Your AI Isn’t Expensive. Your Prompts Are.

Описание: Prompt engineering is quietly becoming one of the biggest drivers of generative AI cost.

Your AI model probably isn’t the expensive part.
Your prompts might be.

In this episode of the AI Proving Ground Podcast, WWT’s Liz Gattra explains why bad prompt engineering can quietly inflate token usage, increase retries, and drive up GPU compute costs across models like ChatGPT, Gemini, and Claude.

As more organizations move generative AI and large language models (LLMs) into production, the quality of prompts is starting to matter as much as the model itself. Vague instructions don’t just produce weaker answers — they create more tokens, more compute cycles, and bigger AI bills.

Liz walks through how better prompts, stronger system prompts, and thoughtful context engineering can dramatically improve output quality while reducing token spend.

In this episode we cover:
• Why vague prompts silently drive up generative AI costs
• A simple prompt blueprint that improves outputs fast
• How to reduce token usage 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 how they think about prompts.

Because in generative AI, precision compounds — and so does cost.

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

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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.

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