Vibe Coding with AI: Building the Future of Investment Software
What if you could build sophisticated software by describing what you want, rather than writing every line of code? This isn’t science fiction—it’s “vibe coding,” and it’s how we built Navam Invest, a complete AI-powered investment advisory platform.
The AI-Worthy Problem
Every great project starts with identifying a problem worth solving. For Navam Invest, the challenge was clear: retail investors managing $50K-$1M portfolios face a dilemma. Professional wealth management costs $1,000-$10,000 annually, putting comprehensive investment research out of reach for most individuals.
This problem is what we call “AI-worthy”—it involves:
- Processing infinite input variables (market data, news, earnings, economic indicators)
- Generating statistical recommendations based on complex analysis
- Delivering superior service at a fraction of traditional costs
- Explaining decisions transparently
What is Vibe Coding?
Vibe coding is a development philosophy where humans focus on strategic direction while AI handles implementation. Instead of writing code line-by-line, you:
- Define the problem and desired outcomes
- Provide domain expertise and strategic guidance
- Let AI generate the actual code
- Iterate rapidly on feedback
The result? Navam Invest was built as a 100% AI-generated system using tools like Claude Code, with humans steering the vision and architecture.
The Evolution: From Complex to Elegant
Attempt 1: Claude Agent SDK
Our first approach used Claude’s Agent SDK with prescriptive agent prompts. While functional, this path revealed significant challenges:
- Complex, verbose prompts required for each agent
- High token usage ($5-10 per multi-agent run)
- Difficult migration and maintenance
- 5-10 minutes per workflow execution
The framework itself was powerful, but the complexity became a liability. When frameworks evolve with 30-60 day half-lives, heavy investment in complex implementations becomes technical debt.
Breakthrough: LangGraph
Switching to LangGraph transformed our development process. LangGraph is a low-level orchestration framework for building stateful AI agents with unprecedented flexibility:
- State Graphs: Visual representation of agent workflows
- Minimal Specifications: Less prescriptive, more adaptive
- Faster Iteration: Changes propagate quickly
- Production-Ready: Built-in persistence and checkpointing
The philosophy shift was profound: less is more. By providing minimal, iterative specifications rather than complex prescriptive prompts, we achieved better results faster.
The Architecture: 10 Specialized AI Agents
Navam Invest employs 10 specialized AI agents, each an expert in a specific domain:
Core Investment Agents
- Quill: Deep fundamental research with DCF valuation and comparable company analysis
- Earnings Whisperer: Tracks earnings surprises and post-earnings drift opportunities
- Screen Forge: Systematic stock screening across quality, momentum, and value factors
- Macro Lens: Top-down economic analysis and sector positioning
Risk & Optimization Agents
- News Sentry: Real-time event monitoring and material catalyst detection
- Risk Shield: Portfolio exposure analysis and VAR calculations
- Tax Scout: Tax-loss harvesting and wash-sale compliance
- Hedge Smith: Options strategies for protection and yield enhancement
Multi-Agent Workflows: Collaboration at Scale
The real magic happens when agents collaborate. Navam Invest includes pre-built workflows that orchestrate multiple agents:
/analyze Command
A comprehensive 5-agent analysis that combines:
- Fundamental research (Quill)
- Technical momentum (Screen Forge)
- Risk assessment (Risk Shield)
- Macro context (Macro Lens)
- Recent news (News Sentry)
This workflow delivers institutional-grade analysis in minutes, not hours.
/discover Command
Systematic idea generation combining screening, earnings analysis, and risk filtering to surface new investment opportunities.
Technical Innovation: Progressive Streaming
One of Navam Invest’s unique features is real-time transparency. You don’t just see the final answer—you watch the AI agents reason:
- See which tools each agent calls
- Track API requests in real-time
- Observe reasoning as it develops
- Full audit trails of every decision
This progressive streaming builds trust. You’re not getting a black box recommendation—you’re watching professional-grade analysis unfold.
The Human-AI Collaboration Principle
Vibe coding doesn’t mean AI does everything. The most successful approach combines:
Human Contribution
- Strategic vision and problem definition
- Domain expertise (investment knowledge)
- Quality assessment and feedback
- Ethical guardrails and user experience design
AI Contribution
- Code generation and implementation
- Pattern recognition across vast codebases
- Rapid iteration and refactoring
- Documentation and test generation
Key Lessons Learned
1. Less is More
Minimal, iterative specifications beat complex prescriptive prompts. Let the AI figure out implementation details while you focus on outcomes.
2. Domain Knowledge is Critical
AI can generate code, but you need deep understanding of the problem domain to steer it effectively. Investment expertise was crucial for Navam Invest.
3. Frameworks Evolve Rapidly
With 30-60 day half-lives, investing heavily in complex framework-specific code is risky. Keep your architecture flexible and loosely coupled.
4. Progressive Composition Works Best
Build incrementally. Start with one agent, validate it works, then add more. This “progressive composition” approach reduces complexity and enables faster debugging.
5. Transparency Builds Trust
Showing the AI’s reasoning process, not just final outputs, dramatically increases user confidence. Progressive streaming was a game-changer.
The Economics of AI Development
Vibe coding changes development economics:
- Speed: Features that might take weeks can be built in days
- Cost: API costs during development ($5-15 per complex workflow) are minimal compared to developer time
- Quality: AI-generated code often follows best practices automatically
- Maintenance: Well-architected systems remain maintainable
A Glimpse at the Future
The most exciting aspect of vibe coding isn’t just speed—it’s flexibility. With Navam Invest’s architecture, we could potentially:
- Shift from investment advice to legal research by swapping tool configurations
- Adapt to new financial markets by updating data sources
- Add new agent capabilities by defining their roles and tools
This flexibility suggests a future where software becomes more fluid, adapting to new domains without complete rewrites.
Getting Started with Vibe Coding
Want to explore this approach yourself? Here’s how:
1. Choose an AI-Worthy Problem
Look for domains with:
- Complex inputs and probabilistic outputs
- Need for expert-level analysis
- Opportunities for automation
2. Select Your Tools
- Claude Code: For vibe coding and rapid development
- LangGraph: For multi-agent orchestration
- Anthropic Claude: For powerful reasoning capabilities
3. Start Minimal
Build one agent. Make it work. Then expand. Progressive composition beats big-bang architecture.
4. Focus on Outcomes
Describe what you want the system to do, not how to do it. Trust the AI to handle implementation details.
Conclusion: The Age of Autopoietic Software
Vibe coding represents a fundamental shift in how we build software. By combining human strategic thinking with AI implementation capabilities, we’re entering an era where ideas can become reality faster than ever before.
Navam Invest proves this approach works for complex, production-grade systems. A full investment advisory platform, with 10 specialized agents and multi-agent workflows, built entirely through vibe coding.
The question isn’t whether AI will transform software development—it already has. The question is: what will you build?
Try Navam Invest Today
Experience the future of AI-powered investment intelligence. Built with vibe coding, ready for real-world use.