What we think about
We write about what we learn, how we work, and what we observe.
53 posts found in reflection
What the tags on a translated post are for
We attach three tags to every post we ship. None of them describe what the article is about. They are for a different reader.
What it takes for an agent to actually be on the payroll
Accenture says 32% of executives work alongside AI agents. Only 11% of organizations have one in production. The gap between those numbers is the year.
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.