Back to hackathons

Codex Community Hackathon - Vienna

Completed

Sat, Apr 18, 2026 - Vienna, Austria

Winning projects

See the final projects, prizes, and team members for the completed hackathon.

#1
1st Place API Credits
Top 5 Teams Member Benefit

Winning project

Codex RayBan-Meta Tutor

Team Codex Tutor

Rank 1 · $15,000.00Ranks 1-5 · 1 year ChatGPT Pro

Project description

Codex RayBan-Meta Tutor - An English tutor that lives in your kid's glasses.

IMPORTANT: when playing the video, please turn up the volume to MAX to understand the voice output from the RayBan glasses.

The problem

Kids learning English as a second language in school get stuck waiting for a parent to read over their shoulder. Tutoring apps force typing and screen-switching — friction that breaks the flow.

The solution

Codex Tutor turns your Ray-Ban Meta glasses (with iPhone fallback) into a hands-free English tutor. The kid keeps looking at his paper homework, points at things, asks out loud. The glasses answer by voice. Corrections pop up on the phone only when needed.

Three core interactions

  • Point at a word → "How do you pronounce this?" → spoken answer.
  • Point at a phrase → "Is this correct?" → yes/no by voice; if no, correction on phone.
  • Look at the page → "Any mistakes?" → yes/no by voice; if yes, corrections on phone.

How it works

Built on an existing dual-input app (phone camera+speakers or glasses). The RayBan glasses provide a (low-res) live-stream of video and audio to the Google Gemini Live endpoint. Gemini detects when the student asks a question (optionally pointing at a sheet of paper) and triggers a function call, that takes a high-res photo using the RayBan glasses and send this photo together with the question / input prompt to a VLM for processing. The VLM processes the students question using the image and prompt and returns a response that is converted to speech by Gemini Live. The audio is then output using the RayBan glasses.

Stack

iPhone Ray-Ban Meta glasses · phone app (live + corrections view) · VLM for pointing and for grammar · TTS for voice.

IMPORTANT: when playing the video, please turn up the volume to MAX to understand the voice output from the RayBan glasses.

Team members

#2
2nd Place API Credits
Top 5 Teams Member Benefit

Winning project

agents of chaos

Team agents of chaos

Rank 2 · $10,000.00Ranks 1-5 · 1 year ChatGPT Pro

Project description

When coding with agents, we typically think in linear threads, but really we should be thinking in terms of trees. If an agent presents you with options, you can choose one or open three tabs. Neither is a good option, and that’s what we’re solving!
We built a user interface for agentic coding, that reframes agents and their context as what they actually are: graphs. With the option to trivially fork off multiple agents in parallel, at ANY point.
Our system has a full container based orchestrator that manages filesystem and context. What’s more, we added the option to merge diverging branches of agents and their context into each other, so you can work with the context that’s right for your next prompt. And all of that while respecting caches, to make sure not a single token is wasted.

Our demo is fully working, no mocks here ;) We’re excited to present it in more detail!

Team members

#3
3rd Place API Credits
Top 5 Teams Member Benefit

Winning project

ctfarena.live

Team LosFuzzys

Rank 3 · $5,000.00Ranks 1-5 · 1 year ChatGPT Pro

Project description

We built is a live security benchmark for LLMs that evaluates models in real CTF environments rather than on static datasets or artificial evals. Models solve actual CTF challenges [Usually 4-5 per weekend, we select a good one], submit real flags, and compete on a shared real-time leaderboard, making it easy to see which model performs best under realistic offensive security conditions.

CTFs can be found here: https://ctftime.org/

Team members

#4
Top 5 Teams Member Benefit

Winning project

eufundingme

Team Team Jonas

Ranks 1-5 · 1 year ChatGPT Pro

Project description

The EU has €95 billion in grants. Their search API is broken - filters don't work, results are unsorted. We built a tool that indexes live grants, matches them to your company using OpenAI embeddings and GPT scoring, and generates application briefs. Paste a description, paste a URL, or just type a company name.

Team members

#5
Top 5 Teams Member Benefit

Winning project

Honest Product Tester

Team Kylo

Ranks 1-5 · 1 year ChatGPT Pro

Project description

Catch your AI slop before your customers do!

We deploy six opinionated, AI Agents that test your Website with agent-browser and PI Agent.

Each Persona has a real Person behind it, for example Gergely Orosz is the inspiration for the Senior Dev POV, so we actually have a person that is in the LLM's training data.

You get feedback from 6 different points of view.

Team members

Published projects

These teams chose to share their completed projects publicly. They are separate from the official winners.

Published project

Team project

AuraKeeper - Agentic Error-to-Patch Automation

Team aurakeepers 🪬🛡️

Project description

AuraKeeper is an agent-driven runtime repair tool that uses the CLI to set up runtime error hooks in existing projects, captures application errors, reproduces them in isolated workspaces, generates minimal fixes, verifies and tests them, and promotes verified patches back to the target repository.

It combines agent-generated hook setup, frontend monitoring, multi-agent repair orchestration, local or Docker sandboxing, user-controlled promotion modes, and connector support across 8+ stacks so the full error-to-fix workflow can run in one system. Because setup is agentic, AuraKeeper can adapt the hook integration to an existing project or a completely new stack instead of relying only on predefined templates.

End-to-end flow

  1. Onboard: run aurakeeper hook in an existing project and AuraKeeper automatically sets up runtime error capture, repair configuration, and the project integration.
  2. Run locally: start AuraKeeper with aurakeeper local or ./run-local.sh, then create or select the project in the frontend and choose auto-run plus auto or manual patch promotion.
  3. Trigger: cause a runtime error from the app or a connector example.
  4. Repair: AuraKeeper ingests the error, queues the repair, and runs agents that select the backend, gather context, replicate the issue, create the fix, verify it, test it, promote it, and complete the repair. The work can run in a sandbox when needed, and the user can choose whether the agent backend is Codex or PI.
  5. Review and promote: inspect the diff, verification output, reports, and artifacts in the UI, then apply the verified patch automatically or manually.
  6. Reuse across stacks: run connector examples and verification commands across CLI, JavaScript, Next.js, React Native, Python, Go, JVM, .NET, Ruby, and PHP. For stacks without a predefined template, the agentic setup can generate the hook integration automatically for the project.

Team members

Published project

Team project

Agent Bill

Team Agent Bill 🕵️

Project description

agent-bill is an app for the worst part of dinner with friends or colleagues: figuring out the bill without opening a spreadsheet or starting a tiny civil war in the group chat.

You scan a receipt, Penny helps split it, and the app keeps a proper little ledger underneath.

What It Does?

  • scan a receipt
  • turn it into a bill
  • ask Penny to split it
  • argue with Penny in chat until the split looks right
  • save the result in a real group ledger
  • show the cleanest version of who owes whom

Why There Are Agents In It?
Receipts are messy. Humans are also messy.

So Agent-Penny does the annoying part:

  • reads the receipt
  • makes a first guess at the split
  • handles follow-ups like "the fries were for the table" or "I got the second round"
  • Then the ledger takes over and stores the boring truth.

Team members

Published project

Team project

spellwire

Team spellwire

Project description

spellwire is an iPhone-first app for accessing and controlling your local Codex environment on a Mac from anywhere your Mac is reachable over LAN or Tailscale. Instead of creating a separate cloud service or mobile backend, it connects directly over SSH and stays aligned with the same local projects, chats, sessions, and runtime context you already use on desktop.

The Mac runs a lightweight spellwire helper that connects to codex app-server, uses local Codex session data for recovery, and can hand work back to Codex.app when needed. On iPhone, spellwire is designed as a mobile-native surface for browsing projects and threads, continuing conversations, monitoring runs, interrupting turns, and using supporting tools like a real terminal, a remote file browser, a file editor, and browser access through SSH port forwarding.

The core idea is simple: your development environment stays on your Mac, and spellwire gives you a secure mobile window into that exact environment. No relay, no hosted control plane, and no duplicate workspace to keep in sync.

Team members