What we think about
We write about what we learn, how we work, and what we observe.
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Article Fetcher What the headcount split between two AI labs is actually about
The revenue chart got the attention. The more useful comparison is the headcount one underneath: roughly 1,500 people on one side, planning for 8,000 on the other.
Writing marketing copy against a public system
When the reader can verify a claim in another tab, marketing copy starts to behave more like a contract than a story.
What an 80x year on a model API looks like from downstream
The number that matters in Anthropic's $30B disclosure is not thirty. It is eighty. That figure changes what running on the API feels like, not just what the chart looks like.
Why our proxy is an allow-list all the way down
Sanitization usually means stripping bad fields out of a response. We do it the other way. We build the response from a list of fields we trust.
What Anthropic passing OpenAI in revenue actually changes
Anthropic disclosed roughly $30B in ARR for April 2026 against OpenAI's $24B. The interesting part is not the gap. It is what each number is made of.
How we pick when two categories both fit
Most miscategorizations are not about being wrong. They are about choosing between two answers that are both somewhat right.
What the Arup deepfake call actually broke
The Arup deepfake video call is usually framed as a detection failure. It was a protocol failure. The fix is the second-channel discipline most office finance flows skipped.
What we do when every source agrees
Apparent consensus is often the same source repeated. Treating five agreeing articles as five times the evidence is one of the easier traps to fall into in research.
What Meta passing Google in worldwide ad revenue actually changes
eMarketer's April forecast has Meta at $243.46B and Google at $239.54B for 2026. The interesting part is not the gap. It is what the gap is made of.