What's this about?
OpenAI's guide covers model selection, prompt and skill consistency, context compaction, caching, monitoring and long-running agent control. Its main message is that production results depend on the surrounding system as much as the model choice.
What exactly is prompt caching?
Applications repeatedly send the same instructions and reference material. Caching reuses earlier computation for that stable prefix, reducing cost and latency when the prefix remains identical.
Why does this matter?
The advice turns vague “prompt engineering” into operational engineering: measure task success, preserve only useful context, define autonomy limits and budget the complete workflow rather than token prices alone.