What’s inside the complete prompt engineering guide
Part I: How to build prompts that actually work
The C.O.R.E. model explained (Context, Objective, Role, Examples) with before/after comparisons
Question layer technique: force the AI to show its work before delivering final output
Context engineering: three rules that keep conversations sharp across 50 messages instead of degrading after three
When to start fresh, how to manage uploaded files, and why your custom instructions are probably too long
Part II: Ready-to-use workflow prompts Four complete, connected workflows you can copy-paste and customise:
Strategic planning and goal setting (4 prompts: performance analysis → vision drafting → team communication → cascading OKRs)
Marketing campaign execution (4 prompts: competitive research → messaging framework → campaign assets → sales enablement)
Product feature development (3 prompts: feedback synthesis → PRD drafting → test case brainstorming)
Employee lifecycle management (3 prompts: job description creation → onboarding design → engagement survey analysis)
Each workflow includes context management tips so you know when to start fresh conversations and what to carry forward.
Part III: Moving from individual skill to team capability
How to build your internal prompt library (not just save templates, but capture your company’s specific context)
From prompts to automation: when a well-defined workflow becomes the blueprint for a custom GPT or AI agent
Your prompt engineering checklist
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