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WEBVTT
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Well, I have to tell you that I'm a little bit sad.
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This is the beginning of the beginning of the end.
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It's the beginning of our last time together.
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The final.
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The end of the finale.
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The conclusion of our eight week voyage.
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To take you from the very beginning to LLM mastery.
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And what a fitting conclusion it should hopefully be.
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I realize I maybe oversold some of the excitement that was in store, but I do hope that you shared
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some of it with me, that you also enjoyed this project and that you're ready for the last stages.
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So what you can do now is so much to it that I couldn't possibly, possibly do it.
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The injustice of squeezing it into three bullets.
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So it now dominates most of this page.
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And obviously what's in store for us today is to get to the top of the mountain and complete the mastering
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of AI and engineering and LLM engineering, the missing piece for us, if we look at our Agentic AI
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solution, we covered each of these different pieces, and perhaps the one that we hadn't yet completely
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ticked the box of was having autonomy.
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We have got memory.
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We've in a sense, although there's not much point in having memory if it doesn't, if it only runs
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once.
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So yeah, we really need to pull all of this together and have it into a process that is running, and
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so that you'll be able to kick something off and then just go away and get on with your daily life and
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get texted.
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Push notified from time to time as deals come up on the internet that seem worthy of your attention.
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Uh, and so this one more time was the agentic workflows that we had put together.
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And of course, we built everything in red in one session when we we built out our, our prices, including
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the specialist pricing that calls out to modal and the frontier processor that uses our chroma lookup.
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Um, and then we built an ensemble that takes the weighted average of them all.
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Uh, and we then assembled it together with our scanner and our messaging and planning so that we'd
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have everything together.
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And then last time we used something that was fancily called an agent framework, but was nothing more
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than a Python script to glue everything together.
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And of course you can, as I say, get agent frameworks through through various off the shelf frameworks.
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But most of what they're doing is exactly what we did ourselves, uh, through simple Python.
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All right.
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So what remains, what remains is for us to go back with one last time to JupyterLab, where we will
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start playing with my old friend Gradio.
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Uh, we will be right there.