The Problem Nobody Talks About
You're starting a business. Smart move: you consult three professionals before choosing your legal entity.
Your Tax CPA says: "Form an LLC. Pass-through taxation will save you $15K in self-employment taxes this year."
Your Corporate Attorney says: "Form a C-Corp. You need proper liability protection, and it's the only structure that scales for equity distribution."
Your Business Strategist says: "Definitely C-Corp. No VC will touch an LLC, and you'll need Series A funding within 18 months."
Three experts. Three different answers. And you're more confused than when you started.
This isn't edge case—it's the norm. These professionals work in silos. Your tax CPA doesn't think about your fundraising timeline. Your attorney doesn't optimize for tax efficiency. Your strategist doesn't consider legal compliance costs.
The result? Conflicting advice that leaves entrepreneurs paralyzed.
The Root Cause: Lack of Coordination
Traditional consulting fails because experts optimize for their domain without understanding interdependencies. Tax strategies that save money today can kill fundraising potential tomorrow. Legal structures that protect liability might create tax nightmares. Growth plans might expose you to unnecessary compliance costs.
What you actually need isn't three separate opinions—you need integrated strategy where all perspectives are considered together.
The Solution: Multi-Agent Coordination
Better Call Saul uses three AI specialist agents—Tax CPA, Corporate Attorney, and Business Strategist—coordinated by an intelligent orchestrator.
The magic isn't having three agents. It's having them work together.
Here's what happens when you ask "What entity should I form?":
- Parallel Analysis: All three specialists analyze your situation simultaneously (not sequentially)
- Conflict Detection: The Coordinator identifies when recommendations contradict (e.g., S-Corp for tax savings vs. C-Corp for investors)
- Unified Strategy: Instead of three conflicting answers, you get one integrated recommendation with trade-offs clearly explained
This mirrors how expert advisory should work in the real world—but rarely does.
Architecture: How It Actually Works
The Agent Hierarchy
User Query
↓
Coordinator Agent (orchestrator)
├─→ Tax CPA Agent (specialist)
├─→ Attorney Agent (specialist)
└─→ Strategist Agent (specialist)
↓
Conflict Resolution
↓
Unified Recommendation
What Makes This Different
Traditional AI chatbot: One model pretending to be everything.
Multiple isolated chatbots: Three models giving conflicting advice.
Better Call Saul: Three specialists + one intelligent coordinator that identifies conflicts and synthesizes solutions.
Real Example Output
Instead of getting:
- Tax CPA: "Use S-Corp"
- Attorney: "Use C-Corp"
- Strategist: "Use C-Corp"
You get:
Recommended Structure: C-Corporation
Key Benefits:
- Investor-friendly for future funding
- Clean equity structure for co-founders
- Strong liability protection
Trade-offs:
- Double taxation on distributed profits
- Higher compliance overhead than LLC
Tax Mitigation Strategy:
- Take reasonable W-2 salary (reduces self-employment tax)
- Reinvest profits for growth (defers dividend taxation)
- Consider QSBS eligibility for eventual exit
This is integrated advice, not isolated opinions.
The Technical Foundation
Built on Google's Agent Development Kit (ADK) with Gemini 2.5 Flash, deployed on Cloud Run.
Why This Stack?
ADK's Sub-Agent Pattern: Built-in framework for hierarchical agent coordination. The Coordinator automatically delegates to specialists in parallel and collects their responses.
Gemini 2.5 Flash: Fast enough for real-time chat (10-15 second responses), smart enough for complex reasoning, cheap enough for production use.
Cloud Run Serverless: Two services (frontend + backend) that auto-scale 0-10 instances. Costs $0 when idle, handles traffic spikes automatically.
Infrastructure Overview
Frontend (React UI)
↓ HTTPS
Backend (ADK API Server)
↓ Parallel Delegation
[Tax Agent] [Legal Agent] [Strategy Agent]
↓ All call
Gemini 2.5 Flash API
↓ Synthesis
Coordinator Agent
↓ JSON Response
User
Key architectural wins:
- Parallel execution = 2-3x faster than sequential
- Scale-to-zero = production-ready system costs nearly nothing during low traffic
- Modular agents = add new specialists without touching existing code
Why This Matters Beyond One Use Case
Better Call Saul demonstrates a principle that applies far beyond corporate law:
Multi-agent AI systems excel at coordination problems that humans struggle with.
Other domains where this pattern works:
- Healthcare: Coordinating cardiologist, neurologist, and nutritionist recommendations
- Finance: Integrating tax advisor, investment manager, and estate planner advice
- Engineering: Balancing frontend, backend, and DevOps perspectives in system design
The future of AI isn't single superintelligent agents—it's teams of specialized agents that coordinate effectively.
The Bottom Line
Traditional consulting: Experts work in silos → conflicting advice → confusion.
Better Call Saul: Specialists coordinate → unified strategy → clarity.
Built in under 24 hours for the Google Cloud Run Hackathon, this system proves that multi-agent AI can solve real-world problems that plague traditional professional services.
The architecture is production-ready, cost-efficient, and scalable. More importantly, it solves a genuine problem that entrepreneurs face every single day.
Multi-agent AI isn't just a technical curiosity—it's how we should be building intelligent systems that mirror the complexity of real expertise.
Tags: #CloudRunHackathon #googlecloud #cloudrun #adk #aiagents #multiagent #hackathon
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