We are proud to be the

Gold sponsor

of

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

View Details

Schedule

Monday, March 10

Time Topic Location
17:00 CET Introduction to AI Agents | Fetch.ai Join

Tuesday, March 11

Time Topic Location
17:00 CET Powered Energy Communities | C4E Join

Thursday, March 13

Time Topic Location
17:00 CET Gameswift workshop Join

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. Your assistant will intelligently connect with other agents to fulfil user needs, orchestrating tasks with precision and efficiency.

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.

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.

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()

Important links

Judging Criteria

Prizes

  • Winner: $1000
  • Second Place: $600
  • Third Place: $400

Collaborators

Judges

Grzegorz Sikora
CIO and co-founder C4E

Maria Minaricova
Director of Business Development at Fetch.ai

Marcin Cichocki
Tech architect at Gameswift

Mentors

Grzegorz Sikora
CIO and co-founder C4E

Maria Minaricova
Director of Business Development at Fetch.ai

Marcin Cichocki
Tech architect at Gameswift