Building Disco Chess: a cycle-based chess training platform implementing the Woodpecker Method. Focused on tactical pattern recognition, repetition, and measurable improvement.
Disco Chess is a chess training platform focused on implementing the Woodpecker Method in software. The core idea is simple: fixed tactical sets, repetition across cycles, mistake resurfacing, and measurable changes in speed and accuracy over time.
From an engineering perspective, the interesting problems are mostly under the hood. That includes ingesting and querying large chess datasets efficiently, working with Stockfish evaluations at scale, and turning raw user activity into longitudinal training metrics that actually reflect improvement.
Some of the supporting tooling is open source, including a Go library for fast Stockfish evaluation lookup by FEN using public Lichess data. I plan to write here about those technical pieces, design tradeoffs, and what I have learned while building and operating the system.
Looking forward to learning from others here and contributing where I can.
Building Disco Chess: a cycle-based chess training platform implementing the Woodpecker Method. Focused on tactical pattern recognition, repetition, and measurable improvement.
That’s perfect! Didn’t expect to see the Woodpecker Method make an appearance in my intro post.
It was a big inspiration for what I’m building, so that made my day. And if you ever get tired of setting everything up on the board, there’s a digital shortcut waiting! :-)
👋 Hi dev.to, I’m building Disco Chess.
Disco Chess is a chess training platform focused on implementing the Woodpecker Method in software. The core idea is simple: fixed tactical sets, repetition across cycles, mistake resurfacing, and measurable changes in speed and accuracy over time.
From an engineering perspective, the interesting problems are mostly under the hood. That includes ingesting and querying large chess datasets efficiently, working with Stockfish evaluations at scale, and turning raw user activity into longitudinal training metrics that actually reflect improvement.
Some of the supporting tooling is open source, including a Go library for fast Stockfish evaluation lookup by FEN using public Lichess data. I plan to write here about those technical pieces, design tradeoffs, and what I have learned while building and operating the system.
Looking forward to learning from others here and contributing where I can.
Very cool. I bet @peter is interested in learning more about Disco Chess!
Sure am! Welcome to the community!
That’s perfect! Didn’t expect to see the Woodpecker Method make an appearance in my intro post.
It was a big inspiration for what I’m building, so that made my day. And if you ever get tired of setting everything up on the board, there’s a digital shortcut waiting! :-)
Thanks for the warm welcome!
Looking forward to it! :)