什么是 Prompt Engineering？

Production environment issues with LLM applications cannot be solved by prompt engineering alone, requiring a control layer to handle structured output failures, input validation, and system stability issues. The author developed an 8-component control layer that improved success rates from 0% to 100% under identical model and query conditions.

AI is reshaping product management paradigms, requiring product managers to transform into AI builders with skills in prompt engineering, data-driven approaches, and rapid experimentation.

A guide from GPT 5.5 Pro on Codex Goal usage reveals two techniques: use /plan to let AI ask clarifying questions and converge on a Goal; use /goal to generate executable Codex instructions, improving code generation quality and consistency.

DeepLearning.AI launches 'AI Prompting for Everyone' course covering prompt engineering, context windows, and AI system fundamentals.

This course by Andrew Ng demonstrates how to build a functional birthday card app in 30 minutes using AI tools like ChatGPT and Gemini, requiring no programming background.

AI technology evolves rapidly, making traditional book formats unable to keep up with knowledge iteration speed. The author questions the feasibility and quality of AI-written books.