In this episode of Generative AI 101, we catch a wave into the BAB framework (we're totally calling it "BABE")—an effortlessly cool method for crafting AI prompts that turn "meh" into "tubular!" BAB, short for Before, After, and Bridge, guides you from dull, lifeless AI interactions to responses that shine like a pro surfer catching the perfect wave. Learn how to structure your prompts for clarity, precision, and maximum impact, ensuring your AI delivers every time. 

If you enjoyed this episode or have questions, reach out to Emily Laird on LinkedIn. Stay tuned for more insights into the evolving world of AI and prompt engineering. And remember, you now know more about BAB prompting than you did before!

In this episode of Generative AI 101, we explore CARE Prompting—a sophisticated method that prioritizes Craft, Audience, Response, and Evaluation to fine-tune AI outputs. CARE Prompting is designed to create responses that go beyond accuracy, ensuring they resonate deeply and reflect a comprehensive understanding of your goals.

In this episode of Generative AI 101, we’re taking a high-speed tour of the RACE Prompting method—where Role, Audience, Context, and Example aren’t just pit stops, but the keys to better communication. 

Ready to take your AI skills to the next lap? Connect with Emily Laird on LinkedIn. Stay tuned for more laps around the ever-evolving circuit of AI and prompt engineering. 

In this episode of Generative AI 101, we explore the ins and outs of RTF Prompting—an approach that sharpens your AI's focus by defining its Role, Task, and Format. Whether you're tasking your AI with writing a travel blog, analyzing financial data, or extracting historical records, RTF Prompting provides the clarity and structure needed to achieve precise results. We’ll break down how to use this versatile tool, discuss its pros and cons, and share some entertaining examples that highlight its effectiveness.

Connect with Us: If you enjoyed this episode or have questions, reach out to Emily Laird on LinkedIn. Stay tuned for more insights into the evolving world of AI and prompt engineering. And remember, you now know more about RTF Prompting than you did before!

Connect with Emily Laird on LinkedIn.

In this episode of Generative AI 101, we break down the concept of self-consistency prompting—a technique that enhances AI accuracy by posing the same question in multiple ways and selecting the most consistent answer. By guiding your large language model through varied prompts, this method improves performance on complex reasoning tasks and reduces errors. However, it's not without challenges: it demands more computational power and isn't entirely foolproof.

Connect with Us: If you enjoyed this episode or have questions, reach out to Emily Laird on LinkedIn. Stay tuned for more insights into the evolving world of AI and prompt engineering. And remember, you now know more about self-consistency prompting than you did before!

Connect with Emily Laird on LinkedIn

In this episode of Generative AI 101, we break down the concept of chain-of-thought prompting—a technique that helps AI models think through complex tasks step by step, improving their logical and accurate responses. By guiding the AI, or your large language model of choice, through detailed instructions, this method enhances performance on tasks like arithmetic and decision-making. However, it’s not without challenges: it works best with large models and can be resource-intensive.

Connect with Us: If you enjoyed this episode or have questions, reach out to Emily Laird on LinkedIn. Stay tuned for more insights into the evolving world of AI and prompt engineering. And remember, you now know more about chain-of-thought prompting than you did before!

In this episode of Generative AI 101, we explore the example-heavy world of few shot prompting. Imagine describing a dish you love to a chef and then offering them multiple recipes on how to make it. That's few-shot prompting—maximum input, maximum efficiency. We'll explore how this technique can turn your AI into a translation whiz or a sentiment analysis expert with just one example. We'll also discuss the pros and cons of this approach.

In this episode of Generative AI 101, we dive into the art of one-shot prompting. Imagine teaching someone a recipe with just one perfect example instead of a whole cookbook. That's one-shot prompting—minimal input, maximum efficiency. We'll explore how this technique can turn your AI into a translation whiz or a sentiment analysis expert with just one example. We'll also discuss the pros and cons of this approach, compare it with zero-shot prompting, and share vivid real-world scenarios. Tune in to discover how one-shot prompting can make your AI sharper and more effective than ever.

Join us on Generative AI 101 as we demystify zero-shot prompting—a technique that lets LLMs perform tasks without prior examples. Imagine whipping up a dish you've never heard of with no recipe; that's zero-shot prompting in action. We’ll explore how AI models leverage vast pre-existing knowledge to answer questions, classify sentiments, and more, all without specific training. But it's not all smooth sailing; we'll also discuss quirks like the "Reversal Curse," where LLMs struggle with reversed statements. 

In this episode of Generative AI 101, we continue with the art of crafting the perfect prompt for AI. Much like brewing the perfect cup of coffee, the right balance of persona, output format, context, examples, and instructions can transform a bland response into a rich, engaging answer. Tune in as Emily breaks down these five key elements, provides real-world examples, and shares tips to elevate your prompt engineering skills from average to exceptional.