Thinking in API Calls

In agentic engineering, we don't just chat. We treat the LLM as a programmable module.

The Completion Pattern

Learn to use the messages structure: system, user, and assistant.

Example Code: python import openai client = openai.OpenAI() response = client.chat.completions.create( model="gpt-4o", messages=[{"role": "system", "content": "You are a logic engine."}, {"role": "user", "content": "Analyze the problem..."}] )

Understanding token management and temperature is crucial for predictable agent behavior.