Ever wondered why AI implementations can be so hit-or-miss? Unlock the mysteries of generative AI and Microsoft's Co-Pilot with insights from my esteemed colleague Murray Fife, as we tackle the excitement and confusion surrounding AI technologies. We break down the differences between tools like Microsoft's Co-Pilot and Azure OpenAI, offering practical advice on setting up guardrails and structured prompts to ensure your AI initiatives are both advanced and reliable. Learn firsthand the strategies for managing AI projects from defining clear inputs and outputs to navigating the iterative nature of AI development, ensuring your projects align with expected results.

From achieving consistency in AI responses to balancing flexibility, we cover it all in this episode. Hear about the importance of early planning, preprocessing data, and structured test cases to achieve cleaner inputs and better outcomes. Our conversation offers valuable lessons on maintaining reliability and contextual appropriateness in AI outputs, making this episode an indispensable resource for anyone involved in AI project management. Whether you're at the start of your AI journey or looking to refine your existing projects, this episode promises actionable insights and real-world experiences to guide you through the complexities of AI implementation.

Don't forget to take a look at the book:  Quick Start Guide to Large Language Models by Sinan Ozdemir

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