Topology Go: Baduk Beyond Flat Boards

What the company appears to be: Topology Go: Baduk Beyond Flat Boards is a self-reported 3D, AI-powered multiplayer game that allows players to play Go on non-Euclidean topological surfaces such as cylinders, tori, and Möbius strips. The author describes it as a fully playable game with online multiplayer, AI opponents, replay, import/export, and AI-assisted post-game analysis.

What changed: The project was built during OpenAI Build Week as a hackathon submission. It represents an experimental approach to board game design using topology and AI assistance for development.

The single most important open question: Is there any evidence of traction, revenue, or customer adoption beyond the author's own account? The description states no commercial data exists.

• The description states that Topology Go is a "fully playable Go game built around three topologies"
• It supports cylinder (left-right edges connect), torus (both pairs of opposite edges connect), and Möbius strip (one pair connects with reversed orientation)
• Players can play locally, create online rooms, face an AI opponent, import/export games, replay matches, and use AI-assisted analysis
• The main interaction happens on a flat grid that visually repeats continuously through connected directions
• It supports switching between flat board and corresponding 3D surface views
• AI analysis displays candidate moves and evaluations on both views

• The description states the project is "A 3D, AI-powered multiplayer game that turns abstract topology into intuitive strategy"
• It positions itself as an experiment in "turning abstract topology into intuitive strategy" rather than a commercial product
• The author claims to have "turned an unusual idea into a game that I genuinely enjoy playing within a single Build Week"
• The project is described as having evolved from "a geometric demonstration" into "a complete, playable game"
• No evidence of pricing, monetization or commercial positioning beyond the author's own account

• Not evidenced. The description does not identify specific customer segments or personas
• The author states that players can play locally, create online rooms, and face AI opponents
• No evidence of target demographics, user types, or customer profiles
• The project appears to be primarily for Go enthusiasts interested in experimental game design

• Not evidenced. The description does not contain any information about pricing, monetization, revenue streams, or business model
• The author states this is a hackathon submission and no commercial data exists
• No evidence of paid features, subscriptions, or transactional models

• Built with: cloudflare, codex, durable, gpt-5.6, javascript, katago, objects, openai, tensorflow.js, three.js, websockets, workers
• The author reports using AI tools (ChatGPT and Codex) for implementation and debugging
• The project was built during OpenAI Build Week as a hackathon submission
• Uses KataGo for AI opponent
• Supports online multiplayer through websockets
• Implements 3D visualization with three.js
• Includes import/export functionality

• Not evidenced. The description contains no information about users, customers, revenue, or adoption metrics
• The project is described as a single-week hackathon effort
• No evidence of user engagement, retention, or usage data
• The author states they "genuinely enjoy playing" but provides no external validation of player interest

• Not evidenced. The description does not mention competitors or market positioning relative to other Go games or topology-based applications
• No information about existing alternatives or competitive landscape
• No evidence of market analysis or differentiation strategy

• Unproven commercial viability: The project is described as a hackathon submission with no evidence of traction, revenue, or customer adoption
• Limited scope: Built for a single week during a hackathon; no indication of long-term development plans or scalability
• Self-reported only: All information comes from the author's own account without independent verification
• Technical uncertainty: Relies heavily on AI tools for implementation with no evidence of code quality, performance, or maintainability
• Niche appeal: The combination of Go + topology + 3D visualization may limit target audience size

1. What specific user feedback have you received about the gameplay experience?
2. How do you plan to monetize this product if at all?
3. What is your roadmap for development beyond the current prototype?
4. Have you conducted any user testing with non-expert players?
5. What are the technical limitations of the current implementation that would prevent scaling?
6. How does the AI opponent perform against human players in terms of skill level?
7. What is your strategy for attracting and retaining users?