🌟 Inspiration

The hackathon theme of AI-powered solutions inspired us to take a step further in automating repetitive tasks. We built AI Agents to simulate employee roles, allowing them to handle mundane tasks while we focus on strategy and innovation. This concept excited us because we wanted to explore how far AI could go in taking over day-to-day responsibilities in a virtual workspace. 🚀

🔍 What it does

• Users can create and assign tasks to their AI agents, who perform actions just like real employees. 🧑‍💻🤖
• The AI agents can communicate, collaborate, and complete work autonomously based on task complexity. 🗂️
• Through our interactive UI, users can track their agents' progress and request reports as needed. 📊
• Each AI agent can handle multiple tasks simultaneously, optimizing productivity. ⚡

🛠️ How we built it

We started by defining the roles AI agents would play and identifying tasks they could handle autonomously. Using Python, OpenAI's GPT, and LangChain for agent behavior, we simulated employees who could make decisions based on predefined parameters. We then connected the agents to a database using PostgreSQL for task and progress tracking.

Our Next.js frontend communicates with the AI agents via API, allowing users to interact with them easily. Each agent was containerized using Docker to enable seamless scaling as more users or tasks were added. 🖥️🛠️

🚧 Challenges we ran into

Defining realistic AI behavior for specific tasks was a big hurdle. We wanted our agents to be autonomous but still make decisions aligned with company policies, which meant fine-tuning the models. We also struggled to keep the agents' actions efficient while ensuring they didn’t overlap or conflict on collaborative tasks. 🧩

🎉 Accomplishments that we're proud of

• We successfully created AI agents capable of completing tasks autonomously with minimal supervision. 🤖
• Our agent-based system scales well across different roles and tasks, allowing flexibility in assigning workloads. 📈
• The collaboration between agents is seamless, mimicking real-world teamwork scenarios effectively. 💡

📚 What we learned

• Advanced techniques for AI task delegation and decision-making. 🧠
• Effective ways to manage and scale multi-agent systems. ⚙️
• Balancing autonomy with oversight for AI in complex tasks. 🔍

🚀 What's next for our AI Agents

• Introducing voice interaction, enabling users to communicate with agents using natural language. 🎙️
• Enhancing agent collaboration to handle more complex, multi-step workflows. 🚀
• Exploring integrations with popular productivity tools like Slack and Trello for seamless task management. 📅

Built With

• nextjs
• python
• react
• tailwindcss
• typescript