AI Dev Team – Agentic App Builder

A multi-agent AI system that simulates a real developer team—planning, coding, reviewing, and fixing applications automatically using Amazon Nova.

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Inspiration

We were inspired by the idea of how software development normally happens in a team. Usually there is an architect who plans the system, a developer who writes the code, someone who reviews it, someone who tests it, and someone who fixes issues. We thought it would be interesting to build an AI system that works like a small development team. With the rise of Agentic AI and powerful models like Amazon Nova, we wanted to see if multiple AI agents could collaborate together and simulate a real development workflow. Our goal was to show how AI can help turn an idea into a structured application faster.

What it does

AI Dev Team – Agentic App Builder takes a simple idea from the user and processes it through multiple AI agents. Each agent plays a specific role in the development process. The Architect agent designs the system structure, the Developer agent generates code based on that architecture, the Reviewer agent analyzes the code, the Tester agent checks the logic, and the Fix agent improves the output. The system runs these steps one after another so that the final result represents how a real development team might approach building a project.

How we built it

We built the project using Python and Flask for the web interface. The backend is designed as a modular multi-agent system where each agent is responsible for a specific task. An Agent Controller manages the flow between the agents and ensures that the output from one agent becomes the input for the next. For AI reasoning and generation we integrated Amazon Nova models through AWS Bedrock. We also used a planning pattern and tool-use pattern to simulate how agents think and perform tasks in a structured way.

Challenges we ran into

One of the biggest challenges was coordinating multiple agents so that they could pass information correctly from one step to the next. We also had to carefully design how the system handles responses from the AI model so the output remains structured and usable. Integrating AWS services and configuring the model access was another challenge. Debugging the pipeline was also tricky because when one agent had an issue it could affect the rest of the process.

Accomplishments that we're proud of

We are proud that we were able to build a working multi-agent system where different AI agents collaborate to simulate a development workflow. Integrating Amazon Nova models and building a structured architecture for the agents was a big milestone for us. Seeing the system take a simple idea and process it through several development stages felt like building a miniature AI development team.

What we learned

During this project we learned a lot about designing agent-based AI systems and how different components need to communicate with each other. We gained practical experience working with AWS Bedrock and large language models. We also learned how important good system design is when building complex AI applications.

What's next for AI Dev Team – Agentic App Builder

In the future we would like to make the system more interactive and intelligent. We want to add live visualization of agent progress, improve how agents collaborate with each other, and allow the system to generate complete deployable applications. Our goal is to move closer to a system where AI agents can work together like a real engineering team and help people turn ideas into applications more easily.

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