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An AI-powered operating system where specialized agents collaborate to research, build, and validate software autonomously.
About the Project
AWOS (Autonomous Workforce Operating System) is an AI-powered multi-agent platform that transforms Slack into an intelligent workplace where autonomous AI agents collaborate to accomplish complex tasks. Instead of acting as a traditional chatbot that only responds to prompts, AWOS understands a user's objective, determines the best approach to achieve it, delegates work to specialized AI agents, and coordinates the execution of the task through external tools.
Modern software development often requires developers to constantly switch between communication platforms, GitHub, documentation, local development environments, and various productivity tools. This constant context switching slows down development and makes collaboration more difficult. AWOS addresses this problem by bringing intelligent automation directly into Slack, allowing users to assign high-level missions while the system manages planning, reasoning, execution, and coordination in the background.
At the heart of AWOS is CORTEX, an orchestration engine powered by Google Gemini and LangGraph. CORTEX analyzes every mission, identifies its intent, determines its complexity, classifies its domain, and generates an execution strategy. Based on this reasoning, it delegates work to specialized AI agents, each responsible for a specific stage of the workflow.
The CEO Agent acts as the decision maker by determining which agents are required, selecting the appropriate tools, and coordinating the overall execution process. The Research Agent gathers technical information, explores relevant repositories, and identifies suitable technologies and implementation approaches. The Engineer Agent is responsible for executing development-related tasks such as creating repositories, organizing project structures, and interacting with development tools. The QA Agent validates the generated work, performs quality checks, and ensures that the final output meets the intended requirements.
To move beyond conversational AI, AWOS integrates the Model Context Protocol (MCP), enabling AI agents to securely communicate with external tools and services. Through MCP, AWOS can interact with GitHub to create repositories, manage branches, generate pull requests, and support collaborative software development workflows. It also connects with the local filesystem, allowing agents to create, organize, and modify project files automatically. This combination of intelligent reasoning and tool execution enables AI agents to perform meaningful work instead of simply generating text responses.
The backend of AWOS is built using Python and FastAPI, while LangGraph manages the orchestration of multiple AI agents. Google Gemini provides reasoning and decision-making capabilities throughout the system, and Slack serves as the primary user interface. GitHub integration allows the platform to automate software development workflows, making the entire system capable of supporting real development teams from initial planning through execution.
Rather than replacing developers, AWOS is designed to function as an intelligent digital workforce that works alongside human teams. By combining multiple specialized AI agents with workflow orchestration and external tool integration, AWOS demonstrates how collaborative AI systems can simplify software development, reduce repetitive work, and improve overall productivity.
Key Features Multi-agent architecture with specialized CEO, Research, Engineer, and QA agents Intelligent mission analysis and planning using Google Gemini Workflow orchestration powered by LangGraph Secure external tool integration using the Model Context Protocol (MCP) GitHub automation for repositories, branches, pull requests, and development workflows Filesystem automation for project creation and management Native Slack integration for workplace collaboration FastAPI backend with a modular and scalable architecture Rule-based fallback mechanisms to improve system reliability Vision
Our vision is to build an Autonomous Workforce Operating System where intelligent AI agents collaborate with one another to perform meaningful work, rather than simply answering questions. We believe the future of workplace productivity lies in AI systems that can understand objectives, coordinate specialized agents, interact with real tools, and execute complex workflows alongside human teams. AWOS is our step toward making that vision a reality.