Site and content updates 17/09/2026
Site and content updates 17/09/2026
Hi all,
Thanks for subscribing to p→q, here is a recap of the recent activity on the blog.
Updates
- Each Series now has a small blurb so you'll know what you're about to get into.
- Added the option to subscribe to very spaced-out email updates from the blog (which I guess you know as you're getting one!).
- In case you're more comfortable reading things on Medium, I've started a mirror for the blog content there. Content will usually be pushed to Medium in a ~2 weeks delay, but everything will get there eventually. You can find me at @yaronassa there.
Upcoming content
- Next in line - a 3 part series on the old a new riddles of induction, and what they could teach us on testing in a age of GenAI.
Recent articles
If GenAI knows anything at all, it knows you've already lost the lottery
Can Generative AI be said to know anything? We'll answer that through the (broken) definition of knowledge, the epistemological concept of sensitivity and a detour into philosophy of law. This time it's all philosophy, no action items.
The Rat in exploratory testing
In this piece we'll take a walk on edge of rationality itself with one of the least stable philosophers from the last 50 years - Nick Land. We'll explore his concept of fanged noumenon outside the boundary of rationality, and how it can vindicate the notion and value of exploratory testing. Oh, and there will be rats.
Testing saints
Being a more professional tester is good. Being the very best should be even better, right? Surprisingly the answer is a resounding NO. Today we'll use Susan Wolf's wonderful paper "Moral Saints" to examine why being a testing saint is a horrible, horrible idea.
If P then Q(A). But turns out P(laning) is trickier than you thought
In this piece we'll have some nerdy fun exploring a cool POV connecting the surprise exam paradox to Godel's incompleteness theorem, then using that to draw insights for project risk management processes. After the fun part, we'll sprinkle in additional pessimism through some empirical data making everything concrete.
