# Learn FastroAI

Build AI applications by solving real problems.

This isn't another "hello world" tutorial. We're going to build real AI applications by tackling actual problems that people face every day. You'll learn FastroAI by understanding **why** certain decisions matter, not just memorizing syntax.

!!! tip "Choose Your Starting Point"
    **New to AI applications?** Start with [What Problems are Solvable by AI?](0-what-problems-are-solvable-by-ai/index.md) to learn how to identify good AI use cases before diving into implementation.
    
    **Want to skip theory?** Check out [Getting Started](../getting-started/index.md) for the 5-minute setup. Come back here when you want to understand the deeper concepts.

Each section starts with real problems and requirements, discusses the technical challenges, then shows you how FastroAI solves them elegantly.

## What You'll Actually Build

Instead of building toy examples, you'll work through a **Personal Finance Assistant** that evolves from a simple idea to a production-ready AI application:

=== "Problem Identification"

    **Learn when AI actually helps**

    - Identifying AI-solvable problems (not everything needs AI!)
    - Understanding what LLMs can and can't do well
    - From vague ideas to concrete requirements
    - Evaluating if your idea actually benefits from AI

=== "Technical Implementation"

    **Build your first AI solution**

    - AI agents and conversation systems that actually work
    - From requirements to architecture decisions
    - Building your first AI application with FastroAI
    - Testing and iteration strategies (because the first version is never right)

=== "Multi-User Systems"

    **Scale beyond yourself**

    - Authentication and user management (the boring but essential stuff)
    - Data isolation and multi-tenancy patterns
    - Admin interfaces and monitoring tools
    - Security and privacy considerations

=== "Business Models"

    **Turn your application into revenue**

    - Payment systems and billing that actually work
    - Access control and entitlements (FastroAI's secret weapon)
    - Usage tracking and cost optimization
    - API access and developer tools

=== "Production Scale"

    **Handle real-world demands**

    - Performance and caching strategies
    - Background processing for heavy tasks
    - Monitoring and observability
    - Deployment and scaling patterns

## How This Works

Here's how we'll take you from idea to working AI application:

<div class="grid cards" markdown>

-   :material-help-circle:{ .lg .middle } **0. What Problems are Solvable by AI?**
    
    *"Should I even build this with AI?"*

    ---
    
    Before you write any code, figure out if you should even build this with AI. Not every problem needs AI, and AI isn't magic.
    
    We'll walk through frameworks for identifying problems where AI actually helps versus where it just adds complexity.
    
    **What you'll learn:** Problem identification frameworks that save months of wasted effort

-   :material-lightbulb:{ .lg .middle } **1. I Have a Problem that Can be Solved by AI**
    
    *"Walking through the complete evaluation process"*

    ---
    
    You think you have a problem AI can solve. But how do you know for sure? Follow along as we evaluate a real problem - personal finance management - and work through the complete process from vague idea to concrete implementation plan.
    
    This isn't abstract theory. You'll see exactly how to evaluate whether AI helps and turn requirements into something buildable.
    
    **What you'll learn:** Complete problem-to-plan methodology using a real case study

-   :material-hammer-wrench:{ .lg .middle } **2. I Want to Build a Proof of Concept**
    
    *"From validated problem to working prototype"*

    ---
    
    You have a validated problem and implementation plan - now build the actual solution. This section shows you how to translate requirements into architecture and build your first working AI application with FastroAI.
    
    Currently covers requirements to architecture translation. More content coming soon.
    
    **What you'll learn:** Requirements to architecture translation (more coming soon)

-   :material-account-group:{ .lg .middle } **3. Multi-User Systems** *(Coming Soon)*
    
    *"Other people want to use my tool"*

    ---
    
    The moment your side project becomes real. When other people want to use your tool, everything changes. You need authentication, data isolation, user management.

-   :material-cash-multiple:{ .lg .middle } **4. Monetizing AI Applications** *(Coming Soon)*
    
    *"AI costs money, I need to make money"*

    ---
    
    AI costs money, so you need to make money. Learn how to build sustainable business models with FastroAI's flexible entitlement system.

-   :material-trending-up:{ .lg .middle } **5. Scaling AI Applications** *(Coming Soon)*
    
    *"Success problems are good problems"*

    ---
    
    Success problems are good problems, but they're still problems. When your application gets traction but becomes slow and expensive, you need to optimize performance and scale intelligently.

</div>

---

## Alternative Learning Paths

=== "By Timeline"

    - **Weekend project**: Sections 0-2 → Working AI application
    - **Side business**: Sections 0-4 → Profitable AI service
    - **Production app**: All sections → Scalable AI platform
    - **Just exploring**: Start with [Problem Identification](0-what-problems-are-solvable-by-ai/index.md)

=== "By Experience"

    - **New to AI**: Start from the beginning, don't skip fundamentals
    - **AI background, new to web**: Focus on sections 3-5 for platform concerns  
    - **Web developer, new to AI**: Sections 1-2 will be your sweet spot
    - **Full-stack developer**: Skip around, but don't skip the entitlement system

=== "By Goal"

    - **"I want to understand AI applications"** → Section 0-1
    - **"I want to build a SaaS"** → All sections, focus on 4-5
    - **"I want to understand FastroAI"** → Section 2, then [Guides](../guides/index.md)
    - **"I have a specific problem"** → Check [Guides](../guides/index.md) first

## Why This Approach Works

<div class="grid cards" markdown>

-   :material-target:{ .lg .middle } **Real Problems, Real Solutions**

    ---

    We don't build todo apps or simple chatbots. We tackle actual problems that people face.

-   :material-cash:{ .lg .middle } **Business Reality**

    ---

    Every technical decision considers real-world constraints: cost, performance, and viability.

-   :material-rocket-launch:{ .lg .middle } **Production Focus**

    ---

    Learn patterns that scale from prototype to production, not just proof-of-concept code.

-   :material-puzzle:{ .lg .middle } **FastroAI Integration**

    ---

    Leverage FastroAI's unique strengths, especially the entitlement system for any business model.

</div>

## Ready to Start?

!!! success "Choose your starting point"

    **New to AI applications?** → Start with [What Problems are Solvable by AI?](0-what-problems-are-solvable-by-ai/index.md)

    **Have a problem in mind?** → Jump to [I Have a Problem that Can be Solved by AI](1-case-study-personal-finance-assistant/index.md)

    **Ready to build?** → Continue to [I Want to Build a Proof of Concept](2-building-your-first-ai-application/index.md) *(in progress)*

    **Want to monetize?** → Monetizing AI Applications (coming soon)

    **Need technical details?** → Explore [Guides](../guides/index.md) for deep dives on each feature

---

**Stop building AI applications that nobody wants.**

Learn to identify real problems, build solutions that work, and create sustainable businesses around AI technology.

[Start Learning →](0-what-problems-are-solvable-by-ai/index.md){ .md-button .md-button--primary }
