Agent Harness Hackathon | Win an NVIDIA DGX Spark AI Supercomputer

You get an agent working in an afternoon. Then you point it at something that matters and it can't reach your tools, can't run its own code safely, and can't be stopped before it does damage. Spend a day building one that can do all three.

​📅 Agenda

• 09:00: Doors and check-in open

• 09:00 - 09:45: Breakfast 🥯

• 09:45 - 10:00: Kickoff speech

• 10:00 - 11:00: Workshops

• 11:00 - 14:00: Hacking

• 14:00: Pizza time 🍕

• 14:00 - 17:00: Hacking continues

• 18:00: Project submission deadline ‼️

🧑‍💻 What you are building

A working AI agent, in a day. Pick a job worth handing to an agent, in any field you like, and build the agent that does it. Devtools, operations, data, consumer apps, multi-agent systems: the domain is yours.

A chatbot answers questions. An agent acts on them: it opens the pull request, queries the database, runs the script, sends the message. That is the bar. Bring an idea or pick one up when you arrive, then present your project live to the judges at the end of the day.

🛠️ The tools

You will build on an open-source agent harness, introduced in the morning workshops. A harness is the layer between a model and everything it acts on. It runs the loop your agent works in, sending the model its instructions, calling the tools it asks for, feeding results back, and keeping context and session state across turns. Practically, that means you get:

• Connections to your tools. Any MCP server, including ones behind OAuth, plus built-in tools and web search.

• Sandboxed execution. Agent-written code runs somewhere isolated.

• Human approvals. Pause before sensitive actions until a person signs off.

• Subagents. Delegate parts of a job to other agents.

• Sessions that survive reconnects. A run keeps going through a refresh or a restart.

• Any model provider. OpenAI, Anthropic, Gemini, or any OpenAI-compatible endpoint.

Skip the plumbing and spend the day on the agent itself.

Qodo is an AI code review platform. Its agents review your pull requests against your full codebase rather than just the diff, flag real bugs and breaking changes ranked by severity, and can apply the fix.

OpenAI is providing $50 in credits to everyone who attends, so you are not paying to experiment.

🏆 Prizes

Best Use of the Agent Harness: NVIDIA DGX Spark Personal AI Supercomputer, worth $5,000. Presented by TrueFoundry. For the agent that gets the most out of the harness. What matters is that the harness is doing the work rather than sitting underneath a thin wrapper.

Best Code Quality: Mac Mini. Presented by Qodo. For the team that treats a hackathon repo like real software. Run your pull requests through Qodo and deal with what it finds before you merge. Using Qodo is required for this track.

Best blog post: Keychron keyboard. Write up what you built, how you wired it together, and what broke along the way. Publish it anywhere.

A team can win one track, not all.

💡 Project ideas

Start from one of these, or bring your own.

• Code review agent. Reads a pull request, runs the test suite in a sandbox, and comments on what it found.

• Incident responder. Investigates an alert with read-only queries, then asks a person before restarting or rolling anything back.

• Analytics agent. Answers questions in plain English by writing the SQL itself, running it, and explaining the result.

• Research desk. Sends subagents across the web on a single question and merges what they find, with sources.

• Approval-gated assistant. Drafts the email, files the ticket, or books the trip, and does nothing irreversible until you approve it.

• Untrusted code runner. Executes code submitted by someone else inside an isolated sandbox and returns the result safely.

👇 Details

Teams of one to four. Free to attend. Come on your own and find people there. Your repo needs to be open source.

Bring a laptop, a charger, and ID for venue entry. Food and Wi-Fi are covered.

Open to platform, infrastructure, and backend engineers, anyone working with LLMs, tool calling, or MCP, founders taking an agent prototype further, and anyone who wants to build their first agent without writing the runtime themselves.