Blunders.ai
AI chess training powered by your own games
Most chess training platforms rely on generic puzzles and lessons that don't reflect a player's real weaknesses. Blunders.ai analyzes each player's own games, identifies recurring mistakes, and converts them into personalized training, making practice more relevant and effective
Most chess training platforms rely on generic puzzles and lessons that don't reflect a player's real weaknesses. Blunders.ai analyzes each player's own games, identifies recurring mistakes, and converts them into personalized training, making practice more relevant and effective
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Hey, just wanted to say — your product looks really impressive. It feels useful, clean, and like something that can actually help people solve a real problem.
I’m building Everyday Tiny Tools — a marketplace for small useful web tools, mini apps, calculators, generators, AI tools, productivity helpers, and simple utilities.
The idea is to give independent creators a real place to showcase their tools, get discovered, and maybe even earn from them.
If you’ve built something small and useful, I’d love to invite you to list it here: EverydayTinyTools.com
Tools can be listed as free, or as a simple one-time purchase through the platform.
And if you have any questions, feel free to reach out anytime: nuchem@lightboltlab.com
Really like what you’re building — wishing you a lot of success with it.
3 Comments
Love this product!
Personalizing training to your own games instead of generic puzzles is the right product instinct because the failure pattern is already in the data. You don't need to guess what someone struggles with, you can just look at what they keep doing wrong under pressure.
The hard part of this category is usually getting people past the ego barrier of watching themselves lose repeatedly. How are you framing that experience so it feels like insight rather than punishment?
This is a strong direction because it replaces generic “difficulty-based practice” with “behavioral feedback loops from your own history.” In skill-learning products, personalization only becomes meaningful when it is tied directly to recurring failure patterns rather than abstract ratings.