The Agentic Systems Series

Introduction

Building AI coding assistants that actually work requires solving some hard technical problems. After analyzing several modern implementations, including Claude Code (Anthropic's CLI), Amp (Sourcegraph's collaborative platform), and open-source alternatives, I've identified patterns that separate practical tools from impressive demos.

Modern AI coding assistants face three critical challenges: delivering instant feedback during long-running operations, preventing destructive actions through clear safety boundaries, and remaining extensible without becoming unwieldy. The best implementations tackle these through clever architecture choices rather than brute force.

This guide explores architectural patterns discovered through deep analysis of real-world agentic systems. We'll examine how reactive UI patterns enable responsive interactions, how permission systems prevent disasters, and how plugin architectures maintain clean extensibility. These aren't theoretical concepts - they're battle-tested patterns running in production tools today.

Key Patterns We'll Explore

Streaming Architecture: How async generators and reactive patterns create responsive UIs that update in real-time, even during complex multi-step operations.

Permission Systems: Structured approaches to safety that go beyond simple confirmation dialogs, including contextual permissions and operation classification.

Tool Extensibility: Plugin architectures that make adding new capabilities straightforward while maintaining consistency and type safety.

Parallel Execution: Smart strategies for running multiple operations concurrently without creating race conditions or corrupting state.

Command Loops: Recursive patterns that enable natural multi-turn conversations while maintaining context and handling errors gracefully.

What You'll Learn

This guide provides practical insights for engineers building AI-powered development tools. You'll understand:

• How to stream results immediately instead of making users wait
• Patterns for safe file and system operations with clear permission boundaries
• Architectures that scale from simple scripts to complex multi-agent systems
• Real implementation details from production codebases

Whether you're building a coding assistant, extending an existing tool, or just curious about how these systems work under the hood, this guide offers concrete patterns you can apply.

Using This Guide

This is a technical guide for builders. Each chapter focuses on specific architectural patterns with real code examples. You can read sequentially to understand the full system architecture, or jump to specific topics relevant to your current challenges.

For advanced users wanting to build their own AI coding assistants, this guide covers the complete technical stack: command loops, execution flows, tool systems, and UI patterns that make these systems practical.

Contact and Attribution

You can reach me on X at @devgerred, or support my Ko-fi.

This work is licensed under a CC BY 4.0 License.

@misc{building_an_agentic_system,
  author = {Gerred Dillon},
  title = {Building an Agentic System},
  year = {2024},
  howpublished = {https://gerred.github.io/building-an-agentic-system/}
}