# Interest in Leetcode, but for Rationality?

the following is motivated by:

*   [Self-Improvement or Shiny Distraction: Why Less Wrong is anti-Instrumental Rationality](https://www.lesswrong.com/posts/uFYQaGCRwt3wKtyZP/self-improvement-or-shiny-distraction-why-less-wrong-is-anti)
*   [The Martial Art of Rationality](https://www.lesswrong.com/s/5g5TkQTe9rmPS5vvM/p/teaxCFgtmCQ3E9fy8)

I've been a long time lurker on Less Wrong and I've noticed the recurring criticism that despite its focus on rationality, the community lacks structured training to develop practical rationality skills. Eliezer Yudkowsky talks rationality as a martial art, because it's something that can be trained and refined through deliberate practice. But where is our dojo?

A model that comes to mind is a website like LeetCode, where programmers can solve coding challenges, share solutions, and see how others approach the same problems. LeetCode can sometimes encourage overfitting to specific problem types so it's not a perfect analogy. The community driven aspect would interesting to me as you can see how other people approach the problem. Could something similar be adapted for rationality?

Imagine a platform where, instead of solving coding puzzles, users engage with problems designed to train rational thinking. Here are a few types of problems that might fit:

1.  **Cognitive Bias Detection:** Users could review novel, real-world scenarios and try to identify what cognitive bias or logical fallacy is present. The goal would be to train pattern recognition for biases without simply memorizing common examples. For instance, a scenario might subtly include a case of *confirmation bias* or *anchoring*, and users would need to spot it.
2.  **Calibration Training:** One of the most important skills in rationality is aligning your confidence with reality. For each problem or scenario, users could submit a confidence interval along with their answer. This serves as a double-training: users practice assessing their certainty, and over time, they get feedback on how well-calibrated they are.
3.  **Bite-Sized, Practical Challenges:** The focus should be on small, actionable exercises rather than lengthy theoretical discussions. For example, a problem might ask users to predict an outcome based on limited data, forcing them to confront the common pitfalls of overconfidence or representativeness heuristics.

This kind of platform could be a place where people practice and refine their skills, not just absorb entertaining ideas in way that some say is weakly applicable. 

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/f42279b7d7f60307e1fdf0664a2747bb67b5e6a092b69e30.png)

"identify the bias" type problem for a prototype i'm working on

I have a few years of experience in Software Engineering (backend and ML) and have been thinking about building a tool like this for my own use. However, if others would find it valuable, I'd be open to expanding it into something that the wider community could use as well. It could even present an opportunity to create a sustainable project with some potential financial benefits along the way. I'd love to hear if there’s interest in such a platform and what features might be most helpful to include.