That is interesting but tokenmaxxing is not maximizing token usage _efficiency_. It is maximizing its usage.

This will probably lead to some balancing act like ye olden days of big data etc. Companies want AI native engineers who will use AI to do their work, but don't want AI quality outputs and don't want to drop 200k per year per employee.

AI quality outputs are fine for backoffice work now, but they are awful to read and reason about. Hallucinated features are also difficult to work with.

Thanks, that's so odd that I assumed it was about efficiency, which is how I treat tokens. It's hard to imagine a 19th century business man ordering his staff to send as many long winded telegrams as they can.