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April 11, 20265 min read

A community growth hack: AI + social listening for GeoMinesweeper

A small case study — using AI and social listening to pull real traffic and users into GeoMinesweeper. Value first, promotion second.


A case study on using AI and social listening to pull traffic and users into GeoMinesweeper.

Context and pain point

I've been building a small Minesweeper project (geominesweeper.com). Exploring the community on Reddit, I noticed a recurring pattern — posts shaped like:

"I'm stuck here. What should I do next?"

People share a screenshot of their board and ask what to play next.

Reddit post: I'm stuck here

The problem: both the asker and the answerers tend to explain in plain text or rough hand-drawn overlays. Something like this:

Text-based explanation

Hand-drawn explanation 1

Hand-drawn explanation 2

The friction:

  • For beginners these explanations are hard to picture — pro players usually solve their own boards and don't post for help.
  • A static board only carries you so far. What comes next depends heavily on which cells open up after the first move.

If you could:

  • Recreate the board
  • Highlight the logic
  • Replay the moves step by step

then understanding the solution would be much easier.

The idea

I put together a simple workflow:

Workflow diagram

It's not fully automated yet — there's a human in the loop. End-to-end automation is possible in theory, but for an experiment manual is fine as long as it stays under 15 minutes per run.

If it works — users get real value, traffic shows up — I'll think about automating the whole thing into a flywheel.

The solution

Social listening

  • Poll RSS feeds frequently for the freshest signal.
  • Use an AI model to classify which posts are "need help" posts.

Recreate the board

  • I built an admin tool: upload the screenshot, detect the grid, rebuild the board state.
  • The image processing is basic — grouping pixels by dominant color. Cells like 1, 2, 3, flag, and blank each have distinct color profiles, so no OCR was needed.

Admin tool — detect the grid from a screenshot

Solver

  • A BFS pass to "scatter" mines into the unrevealed cells.
  • Obviously there are many valid solutions and I can't know the user's real mine map, but I only need one consistent layout for the demo.

End result: the board recreated from the user's original screenshot.

Recreated board

Live URL | Replay URL

A note on the replay: I added an annotation tool that makes the reasoning steps visible — for example, showing "if this cell is a mine, then that one is safe."

Output

When I reply on Reddit, it can be as simple as:

I recreated your board and made a replay explaining the logic here: [link]

The asker can watch the replay and follow the logic:

Reddit reply with the replay link

…then try to solve the board faster than I did:

User tried solving the board again

…and they may poke around the rest of the site out of curiosity:

Exploring other features on the site

Why it worked

A few factors I think made this work early on:

  1. Real need — the poster is genuinely stuck, and the follow-up actually solves their problem.
  2. Timing — replying within the first 15 minutes of a post gets disproportionate attention. That's the payoff from social listening.
  3. Visual explanation — a replay is dramatically clearer than a text description or a rough sketch.

Sample size is still small, so I'd only call this an early signal.

Closing thought

  • The workflow forms a natural growth loop.
  • People post questions every day → there's a steady reason to pull traffic every day — a kind of content strategy.
  • The important part: value first, promotion second.
Tags
#growth