Chat cost is quadratic, not linear, because every turn re-reads the whole history: total ≈ S × N(N+1)/2. At ~500 tokenThe chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.Full definition → an exchange, 30 messages burn 232K tokens and message 30 costs about 31x what message 1 did.
One developer's tracking found 98.5% of his tokens went to re-reading history and 1.5% to producing output. The fix is a fresh chat every 15-20 messages, seeded with a summary you asked Claude to write first.
Batching beats splitting. Three prompts mean three context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → loads; one prompt with three tasks loads context once, and the answers are often better because the model sees the whole job at once.
Optional features tax every response whether you use them or not — web search, connectors, Explore mode, extended thinking. The default should be off, switched on deliberately when a first attempt falls short.
Usage runs on a rolling 5-hour window rather than a midnight reset, so spend decays as the day goes on. Burning the whole allowance in one morning session leaves most of the day's capacity unused.
Terms in this piece · Glossary
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
Why it matters
Nine concrete tactics to cut Claude token usage and stop hitting limits — prompt editing, batching, context discipline. Practical and immediately applicable if you keep slamming into usage caps mid-task.
Key quotes
“Recently I realized that Claude doesn't count the number of messages. it counts tokens.”
“One developer tracked his usage and found that 98.5% of tokens were spent on re-reading the history. Only 1.5% went toward actually outputting the result.”
“Rule: if you didn’t turn this feature on intentionally, turn it off.”
“Choosing the right model is the most important decision you make every day.”
