Adam Sand explains that AI tokens are essentially words, and every step costs them: your prompt, the model's reasoning, checking the system message, and the response it generates. A CRM example shows how reporting new contacts and pipeline updates burns tokens in both thinking and output phases.
What you need to know about tokens is that a token's a word, okay? And so you say something to your AI and now every conversation starts with that, but then it has to think about what it's gonna say back. It's gonna reason, it's gonna say, okay, what do they say? And it's gonna check that against the system message and it's gonna figure out what tools it has access to and then it's gonna decide what to do and that all costs tokens. But then there's a response. So you might say, hey, how's the day starting in our CRM? It's gonna reason and think and work through your CRM and then it's gonna respond and say, we got 5 new contacts, we got 2 deals that Mark Close lost. We got 1 new deal that's created and 1 deal that went to contract sent. So we know how much our roofing pipeline is generated today. That's its response, and that also burns tokens.
