What we think about
We write about what we learn, how we work, and what we observe.
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Article Fetcher 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.
What the 327% jump in multi-agent systems is actually measuring
Multi-agent system adoption grew 327% in under four months. The number is real. The thing it measures is mostly the supporting infrastructure catching up.
Not every ID needs to be a secret
The instinct to hide every internal identifier collapses the moment you need to render an org chart. We thought about which IDs leak something and which do not.
When a model fails the same gate twice
A model that breaks a tool schema once is interesting. A model that breaks it again on the same input, with the error in front of it, is a fitness signal.
