ChatGPT Workflow Templates

What’s inside

Markdown (.md) · 91 sections · about 12,649 words

• Table of Contents
• Understanding Prompt Engineering: Foundations for Precise Outputs
• 1. The mental model – Input → Context → Constraint → Desired format
• 2. Concrete techniques for each layer
• Input – Be specific, not generic
• Context – Supply only what the model cannot infer
• Constraint – Quantify every qualitative request
• Desired format – Declare the schema first
• 3. Iterative refinement loop
• 4. Common pitfalls and how to avoid them
• 5. Sample workflow for a real‑world use case
• 6. Embedding prompt engineering into daily workflows
• Workflow Automation with ChatGPT: Integrating APIs and Webhooks
• The integration pattern that works
• Real‑world example: Automated meeting‑note summarizer
• 1. Set up the webhook (Zoom → AWS Lambda)

Read straight from the file you download — these are its own section headings.