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Your AI isn’t expensive. Your prompts are. Every vague instruction creates compute churn — more tokens, more retries, more GPU burn. Most teams don’t notice the cost compounding until the bill shows up. In this episode of the AI Proving Ground Podcast, WWT’s Liz Gattra breaks down the invisible tax of bad prompt engineering — and how AI literacy becomes a cost-control strategy as generative AI moves into production. We cover: • Why vague prompts silently erode ROI • A practical prompt blueprint that improves outputs fast • How to reduce token spend without downgrading models • When to switch between ChatGPT, Gemini, and Claude • Why system prompts, agents, and context engineering determine whether AI scales — or spirals Most teams upgrade models. The smarter teams upgrade thinking. Precision compounds. So does cost. Stop paying the invisible tax. Support for this episode provided by: ExtraHop Chapters: 0:00 The Hidden Cost Of Bad Prompts 1:04 AI Literacy Isn’t Optional 2:11 Prompting Is the Foundation 3:07 Tokens, GPUs, and Burn Rate 4:17 From Magic to Discipline 6:08 The Prompt Blueprint 8:23 ChatGPT vs. Gemini vs. Claude 10:46 Where Models Get It Wrong 13:12 Meta Prompts & Reusable Personas 15:14 From Assistants to Agents 18:23 Confident. But Wrong. 20:00 Turning Prompts Into Assets 21:32 Context Is the Moat 35:57 Build the Skill or Pay the Cost 🔔 Subscribe to AI Proving Ground on YouTube: / @aiprovinggroundpodcast Connect with us on: LinkedIn: / world-wide-technology Twitter: / wwt_inc About WWT: World Wide Technology (WWT) is a global systems integrator that provides digital strategy, innovative technology, and supply chain solutions to large public and private organizations. For more about the AI Proving Ground Podcast, visit: https://www.wwt.com/events/ai-proving...