The price fell and the bill went up
Three numbers a buyer checks this week turned out to be measuring the apparatus rather than the thing bought.
How we Organise
Traffic through one AI gateway grew 59 per cent in July, and the bill went up
- The average price per token dropped 13.6 per cent. Hold June’s model mix constant and that average is flat: the fall came from teams moving work, not from anything getting cheaper.
We tell a client to price a successful outcome and to treat the token rate as one input to it. Over four weeks the two moved in opposite directions. A firm watching only the rate reports a cheaper month in which it paid more. Vercel sells the gateway and values spend at list prices.
How we Build
Measuring benchmark optimisation in speech recognition
Eleven open speech models were probed three ways. Several reproduced the errors in the reference transcripts they were scored against, and the models with the lowest reported error rate did it most. One supplied a number silenced in the audio. On recordings made after the training cutoffs, it faded.
Our position is that a skill carries a suite of its own, in worked examples, properties and scenarios a business expert vouches for. The test asks that the suite exist and take those forms, never where the examples came from. A team assembling them from a public corpus passes the test and has measured the wrong thing, which is what the model already remembers.
How we Assure
Anthropic on widening access to its strongest cyber model
Security scanning on the strongest model opens to enterprise customers and to partner products, which hand back a vulnerability and a patch rather than model output. That is said to be safer than handing over the model.
We ask that anything able to change an agent’s behaviour pass a change review: models, prompts, tools, retrieval corpora, classifiers, machine identities. The patch has no line there. It is code written by a model nobody in the building may inspect, landing in a repository the client answers for.