Master Prompting: Strategies for Success

CEO & President Kyle and Graphic Designer & Brand strategist Kelsey explore how prompting has evolved from using AI like a “smarter Google” to structured strategies that deliver sharper, less generic results.They break down the CRIT framework (Context, Role, Interview, Task), share why detailed context reduces hallucinations, and explain how prompt libraries and model memory speed up repeatable work. The conversation also dives into context engineering with tools like Microsoft 365 Copilot and Google Workspace Gemini to make AI outputs more relevant and secure.Plus: common prompting mistakes, model comparisons, multimodal inputs, and how to onboard teams without losing brand consistency.Listen now to level up how you work with AI.00:00 Prompting Then vs Now: From “Smarter Google” to Strategic Skill 00:39 Why AI Sounds Vanilla: Averages, Models & AI Slop 01:33 Prompt Engineering & the CRIT Framework 02:35 Interview-Style Prompts: Fewer Hallucinations, Better Results 04:10 Garbage In, Garbage Out: Treat AI Like a New Hire 05:04 Let AI Help Write Prompts + Tools & Libraries 07:08 Why One-Liners Fall Flat (Contractor Analogy) 07:55 From Prompts to Systems: Templates & Model Memory 11:21 Context Engineering: Files, Memory & Workplace Data (Copilot/Gemini) 13:27 Over-Prompting: Context Limits & When to Reset 16:26 Set Outcomes, Don’t Micromanage 18:22 Smarter Models: Gemini & Claude Need Less Steering 19:06 Claude Opus vs ChatGPT: Speed vs Detail 20:27 Multi-Model Workflow: Use Each for Its Strength 21:20 Why New Models Feel Smarter 22:11 Ask AI to Improve Your Prompts 24:42 Planning Mode: Structured Builds & AI Interviews 26:13 Training Teams: Frameworks, SOPs & Safe Experimentation 31:47 Multimodal & Voice Prompting (Gemini’s Edge) 33:15 Wrap-Up & What’s Next