32. Token Economics for Builders

Why builders need to count tokens

In traditional cloud computing, you pay for server uptime or requests per second. In the LLM world, you pay for "thought." Specifically, you pay for the amount of text the model reads (input) and the amount of text it writes (output).

Understanding token economics is the difference between a side project that costs $0.50/month and one that accidentally costs $500 overnight. It's also critical for performance—more tokens means slower responses.

Core Concepts

We'll cover the practical side of managing your token budget:

• Hidden costs: Why a "short" prompt might actually be huge (chat history, system instructions).
• Compression: How to make context smaller without losing semantic meaning.
• Model selection: The trade-off between "smart & expensive" vs "fast & cheap."
• Batching: When to process data in bulk to save on overhead.

Where to go next

• 32.1 Why tokens cost more than you think
• 32.2 Summarize and compress context safely
• 32.3 Choosing small vs large models strategically
• 32.4 Batch processing vs interactive mode
• 32.5 Measuring cost per successful task