AI Token Optimization Cookbook

Overview

20 techniques to reduce token usage without quality loss. A comprehensive reference guide for insights practitioners.

Quick Reference

python
from openai import OpenAI
client = OpenAI()
def solve_ai_token_optimization_cookbook(input_text: str) -> str:
    """20 techniques to reduce token usage without quality loss"""
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role":"system","content":"You are an expert in insights. Topic: AI Token Optimization Cookbook."},
            {"role":"user","content":input_text}
        ],
        temperature=0.3,
        max_tokens=1000
    )
    return response.choices[0].message.content
Usage
result = solve_ai_token_optimization_cookbook("Your ai token optimization cookbook question")
print(result)

Key Concepts

insights: Core to this approach

Validation: Always validate inputs and outputs

Error handling: Implement robust retry logic

Monitoring: Track performance and costs

Best Practices

Start with the simplest approach

Measure quality, latency, and cost

Optimize based on real usage patterns

Document decisions and tradeoffs

Review security implications

Related Topics

insights

optimization

practical

ai