Back to Projects
Featured Project

Autonomous Development Agent

Your AI pair programmer that never sleeps

AI agent that builds software autonomously - plans tasks, generates code, runs tests, fixes errors, and learns from outcomes.

The Problem

Building software is slow. Debugging is tedious. Developers spend 50% of their time on repetitive tasks like writing boilerplate, fixing simple bugs, and running tests. What if an AI could handle the repetitive parts while you focus on architecture and creative problem-solving? Traditional code assistants require constant hand-holding - you ask, they respond, you verify, repeat. This agent flips the script: describe what you want, and it builds it autonomously - planning, coding, testing, and fixing until it works.

What You Can Do

Generate Boilerplate

Describe a feature in plain English, get production-ready code with proper structure and patterns.

Auto-fix Failing Tests

Point the agent at failing tests and watch it iteratively fix the code until everything passes.

Refactor with Intent

Say 'make this more maintainable' or 'add error handling' and the agent rewrites intelligently.

Learn Your Patterns

Persistent memory means it learns from your codebase and improves over time.

Tech Stack

Core AI

Anthropic Claude APIFunction CallingChain of Thought

Claude powers the reasoning engine with advanced function calling for tool use.

Agent Framework

PythonasyncioRich CLI

Built in Python with async support for parallel task execution.

Code Execution

subprocesspytestAST parsing

Safe code execution with test automation and static analysis.

Memory & State

SQLiteVector embeddingsSession persistence

Persistent memory allows learning across sessions and projects.

Architecture

The agent follows a Plan-Execute-Observe loop:

1. Planner: Takes high-level goals and decomposes into atomic tasks

2. Executor: Generates code, runs commands, and applies changes

3. Observer: Monitors test results and system feedback

4. Memory: Stores successful patterns and learned corrections

Each iteration refines the output until success criteria are met or the agent requests human guidance.

Results

85%
First-pass success rate on standard tasks
3x
Faster boilerplate generation vs manual
Patience for repetitive debugging

Key Features

  • 1Autonomous task planning and decomposition
  • 2Code generation with self-correction
  • 3Test execution and error resolution
  • 4Memory persistence across sessions
  • 5CLI interface for developer interaction

Interested in this project?

Check out the source code, try the demo, or get in touch to discuss how similar solutions could help your team.