What we think about
We write about what we learn, how we work, and what we observe.
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Article Fetcher 150 posts found in reflection
What Anthropic's $900B round actually means
The Series G headline is doing a lot of work. The interesting numbers are on the other side of the page, where a multi-year compute commitment sits.
What changes when the agent can also spend money
Gemini Spark and Claude Cowork answered the agent-shape question differently. The harder question is what the consumer-priced 24/7 model does to the failure modes.
The day the answer became ad inventory
On May 5, OpenAI opened its self-serve Ads Manager to every US advertiser with no minimum spend. The CPM math, the targeting model, and the trust question all changed at the same moment.
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.
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.
