'LL LEARN
✦Monthly cost allocation that keeps the 3-tool stack at roughly ¥132k while running 4 sites and a 50M-download indie app business
✦Measured numbers that Antigravity docs do not publish: 16 agents on a 5-minute task burn ~420K tokens, with queue waits past the parallelism cap
✦Full AGENTS.md v1.3 sample used at Dolice Labs, plus the wording that stops Cursor and Claude Code from drifting outside their roles
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Show concrete code examples from existing patterns
Sanity-check design against actual implementation patterns
Phase 1: Architecture & Skeleton (Week 3-4)
Priority: 1st Antigravity, 2nd Claude Code
Build the project scaffold in parallel using Antigravity's agent parallelization.
Antigravity full throttle
Antigravity prompt:
"Specification v1.0 in hand. Build in parallel:
L1: Project Coordinator
├ L2: Backend Architect
│ Deliver: OpenAPI 3.0 spec, DB schema
│ Due: Day 2
│
├ L2: Frontend Builder
│ Deliver: Component design doc, Storybook setup
│ Due: Day 2
│
└ L2: DevOps Engineer
Deliver: Kubernetes manifests, Docker setup
Due: Day 2
After all complete, generate integration test template."
Time: 1-2 days (3 agents parallel)
Output: API spec, UI inventory, deploy config
Cost: 1 agent-day effective (3 agents paralleled → wall time 1 day)
Claude Code for IaC generation
After skeleton is set, generate cloud infrastructure.
Claude Code prompt:
"AWS Terraform config for:
- VPC, subnets, security groups
- ECS (Fargate), RDS (Postgres), ElastiCache (Redis)
- CloudFront + S3 origin
- CloudWatch + SNS monitoring
After generation, execute `terraform plan` and show diff."
Time: 30 min
Executable: Terraform apply ready
Confidence: High (IaC syntax validated)
Phase 2: Feature Implementation (Week 5-12)
Priority: 1st Cursor, 2nd Claude Code, 3rd Antigravity
This longest phase shows tool strengths most starkly.
Cursor: Main development machine
Pattern A: Existing code modification
Cursor prompt:
"In src/pages/signup.tsx, after the <form> tag, add OAuth login button.
Use component: OAuthButton (already imported)
Style: match existing buttons (Tailwind)
File: signup.tsx only"
Time: 30s–1 min
Changed lines: 3-5
Seamlessness: Perfect (Cursor infers style, dependencies automatically)
Cursor's @-mention precision prevents AI hallucination. Existing patterns are auto-inferred.
Pattern B: New module
Cursor prompt:
"New module src/services/purchaseAnalytics.ts
Function: getPurchaseStats(userId: string): Promise<PurchaseStats>
Requirements:
- Last 3 months of data
- Redis cache (1h TTL)
- Return null if user not found
- Reference: src/services/userService.ts pattern
Implement function + types."
Time: 2-3 min
Lines: 30-50
Test: Separate (Claude Code handles)
While Cursor implements, Claude Code builds test suites and CI/CD.
Claude Code prompt:
"Jest test suite for purchaseAnalytics.ts
Test cases:
1. Happy path: fetch 3 months user data
2. Cache: 2nd call hits Redis
3. Error: nonexistent user returns null
4. Resilience: Redis down → fallback to DB
After coding, run `npm test`."
Time: 3-5 min
Lines: 40-60
Coverage: 90%+
Confidence: High (automated verification)
Expand to GitHub Actions:
Claude Code prompt:
"Update .github/workflows/ci.yml for:
- npm test on push
- Coverage comment on PRs
- Auto-deploy staging after main merge
Tech: Node 20, postgres test DB, < 5min runtime"
Time: 2-3 min
Reuse: Every future release (2-3 min instead of 15)
ROI: Immediate
Antigravity: When decision-making is needed
Antigravity shines when implementation touches requirements.
Example: "Should we expand the API spec?"
Antigravity prompt:
"Current status: Backend 80% done, Frontend 60%.
Security review flagged: API response missing compliance field.
Decision needed:
A) Expand API spec + change Frontend type defs (both 1d delay)
B) Satisfy compliance via alternative approach?
AGENTS.md + Spec v1.0 as reference. What's optimal?"
Time: 3-5 min
Output: Architecture Decision Record (what + why)
Confidence: All perspectives vetted
Phase 3: Integration & QA (Week 13-14)
Priority: 1st Claude Code, 2nd Cursor, 3rd Antigravity
Claude Code: Automation backbone
Claude Code prompt:
"Playwright E2E test: user signup → login → search → purchase flow
Steps:
1. Register
2. Login
3. Search products
4. Add to cart
5. Checkout
6. Verify confirmation email
Constraints: Staging env, < 3 min, screenshots on failure
Run `npm run test:e2e` after."
Time: 10-15 min
Lines: 100-150
Trust: 95%+ (human testing supplement)
Add performance measurement:
Claude Code prompt:
"Daily Lighthouse audit (Staging env).
Metrics: LCP, FID, CLS, Performance Score
Diff from yesterday? Alert to Slack.
Store results as JSON (time-series)"
Time: 5 min
Continuous benefit: Daily visibility
Cursor: Performance optimization
Cursor prompt:
"src/components/ProductList.tsx is slow.
Implement:
1. React.memo (prevent re-render)
2. useCallback for event handlers
3. useMemo for expensive computations
Compare Lighthouse before/after."
Time: 2-3 min
Gain: LCP -0.5s, FID -30ms typical
Phase 4: Security & Compliance (Week 15)
Priority: 1st Antigravity, 2nd Claude Code
Antigravity prompt:
"Security pre-release review.
Check:
- OWASP Top 10
- Dependency vulnerabilities
- .env management
- GDPR / data protection
- Encryption (transit + at-rest)
Output: Review Report with Priority-ranked fixes"
Time: 30 min–1 hour
Output: Go/no-go gate decision
Scope: All backend, frontend, infra code
Cursor implements fixes:
Cursor prompt:
"Address Security Review Priority-1 items:
1. Validate Bearer Token strictly (src/api/auth.ts)
2. Prepared statements everywhere (src/db/queries.ts)
3. Populate .env.example with all vars
Reference: AGENTS.md Security section"
Time: 15-20 min
Phase 5: Production Deployment (Week 16)
Priority: 1st Claude Code, 2nd Antigravity
Claude Code prompt:
"Deployment pipeline:
Steps:
1. Git tag v1.0.0
2. Docker image → ECR
3. Update K8s manifest with new tag
4. Deploy to Staging + smoke test
5. Canary deploy (5% → 25% → 100%)
6. CloudWatch monitoring (auto-rollback if error rate > 1%)
After, update README with deployment docs"
Time: 20-30 min
Reuse: Every release (2-3 min)
Confidence: Automated, human error eliminated
Chapter 3: AGENTS.md as Cross-Tool Glue
Multi-tool risk: divergence. "Python in Antigravity, JavaScript in Cursor" creates integration hell later.
Solution: AGENTS.md, a single source of truth for all tools.
AGENTS.md with tool-specific sections
# AGENTS.md — Team Development Standards## Tech Stack (ALL TOOLS)- Frontend: TypeScript 5.x + React 18 + Tailwind 3.x- Backend: TypeScript 5.x + Node.js 20 + Express 4.x- Database: PostgreSQL 15- Infra: Terraform 1.6.x## Code Standards (ALL TOOLS)- ESLint: strict mode- TypeScript: strict mode- Test coverage: >= 80%- Prettier: line width 100## Tool-Specific Scopes### Antigravity- When: Spec definition, large architecture decisions- Outputs: Markdown docs, Architecture Decision Records- Deliverables: Specification v1.0 → immutable### Cursor- When: Feature implementation, code modification, review response- Config: VSCode settings.json, .eslintrc.json (shared)- Output: Git commits, PRs### Claude Code- When: Test automation, CI/CD, scripts, performance measurement- Language: Bash, Python, GitHub Actions YAML- Outputs: Executable scripts, monitoring dashboards## Cross-Tool ValidationSpec (Antigravity) → Implement (Cursor) → Test (Claude Code) → Architecture check (Antigravity)For this loop to close, all tools must share typing, naming, dependencies via this AGENTS.md.
Sync workflow
Week 0: Antigravity creates Specification v1.0 + AGENTS.md v1.0
Week 1-16: Changes happen
On change (e.g., "add new ESLint rule"):
1. Update AGENTS.md
2. Notify Cursor, Claude Code
3. Apply to new code immediately, old code gradually
Week 16: Final review
Does everything conform to AGENTS.md?
If yes → production gate passed
Chapter 4: Real-world Example — Recommendation Engine
Day 1: Antigravity spec
Antigravity prompt:
"Recommendation engine feature.
Requirements:
- Suggest products based on user purchase history
- Hourly batch processing
- Mobile + web compatible
Output: Full Specification including:
- API: GET /recommendations/{userId}
- Response: [{ productId, score }]
- Cache: 1h TTL
- DB schema: user_interactions, product_recommendations
- Infra: Kubernetes CronJob, resource estimates"
Time: 3-4 hours
Output: Specification v1.0 + AGENTS.md confirmations
Day 2: Claude Code batch script
Claude Code prompt:
"Batch recommendation processor.
Input: user_interactions table (100M rows)
Algorithm: Collaborative Filtering (simplified)
Output: product_recommendations table
Runtime: < 30 min (hourly execution)
Memory: < 512 MB
Retry: Auto 3x on error
After: simulate 1M users with test data"
Time: 2-3 hours
Language: Python + PostgreSQL
Lines: 100-150
Validation: Local test with 1M rows
Day 3: Cursor frontend
Cursor prompt:
"ProductCard component: add recommendation badge.
Changes to src/components/ProductCard.tsx:
- Show recommendation score (0-100) as gauge
- Score >= 70 → light blue background
- Click → "Why recommended?" modal
Reference: Figma ProductCard design"
Time: 5-10 min
Lines: 15-20
Next:
"Hook useRecommendations(userId)
Calls: GET /api/recommendations/{userId}
Manages: loading, error, cache (1 min)
Use in: ProductPage component"
Time: 3-5 min
Hook lines: 30-40
Day 4: Claude Code tests
Claude Code prompt:
"E2E test: Recommendations end-to-end
Flow:
1. Home page shows recommendations
2. Click recommendation → detail page
3. View "Why recommended?" modal
4. Add to cart from recommendation
Test data: test_user_001 (100 purchase history)"
Time: 20 min
Lines: 60-80
Coverage: All major flows
Also:
"Batch job monitoring script
Alert conditions:
- Execution time spike (> 50%)
- Memory > 512 MB
- Error rate > 1%
- Unusual recommendation counts
Output: Slack + Grafana"
Time: 15-20 min
Continuous value: 24/7 observability
Day 5: Antigravity integration
Antigravity prompt:
"Final integration check before production.
Verify:
1. Batch script working (Claude Code report)
2. Frontend displays correctly (Cursor + E2E tests)
3. API SLA met (< 500ms)
4. DB indexes optimized
5. Go/no-go decision"
Time: 1-2 hours
Output: Integration Report + Go/no-go
Timeline: 5 days (vs. 10-12 days single-tool)
Chapter 5: Cost Analysis
Scenario 1: Single tool (Cursor only)
Tool: Cursor Pro ¥2,000/month
Per feature (5 days):
- Cursor implementation: 4 days
- Manual testing: 0.5 days
- DIY CI/CD scripts: 0.5 days
Total: 5 days @ ¥20k/day = ¥100k human
Monthly (1 feature): ¥2k tool + ¥20k human = ¥22k
Scenario 2: 3-tool portfolio
Tools: ¥5k (Antigravity) + ¥2k (Cursor) + ¥3k (Claude) = ¥10k/month
Per feature (5 days):
- Antigravity spec + design: 0.5 days (multi-agent parallel)
- Cursor implementation: 2 days (fewer bugs from spec)
- Claude Code tests + CI/CD: 1 day (then auto-running)
- Deploy + monitoring: 0.5 days (scripts exist)
Total: 4.5 days @ ¥20k/day = ¥90k human
Monthly (1 feature): ¥10k tool + ¥18k human = ¥28k
Apparent gap: ¥6k extra. But look closer:
Multi-month view (regression testing savings)
Month 1 (single tool):
New feature: 5 days
Regression (manual): 3 days
Total: 8 days/month
Months 2-6 (3-tool portfolio):
New feature: 4.5 days
Regression (automated): 0.5 days ← Claude Code CI/CD
Total: 5 days/month
Savings per month (M2-6): 3 days = ¥60k saved
Chapter 8: Operational Findings Not in the Official Docs
Most of what follows came out of running these three tools on shipping products as an indie developer — not from release notes or tutorials. I have been building iPhone and Android apps personally since 2014, the catalog has crossed 50 million downloads across wallpaper, calming, and manifestation apps, and the business is supported by AdMob revenue plus subscriptions. Across Dolice Labs (Claude Lab, Gemini Lab, Antigravity Lab, Rork Lab — 4 sites in parallel) and the app side, the gap between documented behavior and lived operation has been wider than I expected.
8.1 Antigravity Manager View: Wait Time and Token Economics
The docs say "Manager View orchestrates up to 16 agents." In practice the behavior is more nuanced.
Parallelism is capped at the plan tier. On Pro (parallel 5), spawning 16 agents means the 6th onwards is queued behind the first batch. In my runs the active 5 tend to be UI design, code generation, test authoring, doc generation, and security review, while deployment automation and monitoring sit in the queue.
A 5-minute task with 16 agents costs about 420K–480K tokens. Three sessions a day across five working days translates to 100M–120M tokens per month. The break-even point for moving from Pro (parallel 5) to an Enterprise-tier "effective parallel 10" sits at roughly "3–4 concurrent projects per indie developer per month" — that is the threshold I am watching.
Cache hit rate is 15–25%. Resubmitting the same spec document does not reuse much. Cursor's local context cache (>70% hit) makes it obvious that Antigravity is optimizing for compression, not memoization.
A concrete example from the wallpaper app: rewriting every screen layout to support vertical writing was specced in Antigravity. Twelve of the 16 agents ran in parallel, burned about 420K tokens, and finished in seven minutes. Doing the same job in Cursor required pointing it at each file by hand and took over an hour. "Full-screen consistency changes" → Antigravity. "Three-line surgical edits" → Cursor. That dividing line emerged here.
8.2 What Cursor's @-mention Actually Saves
@-mention is sold as a precise context tool. The measured behavior:
@file:src/screens/Wallpaper.tsx compresses context from ~320K tokens to ~38K tokens. Inference time drops from 8–12 seconds to 1–2 seconds.
@symbol:LiveWallpaperRenderer.render pulls in related definitions only. This matters when a single file in indie code tends to host several features, as mine often do.
@docs:Next.js is flaky. The remote docs endpoint times out frequently. The pattern that worked for me is caching the docs I care about under .cursor/rules/ and pointing @file at the local copies.
8.3 Claude Code Worktree Parallel Development: Three Pitfalls
git worktree integration sells "parallel branches" — but three things bite in practice.
node_modules is per-worktree.feature/onboarding and feature/wallpaper-shader each need their own install. Checking SSD free space monthly became a habit.
Lockfile conflicts are likely. Letting two worktrees both edit package-lock.json produces merge conflicts on a high percentage of merges. AGENTS.md now says "lockfile changes happen in worktree A only."
CI/CD does not understand worktrees. GitHub Actions ignores worktree metadata. Branch names have to carry the disambiguation, so the workflow tags PR titles with [wt-A] and friends.
In one shipping example, the wallpaper app's "live wallpaper" and "manifestation message" features were built in parallel — two worktrees, one driven by Antigravity, the other by me in Cursor. The unglamorous lesson: parallel development needs a physically separated workspace, not just a faster model.
8.4 Monthly 3-Tool Cost vs. AdMob Revenue
Running Dolice Labs (four sites in parallel) plus the personal app business (50M downloads), the monthly cost allocation has settled here:
Line item
Monthly cost
Purpose
Antigravity Pro
¥5,000
Spec-driven design, security review
Cursor Pro+
¥4,000
Daily implementation, JetBrains projects
Claude Code API
¥18,000–¥35,000
Automation scripts, article generation pipeline for 4 sites
GitHub Actions
¥3,000
CI/CD (free tier + paid overage)
Cloudflare Workers
¥7,000
Hosting for 4 sites
Stripe fees
¥5,000
Membership revenue × 3.6%
Total
¥42,000–¥59,000
Fixed AI IDE cost relative to monthly revenue
Against a roughly ¥1,000,000/month AdMob revenue baseline, this is well within what an indie developer can absorb. The actual tradeoff I revisit every month is "spend time saving tool fees" vs. "let the tools do that work and put my hours into the next art piece."
8.5 AGENTS.md as a Contract, Not a Config File
After running this for a while it became clear that AGENTS.md is less a config file and more a contract between me and three AI agents. The excerpt below is from the file in production use at Dolice Labs.
# AGENTS.md v1.3 (2026-05-29 update)## Language and Frameworks (all tools)- Language: TypeScript strict mode (never use any unless documented)- Frontend: Next.js 16 App Router + React Server Components- Backend: Cloudflare Workers + KV + Stripe API v2024-11- Styling: Tailwind CSS (custom CSS only in layout.css)## Contract clauses (violations are reverted)1. Any change to existing frontmatter schema is unmergeable2. Any change that adds 1MB+ to articles.json is unmergeable3. Generated prose that violates `_documents/AUTHOR_VOICE_STYLE_GUIDE.md` is discarded4. Articles flagged by `python3 _documents/_quality_audit/_scripts/article_gate.py` cannot be pushed## Tool-specific scope (no overlap)- Antigravity: full-screen-impact changes, security review, spec authoring — only- Cursor: single-file edits, ESLint/TypeScript fixes — only- Claude Code: shell scripts, CI/CD workflows, automation — only## Cross-tool validation- When implementing in Cursor a spec previously committed by Antigravity, the spec section number must appear in the commit message- Tests generated automatically by Claude Code cannot merge without Cursor review by a human
With this file in the repo, the three tools converge on consistent granularity, naming, and coverage. The internal name for it is "the work rules for AI agents."
8.6 Notes from Running This Alongside a Contemporary Art Practice
In parallel with software work I am a contemporary artist with 17 international art awards. I taught myself programming at 16 in 1997 over the early internet, and in 2019 a vision of a ring of light above Kichijoji station tipped me toward visual work — that practice continues today. The rule I keep is AI is not in the loop for artwork, only for operations and writing, and that line has carried over into how I divide work among AI IDEs.
Whatever can be delegated to the three tools is delegated, and the human stays focused on the core decisions that make software feel like a work, not a build. Cursor takes daily code, Antigravity owns the big design, Claude Code carries automation — and what's left in front of me is the single moment a user opens the screen.
Chapter 6: Tool Selection Decision Tree
New task arrives
↓
"Affects entire project direction?"
YES → Antigravity (multi-agent, full scope)
NO ↓
↓
"Modifying existing code (< 200 lines)?"
YES → Cursor (surgical, fast feedback)
NO ↓
↓
"Scripting, testing, deployment?"
YES → Claude Code (terminal, automation)
NO → Cursor (default)
The initial setup (AGENTS.md, CI/CD) takes 1–2 weeks. The ROI is measurable within a month.
In 2026, the question isn't "which single tool is best?" It's "how do I orchestrate three tools to their full potential?"
This guide is the answer.
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