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Bayesâ theorem is probably the single most important thing any rational person can learn.
So many of our debates and disagreements that we shout about are because we donât understand Bayesâ theorem or how human rationality often works.
Bayesâ theorem is named after the 18th-century Thomas Bayes, and essentially itâs a formula that asks: when you are presented with all of the evidence for something, how much should you believe it?
Bayesâ theorem teaches us that our beliefs are not fixed; they are probabilities. Our beliefs change as we weigh new evidence against our assumptions, or our priors. In other words, we all carry certain ideas about how the world works, and new evidence can challenge them.
For example, somebody might believe that smoking is safe, that stress causes mouth ulcers, or that human activity is unrelated to climate change. These are their priors, their starting points. They can be formed by our culture, our biases, or even incomplete information.
Now imagine a new study comes along that challenges one of your priors. A single study might not carry enough weight to overturn your existing beliefs. But as studies accumulate, eventually the scales may tip. At some point, your prior will become less and less plausible.
Bayesâ theorem argues that being rational is not about black and white. Itâs not even about true or false. Itâs about what is most reasonable based on the best available evidence. But for this to work, we need to be presented with as much high-quality data as possible. Without evidenceâwithout belief-forming dataâwe are left only with our priors and biases. And those arenât all that rational.
We know the algorithm is dumb and needs massive improvements, but at least you can see us struggle to make it better in real-time and with transparency.
No other social media companies do this.