WEBVTT

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We are doing so much work these days on co -pilot

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agents and AI agents. And Danny, he put together

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this really, really awesome day in the life of

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financial services. here's the demo flow we are

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next gen investments and what's happening is

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there's a customer called lily lily has been

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calling on the phone and having conversations

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that have been recorded and transcribed by co

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-pilot she's been asking about like making changes

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to her investments she sent an email lily to

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a junior associate which is danny danny is kind

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of a new hire i'm a new hire um i mean junior

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or associate financial advisor and i'm leveraging

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the power of my financial advisor pro agent few

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things here to show you um you don't need to

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be or i don't need to be a financial i mean a

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prompt engineer the agent already comes with

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pretty fine prompts so the first thing i need

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to understand is what's the latest in terms of

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what's the latest from our customer. And then

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I'm going to change here the name. Lili is my

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customer, and here's her account number in our

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organization. So Kapada knows now it's smart

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enough, my agent, to go to places inside our

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work data, connectors, et cetera, to pull the

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latest, everything that we know about Lili in

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terms of what's the latest. So I'm going to let

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it run, and this is all I need to do. Input the

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name. let my financial advisor pro come up with

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an analysis of everything what's going on with

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lily and in this case said okay uh looks like

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she had an income increase right here um she

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purchased a house in the past 3 .5 interest rate

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which is awesome family expansion She's going

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to have a son or child soon. And then investment

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interest. Lily's interested in diversifying her

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investment into stocks, mutual funds, and real

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estate, particularly in the technology and renewable

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energy sectors. Great. Now I know. We know exactly

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what's going on. Right now, what I'm going to

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do is, since my manager serving wants me to create

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a proposal for customer, I'm going to start editing

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in pages. So if you think about pages in Copilot,

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this is basically a new canvas for collaboration.

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I'm using the responses created by Copilot using

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generative AI and in smart sources of information.

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And I'm going to be adding those responses into

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a document, which is what you can see on the

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right -hand side. here again it's going to leverage

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the sensitivity labels where this response came

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from it's going to start adding this in a loop

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component that i can start using so now i'm going

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to go back and say view prompts and now i'm going

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to say okay i know and because shervin told me

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my manager that lee is getting a proposal from

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a competitor that competitor is contoso ltd so

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i have another prompt here that says uh provide

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a compute analysis for our current next -gen

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investment portfolio with competitor and i'm

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just going to type the name of the competitor

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contoso ltd and let it run i didn't have to write

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the prompt i'm just using a prompt that's already

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there in my agent and i'm going to have a side

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-by -side comparison between us and our competitor

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now it literally takes less than 10 seconds compiler

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knows where to go creates a very nice table comparing

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our index funds with our our competitor index

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funds and it offers me the sections that i ask

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expense ratio performance and annual gains and

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there's also a column here that says explanation

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Both portfolios have similar expense ratios.

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NextGen focuses on instability and tech growth,

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which is what she asked us in that conversation.

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She's interested in the technology index funds,

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while Contoso emphasizes in emerging markets.

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Bingo. This is a good win for us. Then there's

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a detailed comparison. Expense ratio, why we're

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better than the competitor. Performance, side

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by side. Annual gains, side by side. Wonderful.

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I didn't have to make a marketing compete analysis.

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I can go with this. I'm going to click on editing

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pages and just pay attention to what happens

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on the right side of the screen. So I'm going

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to see click on edit pages. And now the second

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section about, you remember the first section

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that I added, the current status? There we go.

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It's there. And now I added a new section about

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compete analysis. Here's the tape. Wonderful.

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And here's the explanation. Everything in the

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canvas, everything in the loop component. Now,

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the last thing I want to do as a junior advisor

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is to go back again into view prompts and click

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on this is where kind of the money goes when

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it comes to you as an organization showing something

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to your customer. Hi, Financial Advisor Pro.

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Can you help me recommend the best investment

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portfolio for customer name? Lily with the customer

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ID. based in our next gen index funds overview.

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And then I said, provide the results of the options

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in the table with a column explaining why this

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option was selected. Make sure to rank the offers

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from the most suitable to less suitable to the

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customer base on their current situation. We're

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going to hit enter here. Boom. And again, we

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can count it. It's going to take less than 10

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seconds. We'll go find that information for me

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and do exactly as I said, create a table. offer

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our our current investment portfolio tell me

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why you're putting this on the top and and put

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this in the table so i'm offering her five different

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five different index funds you can see that the

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rank is number one this is the one that the first

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one we should offer which is the office stability

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index fund and there's a description this expense

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ratio annual gains and this is why ideal for

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least preference for low risk investments I did

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not ask in the prompt, make sure you're ranked

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with low risk investments as a first off. I did

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not ask that. This is contextual understanding

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and vector search technology. Our pilot knows

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that Lily asked specifically for low investment

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risk. She's having a kid. She just purchased

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a house. She wants to be conserved. Creates a

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table, put them organized here. There's a reason

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for that selection. There's annual gains, expense

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ratio, description, funding rank. And there's

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a whole full analysis here that you can read,

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validate, understand. Good to go. Beautiful.

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Again, I'm going to click and edit pages. Take

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a look at the right hand side of the screen.

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That piece of information will get added into

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my document here. Wonderful. This is getting

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shape and it's looking like a very nice proposal

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that we can send to our customer. But we're not

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going to do that just yet. Well, Danny, I just

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want to say, as your manager, you are an amazing

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junior agent. I mean, look at this body of work

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that, you know, you're just a new hire into the

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company. And because of these tools, you're able

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to hit the ground running and produce. incredible

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and very detailed analysis right and just to

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kind of summarize what you did was first you

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did a discovery of what the customers ask was

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right and it was that was the one prompt that

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you just clicked on from the agent and it it

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you know it went and did all the hard work for

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you two you did a compete analysis because that's

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what the customer was saying they were comparing

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you know our funds with somebody else's and then

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three you asked for like what are the funds that

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we can recommend based on the portfolio that

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we have so those three things were basically

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just prompt that you clicked on and copilot did

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all the heavy lifting and you put it inside pages

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and you documented it so i mean incredible work

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and this is the power of ai agents and there

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are different ways to see the value here one

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you have a new hire uh that's learning and understanding

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how this works they're going to get up to speed

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quickly they can understand how the business

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works they can understand about all these terms

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and i don't know if you notice that the sensitivity

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label change from general when i run the first

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prompt to confidential microsoft extended why

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well that's because one of the responses that

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i got from copilot came from confidential documentation

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as soon as this information comes by the way

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this is a demo this is not really confidential

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information but the point here is if the responses

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from micros from your prom come from confidential

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information is because one you had access to

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that information otherwise compiler would never

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give you the answer one two as soon as i added

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that piece of the response into my collaboration

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canvas which is called pages the sensitivity

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label of my pages change right away from general

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to confidential So now that I'm ready with my

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proposal, I'm going to share this with my manager

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for approval, for review before we share with

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the customer, right? With Lily. So I'm going

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to click share and I'm going to say copy component.

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I'm going to click in settings and I'm going

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to people you choose and I'm going to send this

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to Shervin. He's my manager. So there we go.

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Click on it and apply. Now that I have shared

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my loop component with Sherving so we can start

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collaborating in the final proposal, let me show

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you how that looks like in the web just because

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we have more real estate to work with. I can

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see that my manager, Sherving, is now part of

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the proposal. I can see that he's in. As you

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can see that he's moving the mouse. He's moving

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around the document. He's making changes. Can

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we add a table? Okay, great. So he's actually

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asking me to do a few things here and there.

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If you also notice on my screen, I can click

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on Copilot and then start rewriting these pieces

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of this information with Copilot. I can make

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changes. I do want to ask Sherving, since he

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talked to Lily about, I want to ask about this

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particular section about family expansion. So

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I'm going to create a comment here and I'm going

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to ask Sherving, I'm going to tag Sherving, please.

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Please confirm this is accurate. My manager is

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coming here. He says it's looking great. Finally,

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Shervin thinks that this is a great document.

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He's going to prove it to me. So then we're ready

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to, there you go. I got a boost from my manager.

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Wonderful. So this is the document that we're

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going to be presenting to our customer. The next

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thing I want to do now is I'm going to go here

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and I'm going to print and PDF export. I'm going

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to create a PDF document out of this particular

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loop component that has all the information coming

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from Copilot. As you can see, you can make all

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the changes that you want. I'm going to go here

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and print this document. Finally, I want to show

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you how you can create a PowerPoint that you're

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going to be presenting to your customer using

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Copilot in PowerPoint. So I'm going to use a

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pre -approved template. This is the one from

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Microsoft 365. So I'm going to go click here.

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This is a template. As you can see, fonts and

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colors are all there. And I'm going to click

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on Copilot, and I'm going to go into the narrative

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builder. Copilot here. Make a representation

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about... this particular file. Again, this is

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the Lily Vildes customer proposal, and I'm going

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to run it. These are different sections. It creates

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a section for the summary of the latest communications,

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key points from the meeting, investment interests,

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comparison with Contoso. Fantastic. It's covering

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everything. Let Copata generate the slides. So

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finally, once I have this PowerPoint, which is

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ready to go, I'm able to schedule a call with

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the customer lady and come up with a proposal.

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So she's going to see a folder, a PowerPoint

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that has speaker notes to help you present that

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information. There's an agenda. There's a current

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status where she is today. Investment interest.

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This is what she's looking for. What about the

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income increase particular real estate purchase

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and all the things that we collected from our

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particular conversation? We're now ready to go.

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Again, in a matter of minutes. This is a word

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called Pi Engineering of AI can really help you

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boost productivity and customer satisfaction.

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Congratulations. You know, I'm going to give

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you more of a workload now. Like if you can bang

00:12:33.639 --> 00:12:36.399
out these in like 10 minutes, you need to work

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harder. So you're too efficient. Yes, that's

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right. So I need a raise right now. I wouldn't

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mind. And by the way, Danny, why don't we show

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like this agent. that you created you know like

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now that we've showed this demo maybe just a

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sneak peek into the agent itself so when whenever

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you get a copilot microsoft 365 copilot license

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it went in copilot chat you can see where it

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says create an agent i'm going to go here to

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create an agent and then finally i'm going to

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go over here view all my agents so i'm going

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to show you the financial advisor program edit

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so you can see how this was created against a

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low code no code you can see that it's using

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a lighter version of copilot studio in the back

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end i'm able to add an icon to it or an avatar

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name description there's uh some instructions

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here and here's the key right this is probably

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the most important thing about this copilot agent

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is the knowledge this is where i can start at

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telling my copilot agent these are the things

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that you need to go to pull data for my for my

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purpose right in this case i have a sharepoint

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site i call it fsi demo it can be any sharepoint

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site in your organization you can enable the

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web access is that's what you want to do and

00:13:58.019 --> 00:14:00.120
then here's where you can start adding connectors

00:14:00.120 --> 00:14:03.419
these are what we call extensibility options

00:14:03.419 --> 00:14:06.379
connecting to a service now instance maybe connecting

00:14:06.379 --> 00:14:09.759
to a wiki page connecting to an sql database

00:14:09.759 --> 00:14:12.620
connecting to whatever you want again sky's the

00:14:12.620 --> 00:14:17.740
limit if there's an api we can get there So,

00:14:17.779 --> 00:14:19.840
Danny, thank you very much, man. This this was

00:14:19.840 --> 00:14:23.500
amazing. This was awesome. You are probably you

00:14:23.500 --> 00:14:25.100
are going to get a raise. I'll tell you that

00:14:25.100 --> 00:14:26.860
much, because, you know, even though you just

00:14:26.860 --> 00:14:30.659
got hired in the company as my junior financial

00:14:30.659 --> 00:14:33.720
advisor, you're doing such great work that, you

00:14:33.720 --> 00:14:35.860
know, I can't help but promote you right away.

00:14:35.960 --> 00:14:39.360
Right. So you've done fantastic work. This was

00:14:39.360 --> 00:14:42.500
a great demo. Great usage of AI and copilot and

00:14:42.500 --> 00:14:45.860
agents. So thanks again. And I'll leave the last

00:14:45.860 --> 00:14:49.049
words with you as well. No, I want to thank you

00:14:49.049 --> 00:14:50.990
for the opportunity to come here, join your channel

00:14:50.990 --> 00:14:55.269
and explain, kind of help your community understand

00:14:55.269 --> 00:14:57.250
and learn more about Copilot. You have a great

00:14:57.250 --> 00:15:00.230
community of users, so we want them to learn

00:15:00.230 --> 00:15:02.549
more, understand more about this, reach out to

00:15:02.549 --> 00:15:04.870
your... Microsoft representatives, if you want

00:15:04.870 --> 00:15:07.210
to learn more, what we show you today is a financial

00:15:07.210 --> 00:15:09.590
services use case, which is what I do kind of

00:15:09.590 --> 00:15:12.289
in a daily basis, but sky's the limit here. Like

00:15:12.289 --> 00:15:14.370
you can do anything, everything you want. And

00:15:14.370 --> 00:15:18.149
what's coming next now is autonomous agents,

00:15:18.210 --> 00:15:20.929
which I know Sherving and I are working on something

00:15:20.929 --> 00:15:25.360
internally at Microsoft too. Yeah, I know. and

00:15:25.360 --> 00:15:27.759
and i think on that point and you know you're

00:15:27.759 --> 00:15:29.659
wearing such a cool hat that i got to put my

00:15:29.659 --> 00:15:32.240
co -pilot hat on too you know i can't be out

00:15:32.240 --> 00:15:37.080
done with that cool hat so i was just going to

00:15:37.080 --> 00:15:40.399
say that there's so much more to come you know

00:15:40.399 --> 00:15:42.779
we're just scratching the surface here so whether

00:15:42.779 --> 00:15:46.480
it's agents that are using connectors and apis

00:15:46.480 --> 00:15:49.679
or autonomous agents that have triggers that

00:15:49.679 --> 00:15:53.039
are automatically being used based on emails

00:15:53.039 --> 00:15:56.259
or like documents or new users being added they're

00:15:56.259 --> 00:15:58.320
just kind of running in the background we're

00:15:58.320 --> 00:16:00.399
going to be building these things and doing more

00:16:00.399 --> 00:16:03.000
content for you all so if you are interested

00:16:03.000 --> 00:16:05.960
in anything specific let us know but danny again

00:16:05.960 --> 00:16:09.840
man thanks so much and you like the hat i like

00:16:09.840 --> 00:16:11.399
it you should send me one of those i don't have

00:16:11.399 --> 00:16:15.500
that well i got i do have a bottle but oh the

00:16:15.500 --> 00:16:18.860
bottle Maybe I'll trade you for the bottle, man.

00:16:19.379 --> 00:16:21.779
We'll see. We'll see. All right. Okay. Thank

00:16:21.779 --> 00:16:23.559
you. Thanks, Charlie. Thanks, Danny. Thanks,

00:16:23.700 --> 00:16:25.539
everybody. Take care. Bye. Bye.
