Token Economics: Managing Cost and Value in LLM and AI Applications

A practical introduction to tokens in large language models and how they shape cost and performance. Learners discover how to measure, monitor and optimize token use in their applications while keeping output quality high.

What Is a Token?
- Define the basic unit of value in AI and connect it to readable text.
Pricing Models: Input vs. Output Tokens
- Calculate input and output costs using different LLM price lists.
Managing the Context Window
- Analyze how context window size affects cost and performance.
Strategies for Optimization and Cost Reduction
- Apply focused techniques that reduce token use while keeping output quality high.
Course Summary & Key Takeaways
- Synthesize core concepts of tokens, subword tokenization, and cost estimation
- Review key pricing differences between input and output tokens
- Summarize best practices for context window management and prompt optimization