SoftwareUnit: I Hired 8 AI Agents So I Could Be a Sloth

Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Submission 🦥

This is a submission for the Hacktoberfest Open-Source AI Challenge: Week 3 (theme: Slow and Steady).

Sloths move slowly, conserve energy, and let the world come to them. Starting a new software project is the opposite: write the plan, the requirements, the architecture, the design spec, the backend, the frontend, the tests, the Docker files. Every time. Before the fun part even begins.

So for International Sloth Day week, I built SoftwareUnit: a virtual software team of 8 AI agents. I type one project idea, and the team hands me back a full project to review.

Repo: https://github.com/madhumitha-r26/SoftwareUnit_CrewAI

SoftwareUnit is an automated software delivery workflow built on the open-source CrewAI framework, with Gemma running through Ollama. You give it a project idea, and it produces:

Generated apps follow one fixed stack, so every agent works from the same technical contract:

That stack requirement flows through architecture, implementation, QA, and deployment, so the frontend, backend, tests, and Docker files all agree with each other.

When started, the app asks for a project idea and runs these stages:

The backend and frontend tasks run asynchronously, so they build in parallel. QA and DevOps then take both outputs as context. Like a real team, the later roles build on what the earlier ones decided.

output/ documentation/ 01_project_plan.md 02_requirements.md 03_architecture.md 04_ui_design.md 05_qa_report.md 06_deployment.md backend/ # Node.js/Express.js app + MongoDB integration frontend/ # React.js + Tailwind CSS app tests/ # QA and automated test artifacts deployment/ # Dockerfiles, Docker Compose, related assets Enter fullscreen mode Exit fullscreen mode A small file-writing tool in tools.py is scoped to output/, so the agents can only write inside that folder and not elsewhere on my machine.

python -m venv. venv. \.venv\Scripts\Activate.ps1 python -m pip install crewai crewai-tools python. \main.py Enter fullscreen mode Exit fullscreen mode Enter a project idea when prompted, then check output/.

The honest framing: the output is scaffolding. It still needs review, configuration, and testing before production. But getting from a blank folder to a reviewable project in one prompt is exactly the kind of laziness I was after.

To run the generated application, update your credentials in both the frontend and backend code the agents generated.

Clone it, give it your own project idea, and let the crew do the heavy lifting. Issues and PRs are welcome. Happy Hacktoberfest! 🦥