Ep 848: Context Engineering: How to Get Expert-Level Outputs From AI Chatbots (Start Here Series Vol 7)
episode
Everyday AI Podcast – An AI and ChatGPT Podcast
37 min
2 speakers
4 chapters
transcribed 21 days ago
Transcript
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Transcript generated automatically by AI and may contain errors.
What is context engineering and why did prompt engineering become obsolete?
Welcome to the Everyday AI podcast. My name is Jordan Wilson, and for the past three and a half years, we put out more than 800 episodes. Yet, one of the most common questions I get, I didn't really have an answer for. Where do I start on the Everyday AI podcast? And that's why we started the Start Here series. And with Fall now back in full swing, the Everyday AI podcast is Is going back to school and playing back the entire Start Here series from front to back. We've hit pause on our normal Monday to Friday programming to run back our most popular series ever for the next 30 days. We made the Start Here series for beginners and AI champions alike. So whether you're just trying to get a grasp on large language models or grappling with the best coding harness for multi-agentic.
Workflows, the Start Here series covers it all. Plain language, no jargon, and easy to follow along each day. So make sure to subscribe to the podcast and check back each day for new insights day by day. The series is a culmination of spending more than 10,000 hours covering generative AI over the past three and a half years. So you don't want to miss a single episode of the Start Here series. Let's get into it. Why does no one talk about prompt engineering anymore? I mean, if you were whined back like two years ago, you would have sworn that prompt engineering would be the world's most popular future job title. But that's obviously not the case. And the essential disappearance of that term is twofold.
One, models are smarter, and it doesn't always matter the exact way we talk to them, as long as we get the message cross. And two, an output that moves the needle is much more dependent on business context versus just wording something a certain way. Hence the resurgence of the term context engineering. But what does that even mean? And how can you understand the required inputs of context engineering to get better outputs out of a large language model? Well, if that's one of the things that you or your business is grappling with. Then you're in luck because on today's episode of our Start Here series, we're tackling context engineering and how to get expert level outputs from AI chatbots. All right, I am excited for today's show.
I hope you are too. If you're new here, welcome. This is the everyday AI Start Here series. So after 700 plus episodes, one of the most Common questions I get is where do I start? So that's why we started the start here series. And this is actually volume seven of this exact series. So The Start Here series is the essential podcast series to both learn the AI basics and to double down on your knowledge. So if that's what you're trying to do, you're in luck. Make sure you go to starthearseries.com. That's going to redirect you and give you free access to our inner circle community. So there you can not only go take our context engineering course called Prime Prompt Polish for free, but also network with a bunch of other people and you'll be redirected right to our start here series area where you can go and listen to every single episode in this series, all right there at your fingertips.
All right. And if you missed our last episode of this series, we talked about how to train your team on AI and the seven steps to educate your organization on large language models. And the last step in there was well, making that step to go from operator to orchestrator. So that's where we kind of left you with the last step in our series. And that's where we're going to pick up because. Actually, one of the biggest things that you can do from going from an operator or essentially someone pushing all the buttons to an orchestrator, right? Which is when AI starts to do the work for you, is having the right data and providing that data to the model in the right way. And that is the backbone of what context engineering is.
It is the process a human goes through to make sure a large language model has the right context about not just you, your role, what you're trying to accomplish, but maybe most importantly your business and the competitive market.
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Chapters
4 chapters
1
What is context engineering and why did prompt engineering become obsolete?
0:00–6:32
2
How do you define and structure context for AI chatbots?
6:32–25:08
3
What are the six building blocks of an effective context window?
25:08–26:41
4
How can you create reusable context vaults and skills for scalable AI?
26:41–37:31
Speakers
2 identifiedMore from Everyday AI Podcast – An AI and ChatGPT Podcast
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Ep 857: From Chatbots to Super Agents: The 11 AI Tool Categories Explained (Start Here Series Ep 16)
Ep 855: AI Governance in Plain English: 5 AI Rules Every Company Needs to follow (Start Here Series Vol 14)
Ep 856: Everything Is Fake: How Your Company Can Leverage Human Expertise and Fight AI Workslop (Start Here Series Ep 15)