We are proud to be the

Gold sponsor

Hack-of-Tomorrow-Hackathon

Explore real use cases of AI, Blockchain and IoT

March 22, 2025

Franklin Templeton Investments, Nowy Rynek, Ul. Przemysłowa 3, 61-579, Poznan, Poland

Schedule

Monday, March 10

Time

Topic

Location

17:00 CET

⁠Introduction to AI Agents | Fetch.ai

Tuesday, March 11

Time

Topic

Location

17:00 CET

Powered Energy Communities | C4E

Thursday, March 13

Time

Topic

Location

17:00 CET

Gameswift workshop

Saturday, March 22

Time

Topic

Location

09:00 CET

Registration and Matchmaking

10:00 CET

Welcome & Official Opening

10:15 CET

Challenges & Mentors Presentation

10:45 CET

Start of Hacking Session

12:00 CET

Keynote Presentations

15:30 CET

Lunch Break

16:30 CET

Keynote Presentations

23:00 CET

Closing the building

Sunday, March 23

Time

Topic

Location

06:00 CET

Opening of the building

10:00 CET

Breakfast

10:45 CET

Completion of Project Work*

11:00 CET

Project Presentations

14:00 CET

Announcement of Winners

Introduction

Fetch.ai’s vision is to create a marketplace of dynamic applications. We are empowering developers to build on our platform that can connect services and APIs without any domain knowledge.

Our infrastructure enables ‘search and discovery’ and ‘dynamic connectivity’. It offers an open, modular, UI agnostic, self-assembling of services.

Our technology is built on four key components:

uAgents - uAgents are autonomous AI agents built to connect seamlessly with networks and other agents. They can represent and interact with data, APIs, services, machine learning models, and individuals, enabling intelligent and dynamic decision-making in decentralized environments.

Agentverse - serves as a development and hosting platform for these agents.

Fetchai SDK – seamlessly integrates your AI Agent into Agentverse and empowers dynamic connectivity with the Fetch.ai SDK

Fetch Network - underpins the entire system, ensuring smooth operation and integration.

ASI-1 Mini - A Web3-native large language model (LLM) optimized for agent-based workflows.

Challenge statement

Unleash your creativity by designing specialised AI Agents in any domain—whether it's Mobility, Smart city, ** Energy**, or Gaming, using any Agentic framework of your choice, register your agents on Agentverse, a dynamic open agent marketplace, where agents seamlessly interact and collaborate to deliver powerful solutions.

Take it a step further by building a personalized assistant that leverages the Search and Discovery feature on (Agentverse.ai)[https://agentverse.ai/]. Your assistant will intelligently connect with other agents to fulfil user needs, orchestrating tasks with precision and efficiency.

Picture a world where users can effortlessly engage with a network of AI Agents tailored to their unique requirements—this is your opportunity to make it a reality.

Are you ready to innovate, collaborate, and automate the future of intelligent systems? The challenge awaits!

What to Build

In this hackathon, participants are encouraged to showcase their skills by building innovative solutions centered around AI Agents. Here's what you'll create:

Specialized AI Agents

Use your creativity to design AI Agents tailored for specific domains or tasks, such as customer support, data analysis, content creation, research assistance, or more. Leverage agentic frameworks like uAgents, LangChain, CrewAI, Autogen, or others to build these agents. Once your agents are ready, register them on Agentverse using the Fetch.ai SDK enabling them to interact with other agents in the ecosystem. Your goal is to contribute to a diverse and robust agent directory.

Personalized Assistant Agent

Build a Personalised Assistant Agent that uses the Search and Discovery feature on Agentverse. This assistant will dynamically connect with the most relevant agents-whether created by you or other participants to fulfil user queries and coordinate tasks efficiently. The assistant should intelligently manage interactions to deliver seamless, user-centric experiences.

Fetch.ai tech stack

Product Overview

Quick start example

This file can be run on any platform supporting Python, with the necessary install permissions. This example shows two agents communicating with each other using the uAgent python library.
Read the guide for this code here ↗

from uagents import Agent, Bureau, Context, Model
    class Message(Model):
        message: str
    
    sigmar = Agent(name="sigmar", seed="sigmar recovery phrase")
    slaanesh = Agent(name="slaanesh", seed="slaanesh recovery phrase")
        
    @sigmar.on_interval(period=3.0)
    async def send_message(ctx: Context):
       await ctx.send(slaanesh.address, Message(message="hello there slaanesh"))
        
    @sigmar.on_message(model=Message)
    async def sigmar_message_handler(ctx: Context, sender: str, msg: Message):
        ctx.logger.info(f"Received message from {sender}: {msg.message}")
    
    @slaanesh.on_message(model=Message)
    async def slaanesh_message_handler(ctx: Context, sender: str, msg: Message):
        ctx.logger.info(f"Received message from {sender}: {msg.message}")
        await ctx.send(sigmar.address, Message(message="hello there sigmar"))
        
    bureau = Bureau()
    bureau.add(sigmar)
    bureau.add(slaanesh)
    if __name__ == "__main__":
        bureau.run()