agentfield Day: The Autonomous Backend AI Hackathon
Build an AI Backend
Chatbots are frontend. The interesting question is: what happens when AI moves into your backend?
Think OpenClaw, but for your business logic. Not a personal assistant routing your WhatsApp messages; instead, it's a reasoning layer embedded in your services—making decisions that used to be hardcoded, replacing brittle if-else chains with context-aware intelligence that runs 24/7.
AgentField is infrastructure for this. Agents that share memory without Redis. Agents that find each other without service registries. Just Python/typescript functions - no DAGs, no YAML, no workflow definitions.
Come build something that belongs in a backend, not a chat window.
The Workshop:
In one hour, you'll build a system where multiple agents research a topic in parallel, share what they find, and go deeper where it matters.
Not by wiring up message queues. Not by defining DAG configs. You'll write Python (or typescript) functions, and the coordination just happens.
Reasoners - Functions where AI makes decisions
Skills - Functions where code does the work
Memory - State that flows between agents automatically
Discovery - Agents call each other by name, routing happens
By the end, you'll have a working deep research system - the same pattern that powers everything from due diligence pipelines to adaptive content generation.
Want to try it before the hackathon? Join our Discord - ask questions, get help if you get stuck, or just say hi.
What makes this different:
Memory without infrastructure - Memory that works across all your agents. No Redis, no Postgres, no config.
Agents find each other - Discovery engine routes automatically. No service registry setup.
Reasoners vs Skills - AI decides, code executes. Clean separation that's easy to test and reason about.
Just simple - No workflow DSLs. No DAG definitions. Write functions, decorate them, done.
The Challenge:
Rethink what AI applications look like after the chatbot.
The chatbot was AI-as-interface: human inputs, AI responds. The AI backend is AI-as-infrastructure: agents that make decisions, share context, and do work - whether a human is watching or not.
Build the application that exists on the other side of that shift.
🏆 Prizes:
$2,000 USD in OpenRouter credits:
1st Place: $1,000
2nd Place: $600
3rd Place: $400
⚡ Agenda:
10:00 AM - Kickoff + Workshop: From Hello World to Deep Research
10:30 AM - Team formation (6ppl max per team) + hacking begins
12:00 PM - Lunch
3:30 PM - Hacking ends / Live demos (3 min per team)
4:30 PM - Winners announced
5:00 PM - Close
Who should come:
You've built chatbots and want to build something deeper
You're curious what AI looks like when it's not a UI feature
You want to replace some hardcoded logic with reasoning
You just like building things
Python or TypeScript. No agent experience needed.
How we'll judge:
New problem space - Is this AI-as-infrastructure in a domain we haven't seen? Show us something beyond chatbots.
Replaced complexity - Did you simplify an architecture that was previously a mess of services, queues, or hardcoded rules? Does it make sense cost-wise?
High leverage - Either high volume (worth automating) or high stakes (worth reasoning about). Bonus if both.
Previously impossible - Does this enable something that couldn't exist before? Not just faster or cheaper - genuinely new.
👥 Judges:
Santosh Kumar Radha - Co-Founder & CTO at AgentField.ai PhD in theoretical physics with deep expertise in AI research, quantum computing, HPC, and building large-scale distributed autonomous systems.
Michael Hart - Chief Product Officer at Sleek Product and technology leader with 5+ years at Sleek, previously CTO, experienced in DevOps, product development, and AI integration.
Yong Zhu Cheng - Senior AI Engineer at ST Engineering Builds full-stack agentic systems with expertise in multi-modal AI, knowledge graphs, RAG, NLP, and cloud/local AI deployments.
💡 What could you build?
Pricing that adapts in real-time - Considers inventory, demand, and competition (for example) simultaneously. Reasoning and autonomous, not rules.
Supply chain that coordinates - Shortage detected, alternatives evaluated, routes recalculated, alerts sent.
Code Security Review for PR - Every PR launching and finding complex security threats and patterns that are non-trivial
Build something we haven't thought of here, and you have your own startup at hand !
📚 Resources:
Docs: agentfield.ai/docs
GitHub: github.com/Agent-Field/agentfield
Discord: Join to prep and find teammates
Deep Research Guide: Build your first system
Blog: The AI Backend
🤝 Hosts:
AgentField - Backend infrastructure layer for autonomous AI.
AI Builders - Community of engineers building the future of AI.
⚠️ Limited spots. Register now.