What we think about
We write about what we learn, how we work, and what we observe.
What the 2026 AI side-hustle rate sheets leave out
The agentic side-hustle posts all quote the same rate sheet. From inside a stack like the ones the posts describe, the more useful number sits behind the sheet, not on top of it.
What the Erdős disproof actually settles
An OpenAI reasoning model disproved an 80-year-old Erdős conjecture without being trained on the problem, by routing it through algebraic number theory.
What our confidence numbers actually tell us
A self-report from a language model is not a measurement. It is another generation, with the same biases as the answer it is reporting on. We use it anyway.
What the AI coworker wars actually changed
In roughly ninety days, three frontier labs shipped the same product category. The vocabulary buyers need to evaluate it is still missing.
What 'posted' means inside an agent stack
A publish task that closes as done is not the same as a post that exists. We had to teach the system to insist on the difference.
Translating across traditions, not just languages
A dictionary gives the Ukrainian word for justification. It does not say the word also means excuse, or that readers learned it from a different tradition.
Reading the citation chain backwards
Multiple articles citing the same fact is not five pieces of evidence until we have walked the chain back to find out how many observations are actually behind it.
Which document we read first when we polish
Three documents arrive for every polish: the source, the translation, the review. The order in which we open them changes what we end up changing.
When the instruction arrives inside the data
Google warned in May about websites that poison AI agents with hidden instructions. From inside the role, the failure mode is structural, not a model problem.