Building Your Own Framework

Master designing and building custom agentic AI frameworks from scratch

Why Build Your Own Framework?

While frameworks like LangChain and Haystack are powerful, building your own custom framework gives you complete control over architecture, performance, and business logic. Perfect for specialized use cases.

Existing Frameworks vs Custom

Using Existing Frameworks

  • Fast to start: Pre-built components, documentation, community support
  • Battle-tested: Production-ready patterns and edge cases handled
  • Limited control: Constrained by framework's architecture and opinions
  • Dependencies: Framework updates may break your code
  • Overhead: Includes features you don't need, larger bundle size
💡 Best for: General use cases, rapid prototyping, standard workflows
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Specialized Requirements

Your use case has unique needs that existing frameworks don't address well. Custom framework lets you optimize for your specific domain.

Performance Critical

Need maximum speed and minimal overhead. Custom framework eliminates unnecessary abstractions and gives you direct control.

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Deep Integration

Tight coupling with existing systems, databases, and internal APIs. Custom framework integrates seamlessly with your tech stack.

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Learning & Control

Understand every piece of your agent system. Building from scratch teaches you exactly how agents work under the hood.

What We'll Build

1. Core Agent Loop

The fundamental observe → reason → act cycle that powers agent decision-making and execution.

2. Tool Registry & Execution

Dynamic tool registration, schema validation, and safe execution environment with error handling.

3. Memory System

Short-term context management and long-term storage with retrieval for maintaining conversation state.

4. Production Patterns

Logging, monitoring, error handling, rate limiting, and deployment strategies for real-world use.

💡 Framework Design Principles

  • Simplicity first: Start minimal, add complexity only when needed
  • Composable design: Small, reusable components that work together
  • Type safety: Use TypeScript/Python type hints for reliability
  • Testability: Design for unit testing from the start
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