February 1, 2025
Michigan State University
08:00 EST
Check-in and Breakfast
Michigan State University
10:00 EST
Opening Ceremony
Michigan State University
12:00 EST
Hacking Begins
Michigan State University
13:00 EST
Intro to Fetch.ai Tech
Michigan State University
14:00 EST
Lunch
Michigan State University
15:30 EST
Learn how to best utilise Fetch.ai to Build Solutions
Michigan State University
24:00 EST
Midnight Snack
Michigan State University
08:00 EST
Caffeine Recharge
Michigan State University
12:00 EST
Hacking Ends
Michigan State University
12:00 EST
Brunch
Michigan State University
13:00 EST
Hacker Demos
Michigan State University
15:00 EST
Closing Ceremony
Michigan State University
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.
Challenge statement
Unleash your creativity by designing specialised AI Agents in any domain—whether it's Finance, Healthcare, Education, or Social Impact using any Agentic framework of your choice, register your agents on Agentverse, a dynamic central directory 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. 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!
Additional Information:
Pre-Hackathon Workshop Presentation
Please submit your projects on Devpost
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()
Examples to get you started:
Judging Criteria
Winner
$1000
Fetch.ai Nexus Prize
Second Prize
$500
Agentverse Champion
Third Prize
$500
Fetch.ai AI Agent Trailblazer Prize
Judges
Sana Wajid
Senior Vice President
Mark Losey
CTO at FlockX
Devon Bleibtrey
CEO at FlockX
Abhimanyu Gangani
Developer Advocate
Kshipra Dhame
Developer Advocate
Mentors
Tanay Godse
Developer Advocate
Parth Joshi
Developer Advocate
Aneil Shah
Developer Advocate
Ready to get started with Fetch.ai Platform?