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