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Build and Use Agents in Microsoft 365 Copilot: Complete Tutorial (2026)

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FULL TRANSCRIPT

0:00

Hello and welcome to this complete guide

0:02

on co-pilot agents. I'm going to take

0:05

you from the beginning through to

0:07

everything you need to know to be

0:08

somebody who can use, build, and work

0:11

with agents in Microsoft 365 Copilot at

0:14

work. I'm going to take you through both

0:16

the free version of Copilot Chat and the

0:19

paid version of Microsoft 365 Copilot so

0:22

that you understand what you can do

0:23

depending on which license you have. and

0:26

I'm going to take you through the skills

0:29

you need, the concepts you need, and

0:31

some of the out- of- the-box experiences

0:33

and how to get the most value out of

0:35

them. This is not a quick guide. This is

0:38

designed to be comprehensive. I'm going

0:40

to go at a pace that you should be able

0:41

to follow along. Please pop any

0:43

questions you have into the comments

0:46

below on this video, and I'll do my best

0:48

to answer them. And if you get value out

0:50

of this content, don't forget to like

0:52

and share it with others to help it

0:54

reach a bigger audience. And if you're

0:56

not already subscribed, you know what to

0:57

do. Let's get into it. Before we get

1:00

started, a couple of things. This is

1:02

working always with a work license. So,

1:05

we're talking here about having access

1:07

to the free version of Copilot Chat that

1:10

comes with your Microsoft 365 license at

1:12

work or the same situation with an

1:16

additional paid add-on license called

1:19

Microsoft 365 Copilot. None of what I'm

1:21

showing you here is possible with a

1:23

personal or consumer license. This is

1:25

very focused on agents at work. This is

1:28

also dependent on what your IT admin has

1:31

allowed or blocked in your organization.

1:34

So, if you can't see what I can see,

1:36

you're going to need to talk to your IT

1:37

admin about where they're at with

1:38

allowing agents. Maybe get them to watch

1:41

this video if they need to catch up on

1:43

what's possible here. So, I'm going to

1:45

start with a user who does not have a

1:47

paid license. This is somebody who's

1:49

logging in at work with their Microsoft

1:51

365 license and they have access to the

1:53

free co-pilot chat. Now, if you've got a

1:55

paid license, stay with me here because

1:57

we're actually going to build the

1:59

knowledge. You have access to all of

2:01

these things and more, but we're going

2:02

to start from the ground up with the

2:04

concepts here. So, don't jump away cuz

2:06

you'll miss some you'll miss some really

2:08

good stuff here. Now, the way that you

2:10

can tell whether or not you've got a

2:11

paid license, couple of things. If you

2:14

don't have the paid license, when you

2:16

log in, there will be nothing at the top

2:18

here. You just straight into Copilot

2:21

Chat. And you will see at the bottom

2:23

here that your license says Copilot

2:26

Chat. And you've got a little

2:27

information icon that explains that with

2:29

the free version of Copilot Chat,

2:32

everything you're doing here with

2:33

building agents is based on what you

2:37

upload or what you provide to it or web

2:39

sources. You can't automatically connect

2:42

to your teams, emails, all your

2:44

documents in SharePoint. That's the

2:46

stuff you have to pay for. So, if you're

2:48

seeing nothing at the top here, Copilot

2:50

Chat, and honestly, an upgrade button

2:52

because Microsoft wants everyone to be

2:54

on that paid version, you are in the

2:56

free version of Copilot Chat. If you see

2:59

some different things, if you see this

3:01

work and web at the top and M365 Copilot

3:06

at the bottom, that means you have the

3:08

paid add-on license. somebody in your

3:10

organization has paid extra for you to

3:12

have that and you will actually have

3:14

much more sophisticated experiences. So

3:17

I'm going to go through here the concept

3:19

of what an agent even is and this

3:21

applies equally to no matter which type

3:23

of license you've got. So I'm in my main

3:25

co-pilot chat experience here and let's

3:28

say I need some help with my

3:29

productivity. Not confessing at all that

3:31

this is a real use case but you can read

3:34

between the lines as as you like. So,

3:37

what I'm going to do here is just put a

3:39

prompt into my main chat experience. I'm

3:42

just going to copy and paste so you

3:43

don't have to watch me type here. I have

3:45

a big piece of work to get done, but

3:46

it's difficult to get started. So, I

3:48

keep ticking off smaller, easier tasks

3:50

instead. Anybody else? So, what this is

3:53

going to do, I'm just putting this into

3:54

the chat. This is just going to use AI

3:58

to give me a response. This is a secure

4:00

chat for my work scenario, but it's

4:02

actually not referring to anything. This

4:04

is just a general AI kind of chat coming

4:07

back at me. Uh Amy is the loggedin demo

4:10

user I have here who doesn't have a

4:11

license. That's why it's calling me Amy.

4:13

I'm obviously Lisa, not Amy. So, it's

4:15

actually just sort of coming back with,

4:17

you know, the cute little emojis and

4:18

it's giving me some general advice and

4:21

that's fine. Now, the difference between

4:24

just putting in a prompt like this and

4:26

building an agent is where you want

4:28

something that is very specifically

4:30

designed to handle certain types of

4:32

questions or certain types of tasks in

4:34

the way that you want. So, for instance,

4:37

this is just advice of a general nature

4:39

if you like that you're getting from the

4:40

AI response here. But let's say that I

4:42

want it to respond to me in a certain

4:44

way every time. I want it to have a

4:47

certain tone of voice. I want it to give

4:50

me some, you know, inspirational

4:52

encouragement, those kinds of things.

4:54

So, I could absolutely put all of that

4:56

into a prompt, but my prompt might start

4:59

getting quite long. And I want it to be

5:02

much more focused in the way that it

5:04

answers. So, the sort of the the path

5:06

here going from when is it a prompt to

5:08

when is an agent is to start to think

5:11

about is this something I want to do on

5:14

a repeatable basis, something I want to

5:15

come back to over and over again. That's

5:17

one reason you might want to create an

5:19

agent. Can I describe a specific task

5:22

and the way I want it done or a specific

5:25

kind of question and the way that I want

5:27

it answered and I want to do that in a

5:30

lot of detail and I don't have to type

5:32

that in every time and then do I want it

5:34

to refer to certain types of knowledge

5:37

in order to answer that question. So

5:38

these are all the types of things you

5:40

should be looking at. So let's have a

5:42

comparison here with what happens. This

5:44

is just in my chat experience in the

5:47

agent experience. So I'm going to come

5:49

across here and say new agent. Now there

5:52

are two ways that you can build an

5:53

agent. I'm going to show you the easier

5:55

way first and then the way that gives

5:57

you a little bit more control as we

5:58

build up to it. You'll see here there

6:00

are two tabs, describe and configure.

6:03

Depending on how your thing is set up,

6:06

I'm not sure where it will land.

6:07

Wherever you are, I want you to click on

6:09

that describe tab if it's not already

6:11

the one that's open. If you were already

6:12

there, then that's one less click that

6:14

you have to do. So, what I'm going to do

6:17

is actually give it a description of

6:19

what I want it to do. So, this is going

6:21

to be a productivity agent here. Help me

6:24

with my everyday productivity. When I'm

6:26

stuck, I want to come to you and get

6:28

pragmatic and practical advice on how to

6:30

improve my habits and my output. You'll

6:33

notice in my prompt here that I'm giving

6:35

it something more specific. I want you

6:36

to always begin by encouraging me and

6:39

then I want you to respond in no more

6:41

than three sentences and then I want to

6:42

finish with an inspirational phase

6:44

phrase. So what happens here is that it

6:47

is going to interpret all of this and do

6:50

the configuration in the background and

6:52

set up an agent for me. So let's take a

6:54

look at what it's done. Firstly, it

6:56

gives me a bit of a sort of confirmation

6:59

back that it understood. It has given it

7:01

a name, everyday productivity coach.

7:04

Fairly good so far. So good. Now, before

7:07

I go ahead and test, what I'm going to

7:08

do is switch across into the configure

7:10

tab. Now, if you saw my screen before,

7:13

when I was on that configure tab, you'll

7:15

notice that was all blank. I will show

7:17

you you can start there if you like. But

7:20

the way this works and especially with

7:22

all of the the way this is working

7:24

recently is just that two or three

7:26

sentences. If I'm kind of clear on my

7:28

intent, it is able to actually

7:31

extrapolate that into a set of very

7:33

detailed instructions for this agent.

7:36

Think of this as like writing a job

7:38

description. So this is now where I, as

7:40

a person at work, can have a whole team

7:43

of agents helping me with things. And

7:45

these are very specialized agents.

7:48

They're like subject matter experts. So

7:50

now this is my productivity agent. I

7:53

could have dozens of agents doing all

7:55

sorts of different things and they work

7:57

at their best when they are very

7:59

specific. So this is like I've hired a

8:01

little productivity coach, virtual coach

8:03

into my team. So it has a description.

8:06

Again, think of a job description.

8:08

There's usually like a purpose statement

8:09

at the top. So that's what that

8:10

description is doing, its overall

8:12

purpose. And then in the instructions

8:15

here, you'll see that we've got quite a

8:17

lot. It's pulled out quite a lot of

8:19

things based on the way that I've

8:21

described it. So, the approach is very

8:24

much coming from the way that I

8:26

described that I wanted it to work. It's

8:28

got a bit of a mission statement there

8:29

as well, which I like. It's guidance and

8:31

tone. Uh, we've got some examples. So,

8:34

it's it's kind of working well with

8:36

providing an example of how we want it

8:38

to work, limitations, and so on. Now,

8:41

you've actually got with this

8:43

description here 8,000 characters. So,

8:46

if you want to come back and work on

8:48

this or if you want to write something

8:49

yourself, I'll share with you a little

8:50

bit later some best practice guidelines

8:52

for this. You can actually go into a lot

8:55

of detail. Now, I can edit this from

8:57

here. If there's anything here I don't

8:59

like, I can change it. But let's see how

9:01

it goes. So, for now, we'll come back to

9:03

that knowledge piece if you took a peek

9:04

at that in a minute. I'm just going to

9:06

give this a try. So, I've got a test

9:09

window over the side here.

9:11

And I'm going to come back and put in

9:14

that exact same prompt. And remember

9:17

what it did last time. It gave me advice

9:19

of a general nature with pretty emojis

9:21

and kind of general advice. I've asked

9:23

it to behave quite differently here.

9:24

I've asked it to kind of start with some

9:26

encouragement, be concise, be pragmatic,

9:29

end with something inspirational. So I

9:31

hope you can see there the difference in

9:34

how it's responded and how much I've

9:37

been able to guide and control this. So

9:41

the concept that to get your head around

9:42

here is that even though we talk about

9:44

this as building an agent. So we come in

9:47

here and click new agent and and we talk

9:50

when we talk about this as building an

9:52

agent. Realistically what I'm doing is

9:55

refining the existing co-pilot chat

9:58

experience because I can do this exact

10:00

same thing in the co-pilot chat

10:02

experience and get a general answer. But

10:04

now I want to have a subject matter

10:06

expert that is doing it my way in the

10:08

way that I've described. And look how

10:10

much control I have over that. So that's

10:12

one example of what you can do. Now, if

10:15

I want to go ahead and save this agent,

10:17

I'm just going to click create. And that

10:21

will now add that into my experience of

10:24

working with Copilot Chat. And I can

10:26

very easily come back and use that

10:28

anytime I like. So let's just close that

10:31

down. you'll see it comes over here into

10:34

my agents experience. And if I hover

10:38

over that, I've got some options. Let's

10:40

just um sort of go back out of it and

10:42

back over here. If I click on pin, then

10:46

that means it's pinned into that

10:48

section. So, it's going to appear at the

10:49

top of the list if this is something I

10:50

want to come back to. Now, I select it

10:53

and it is sitting in there. And if I

10:56

wanted to go back and make any changes

10:58

to that, the three dots at the end here,

11:00

I can click edit and I go back into that

11:03

configure, make any changes I like and

11:06

update it. And you will find that as you

11:08

work with agents. And in fact, as you

11:11

work with any of these AI tools, don't

11:13

think of it as perfection the first

11:15

time. Think of it as an iterative

11:17

process. So have a go with that the

11:19

first time. Put in the description of

11:21

what you want it to do. Let it do its

11:23

thing and use it for a bit. And then

11:25

you'll find ah maybe that encouraging

11:27

tone is a bit annoying. Let's go back

11:28

and change that. Or let's go back and

11:31

say actually I want you to give me a bit

11:33

more depth or other things that you

11:35

might want to do. So if you come back in

11:38

here to edit, you can edit either by

11:40

directly changing those instructions or

11:43

you can actually come back into here and

11:45

describe how you want to update that

11:48

agent. So we'll come back to that in a

11:50

moment. The other way that you can use

11:52

it is that when you're in the chat, you

11:55

can actually talk to that agent, you can

11:58

at@mention it the same way you might

12:00

at@mention a colleague. So again, if I

12:02

want to have this I have a big piece of

12:04

work to get done, you know, how should I

12:06

do it? Instead of just coming in and I I

12:08

could switch across into my productivity

12:10

coach, but now that it's there, what I

12:13

can do is type in this at@mention and

12:16

say productivity coach. And now when I

12:19

put that message in there, it's actually

12:21

going to call on that agent to give me

12:25

the answer rather than doing it in the

12:27

general chat. So the idea here is that

12:29

you would have dozens of these and

12:32

you're calling on them to help you with

12:33

specific things and really tailoring

12:35

that experience of what you're getting

12:37

out of that co-pilot chat to make it far

12:40

more valuable than just that very

12:42

generic AI type of response. Let's do a

12:45

different version of the same thing.

12:46

This time what we're going to do is have

12:49

a look at working with a knowledge

12:51

source. So I'm going to come over here

12:53

again and say I'd like to create a new

12:55

agent. Again, we'll go back into that

12:57

describe tab. This one is now a little

13:00

bit different. What you'll see I'm doing

13:02

here is you should only provide advice

13:04

from the content in the knowledge

13:06

provided. And what I'm doing is putting

13:08

in a website here which is James Clear

13:11

who's the author of a uh a book um on

13:14

productivity that that's um that's very

13:16

famous and there's a lot of content on

13:19

his blog here like he's got a lot of

13:20

articles and things and let's say I'm

13:23

really you know into this idea of

13:26

working with atomic habits and I want to

13:28

do that. Now I could actually put in the

13:29

name of that and say follow those

13:31

guidelines but instead of that I'm

13:33

saying I want you to just use this as a

13:35

knowledge source. I don't want you to

13:36

kind of generate stuff out of your own

13:38

brain. So, not that it has an actual

13:41

brain, but you know what I mean. So,

13:42

what we've got here now is that it's

13:44

coming back and adding those things in

13:46

here. So, now we've got Everyday

13:48

Productivity Coach. We've already got

13:49

one called Everyday Productivity Coach.

13:51

So, let's change that. So, I'm going to

13:54

call this one atomic

13:58

atomic productivity coach. And you'll

14:00

see that it is now grounded solely in

14:03

the content of this. But something else

14:05

has happened here. If I come down to

14:07

knowledge, you'll see that it's got this

14:09

website in there. Now, it's picked that

14:12

up from my instructions. But if you

14:14

wanted to do this yourself without

14:16

including it in the instructions, let's

14:17

say I came back to the other one and

14:19

said, "Actually, I want you to just use

14:20

this website." You can just enter that

14:23

website in there and add it as a

14:25

knowledge source. And the other thing

14:27

you want to do here is to say only use

14:30

specified sources. So if I toggle that

14:32

one on now, it will only use that. So I

14:35

should only get advice based on what's

14:38

going on that it can draw from that

14:40

website rather than the general answer

14:42

that it gave me before. So let's create

14:46

this one and have a look at the

14:48

difference. I could have done a test in

14:49

there as well. Let me just grab my um

14:53

same prompt again because I think it's

14:54

useful to kind of see a direct

14:56

comparison of the differences. and that

14:58

will also appear over here on the side.

15:02

Let's go straight to the agent from

15:04

there. And I'm going to put that same

15:07

thing in here. You'll see those starter

15:08

prompts. We'll come back to those in a

15:10

minute. So now what happens is that it

15:13

is referring to James Clear. It's his

15:15

website, his blog that I've used. And

15:17

now we're talking about the twominut

15:19

rule, the next specific action. So

15:22

you'll see this is a very different type

15:23

of response than what I got before

15:26

because before I said just use general

15:28

AI but answer me in a certain way. Now I

15:31

didn't specify those things but actually

15:33

I asked for it to give me advice based

15:36

on that particular knowledge source

15:38

that's sitting on the web. Other uses

15:40

for this if you've got say your own

15:42

website with a lot of jargon on it or a

15:45

glossery on it. You could create an

15:47

agent for new employees or even for

15:49

yourself that helps you understand your

15:51

organization's jargon. If you've got a

15:54

partner that you work with or another

15:55

organization you work with, if you're

15:57

say in a an organization that has a lot

15:59

of regulations and and has government

16:01

websites and things you need to refer

16:02

to, you could create an agent based on

16:04

that. I will give you a couple of

16:06

warnings about use using websites and

16:08

where the limitations are. So, let's go

16:10

back into this one, the Atomic

16:12

Productivity Coach, and just go into the

16:14

edit section here and take a look at

16:16

that. So, when you're using websites

16:19

here, you'll notice that this one is a

16:22

single website with a single level down,

16:25

jamesclar.com/productivity.

16:28

Let's say I had a website that was

16:30

further down the URL path than that. So,

16:32

I'm just going to show you a Microsoft

16:34

365 website as an example here. This is

16:36

a co-pilot learning site. So let's say I

16:38

wanted to create an agent that was

16:40

grounded on that's the phrase we use

16:42

where it's connected to that data and

16:43

just responds to that data. We say it's

16:45

grounded on that data. We've got see

16:47

here learn.microsoft.com 1/en

16:50

us1/copilot

16:52

1/icrosoft 365. We've gone more than two

16:56

levels down and you can't actually do

16:57

that. So if I come in here and say add

17:02

that URL

17:05

you'll see it gives you an error. The

17:07

website can't be more than two levels

17:08

deep. So that's always going to be a

17:10

limitation. You can go further up. So I

17:13

could go further up the chain here and

17:15

just do copilot. It will actually read

17:18

everything all the way down the

17:19

hierarchy, way more than two levels, but

17:21

the starting point can only be two

17:24

levels deep. So that is a limitation of

17:25

using the website. The other thing to

17:27

look out for on websites is that you

17:29

need the content to be on the website.

17:32

These are both good examples because

17:34

with this one, this is a blog. So the

17:36

the content is all just sitting here.

17:38

It's just text that you can that you can

17:40

read. Uh something like this again has a

17:43

lot of text in it that you can read. But

17:45

if you've got a website that has a lot

17:47

of codec coded elements like JavaScript

17:49

elements that are displaying tables that

17:52

aren't actually tables underneath or

17:55

displaying things in a way where the

17:57

substance of the words isn't actually on

17:59

the website or say it's an embedded

18:02

e-reader in the website, you're going to

18:05

have a problem. So basically what it can

18:07

read is the same thing that a search

18:09

engine indexes. So, if your favorite

18:12

search engine can't find that content,

18:14

your copilot agent also won't be able to

18:16

find that content. Let's take a look at

18:18

one final example here of working with

18:20

this style of agent, but using all

18:23

websites. So, when we made the first

18:26

agent, I just asked it to give me a

18:29

general answer. The second one, I asked

18:31

it to be grounded in or refer to only

18:33

that one website. This one, I'm saying

18:36

use websites for reference and provide

18:37

me with links for further relevant

18:39

reading. So this is one that's going to

18:41

be sort of a bit more uh giving me some

18:43

research and reading guides and things.

18:45

So if I have a look at the configure

18:46

option here, what happens is if we go

18:50

down to the knowledge, then it allows it

18:53

hasn't actually done this direct from

18:54

the instructions. You do have to toggle

18:56

this on search all websites. So you

18:58

remember in the previous example, we

19:00

just had that single website for the

19:02

James Clear blog and then I said use

19:04

only specified sources. In the very

19:06

first example, I didn't toggle this on,

19:08

which means it's not reaching out to the

19:10

web. It is just using the AI's internal

19:13

language, predictive language. Whereas

19:15

this one, I'm now saying, actually, I

19:17

want you to draw on all of the sources

19:19

for the web. So, if I come back in here

19:22

and do the same thing again for the

19:25

third and final time, this is a

19:26

productivity advisor. You'll see that

19:29

this is another different example of the

19:31

result that you can get because this

19:32

time I've asked it to go out and find

19:36

other things on the web. So now we're

19:37

getting kind of uh advice here around

19:43

different things including so you'll see

19:45

this one's come from the Harvard

19:46

Business Review. So again you can refine

19:48

this to encourage it to give you more

19:50

links but it's drawing on those sources

19:51

from outside. So that's websites. The

19:54

other thing that you can do here is work

19:58

with these suggested prompts. So, you'll

20:00

see that this one came up with some

20:02

suggested prompts to put on the front

20:06

page when you use it. Now, sometimes

20:08

that's incredibly useful. Sometimes it's

20:10

not incredibly useful. So, if you like

20:13

these ones, awesome. But you can very

20:14

easily come in here, you can edit the

20:17

title, you can edit the message, you can

20:18

delete them, you can add new ones. So,

20:22

you can do whatever you like here. You

20:23

can have anywhere between zero and six

20:26

of them. So that's entirely up to you.

20:28

Sometimes in the description, it will

20:29

generate those suggested prompts and

20:32

then do what you will to make them

20:34

useful for you. Now, you will have seen

20:36

as we went through and wrote those

20:38

descriptions that it's filling in that

20:40

configuration box for you with an

20:41

overarching purpose in the description

20:43

at the top and then a bunch of different

20:45

sections below. Honestly, as you're

20:48

getting started, that is far and away

20:49

the most easy, the most effective way to

20:52

do this. But here are some guidelines

20:53

and I'll put a link to the source of

20:55

where this comes from. There's a

20:56

Microsoft documentation site that has

20:57

some more detail if you want to follow

20:59

up on that where you can actually write

21:02

your own instructions. So instead of

21:03

starting from describe, you can just go

21:06

straight into that configure tab with

21:07

the blank box and just start typing in

21:10

whatever you like and create that from

21:11

scratch. So as you get more experience

21:13

and confidence and if you want more

21:15

control with this, these are the types

21:17

of things that you should put in there.

21:19

And what you can do is just go in here

21:21

and say new agent and just put all of

21:24

those things in. Here's my agent. Here's

21:26

the description. Here's the

21:27

instructions. Just start typing it and

21:29

and and work from there. Select what you

21:31

want in there for a website and and how

21:33

you want it to work. So you have

21:35

complete control over those things. Now,

21:37

there is one other last thing that you

21:39

can do here with the free version of the

21:42

license. Actually, two things. One of

21:44

the things you can do, let's go back

21:45

into our um everyday productivity coach

21:49

and I'm going to edit this. So, one of

21:52

the things that you can do here is give

21:54

it a new icon. So, it'll give you these

21:55

default kind of icons in pretty colors.

21:58

But if you edit this, you can browse

22:01

sort of standard little icons here. So,

22:03

you know, something like that might be

22:05

quite nice for productivity. You can

22:07

upload a file. So, if you've got a PNG,

22:10

it has to be quite small. I think it's

22:12

192x 192 pixels, no more than one um

22:16

than one meg. Or you can use an AI

22:19

generated image. Obviously, you can go

22:20

back into the main copilot or other AI

22:22

tool of choice and generate an image,

22:24

but this can actually now generate

22:26

something directly from the description

22:29

of the agent. Now, I will confess I'm

22:31

doing this live for the first time

22:32

because this is actually a fairly new

22:34

feature at the time that I'm doing it. I

22:36

am trusting in the process and I do

22:39

enjoy the thrill of doing something live

22:41

and hoping for the best. Looks like it's

22:44

going to come up with something fairly

22:47

[laughter] fairly fairly abstract. Oh,

22:50

here we go. Oh, no. It's cute. Oh, look

22:52

at that. Oh, see, look. It was worth

22:53

trusting in the process. It hasn't even

22:54

finished this, but I love it already.

22:56

Uh, while we're just waiting for this

22:58

little cute icon to uh [laughter] to

23:00

generate, don't forget if you're getting

23:01

value out of this, please like, share,

23:03

subscribe. All of those things really

23:05

help with uh with growing the channel

23:07

and helping this content get out there.

23:10

Oh, do we love that or what? That's I

23:13

mean, honestly, image generation is

23:14

getting a whole lot better. I'm just

23:16

going to apply that. And there it is.

23:18

It's so cute. I'm very glad I very glad

23:21

I did that. There's one more thing I

23:22

want to show you here that you can do in

23:24

your agent still in the free version of

23:26

Copilot Chat before we move into the

23:28

limitations uh where you need the paid

23:30

version. So, we go all the way down

23:32

below the knowledge here. There are two

23:34

capabilities that you can choose to add.

23:36

This is as simple as enabling a toggle

23:39

switch. And this is just a choice about

23:40

whether you want your agent to be able

23:43

to do these things or not. So, what I'm

23:45

going to do is switch both of these on.

23:46

The first one is giving it the ability

23:48

to create documents, charts, and code.

23:50

Now, for this use case, probably doesn't

23:53

really map across. This is more useful

23:55

if you've got an agent that sort of

23:56

needs to help you analyze and understand

23:58

things, but you are giving it the

24:00

ability to generate a document of some

24:02

kind. We'll have a look at that. And the

24:04

other one here is something where we're

24:07

going to allow it to be able to create

24:09

images. And again, if you don't switch

24:11

that on and the person using the agent

24:13

comes in and says create an image, it

24:14

just won't do that. So that's just a

24:16

decision there. Update at the top is the

24:18

sort of save to keep it going. Uh that

24:21

is the decision that you need to make

24:23

whether you want your agent to have

24:24

those capabilities or not. So let's go

24:26

back into the agent now and let's say

24:29

generate a spreadsheet.

24:32

showing me how much time I could save in

24:36

a week if I used proper

24:42

productivity

24:44

techniques.

24:47

So, we'll see we'll see whether it can

24:49

do this or not. If you put in a prompt

24:52

like the one I used before and then said

24:54

generate a word document with this

24:55

content, then it will actually literally

24:58

take the content and do that for you. So

25:00

what this is doing because I've added

25:02

this type of uh it's called code

25:05

interpreter even though the description

25:07

says create documents. What it actually

25:10

does is writes code underneath. You

25:12

don't have to know anything about what

25:13

it's doing. It does that for you and it

25:14

can actually kind of generate more

25:16

sophisticated types of things here. So

25:18

this has now given me a weekly time

25:20

savings calculator. So you'll see that

25:22

that is in fact an Excel document. Let's

25:24

open that file and

25:27

see what we've got. So here we go. So,

25:30

it's put some things together. Total

25:32

hours saved per week. It hasn't kind of

25:33

put the Oh, so it's asking me to fill in

25:36

the number of hours, hours saved per

25:38

week, and it's going to do that

25:39

calculation. So, it's basically created

25:40

a template for me. I could push further

25:43

with the prompting to ask it to actually

25:44

suggest times and things, but that's

25:46

actually sort of not a bad starting

25:48

point. If I come back into my So, again,

25:51

I can go new chat and stay within that

25:53

agent. And let's come back one more time

25:56

to this example we have about the big

25:58

piece of work. and what it's going to um

26:01

what it's going to to help me with. And

26:03

then I'm going to say, let's say, please

26:05

generate a fun image to remind me of

26:09

this. And that will trigger the image

26:11

generation capability that I switched

26:13

on. That will take a minute with the

26:16

magic of video editing. I'm just going

26:17

to pause and come right back when it's

26:18

done. And there it is. Not quite as in

26:21

love with that one as I was with the

26:22

icon, but you get the point. I didn't

26:24

write a particularly good prompt for it.

26:25

So, the better the prompt, the better

26:27

the image generation. Incidentally, off

26:30

topic, I'm left-handed. AI generates

26:32

every single image of somebody writing

26:34

with a pen with their right-handed. If

26:35

I've got any other fellow left-handers

26:36

who are watching and you've figured out

26:38

how to get AI to generate a left-handed

26:40

person, do let me know. One of those uh

26:43

little biases that's uh that's in the

26:45

training data that I haven't been able

26:46

to resolve or I haven't tried recently.

26:48

Okay. So, let's have a look now at where

26:51

we hit the limitations because pretty

26:52

much everything I've shown you now is

26:54

what you can do with the free version.

26:55

So you can write really good

26:57

instructions to get it to respond

26:58

exactly the way you want. Connect it to

27:01

websites, multiple websites like all the

27:04

internet or just a specific website. You

27:06

can have it generate documents. You can

27:08

have it uh generate images. But here's

27:11

where we hit the wall. So if I come in

27:14

here and say let's um let's start with a

27:16

new agent because it is a little bit of

27:18

a trick here that might mislead you.

27:19

When I go down into the knowledge

27:21

section, you'll see the only options are

27:24

to add a website or to add all websites.

27:27

That's it. This is the biggest

27:29

limitation between the free license and

27:31

the paid license. If I go into the

27:33

describe one here, let's say I'm going

27:36

to do something a little bit different

27:38

here. So, I have got a pets at workday.

27:41

Let's say we want to have something

27:42

where we allow people to bring their

27:44

dogs and cats into work. So, I can say

27:46

help me plan our pets at workday. Now,

27:48

there is an add content here which makes

27:51

it look like you can bring these things

27:53

in here. So, I've got my proposal for

27:55

pets at workday and I've also got a

27:59

budget file in here. Now, it looks like

28:01

I've added those as document sources.

28:04

What actually happens here is that it

28:07

can not it doesn't actually keep them as

28:10

sources because these are files that are

28:12

sitting on my one drive on my sharepoint

28:14

and even though I can access them there

28:16

that's actually because when I run the

28:18

agent I can upload files but it's a bit

28:21

of a it's a bit of a trap because what

28:23

happens is that it'll actually say it's

28:25

giving you this warning now. So I've

28:26

tried to do something and it's saying I

28:28

can't add SharePoint files. I can't do

28:31

that. Um, and so then it's giving you

28:34

that warning. So, we'll go ahead and

28:35

switch across into the full version of

28:38

the license, uh, where you've got a paid

28:40

Microsoft 365 co-pilot license. So,

28:42

someone in your organization has paid

28:44

additional money and assigned that

28:45

license to you. And we'll take a look at

28:47

the difference in that experience. So,

28:50

as I showed you earlier in the video,

28:51

the experience when you're starting here

28:53

with a paid Microsoft 365 copilot

28:56

license, you've got a couple of clues

28:57

that you have that license. You have

28:59

both a work and web tab at the top here.

29:02

And down the bottom here, you will see

29:04

that you have a Microsoft 365 co-pilot

29:07

license. Doesn't want you to upgrade now

29:09

because you've already got it. And

29:11

you'll see here the key difference

29:13

answers are informed by your work data.

29:15

So this as a starting point in the chat

29:18

is connected to everything that you've

29:21

done in your Microsoft 365 world of

29:24

work. This is called work IQ. And this

29:28

is essentially what you're paying for to

29:30

be honest with the Microsoft 365

29:32

license. It knows your context at work.

29:35

It knows where you sit on the org chart,

29:37

who reports to you, who your boss is. It

29:39

knows your collaboration, who you work

29:42

with, the documents that you work on in

29:44

SharePoint and one drive. It doesn't

29:46

reach other systems unless someone's

29:48

explicitly connected it to those

29:49

systems. It has all your Teams chats,

29:53

Teams um conversations, your emails. So

29:56

it's got the full context of everything

29:58

you're doing at work as it stands and

30:01

that's the value of what you're paying

30:02

for. That's a concept called work IQ

30:05

which is to which is which is how we we

30:07

understand that. So what happens here is

30:09

that when you're building an agent in

30:11

the paid version that work IQ stuff

30:14

becomes available to you. So let's come

30:15

in here and have another go at this

30:17

bring your pets to workday agent. We'll

30:19

start by selecting new agent. Before I

30:21

go in and put that description in, just

30:23

want to scroll down and you'll see

30:25

something very different from what we

30:26

saw with the free version. The top

30:28

section is the same new agent

30:30

description. The instructions are the

30:32

same. Down the bottom here, these

30:33

capabilities and suggested prompts, all

30:35

the same. Where the value of the paid

30:37

license comes in when you're working

30:39

with agents is in the knowledge section.

30:41

So, you'll see here that you can add

30:43

files, meetings, chats, emails, and

30:46

websites. This allows you to have an

30:50

agent that is grounded on your work

30:52

data. So, what we saw earlier was that

30:55

you were working with websites, but you

30:58

couldn't upload any documents. What we

31:00

can do here is actually have it pointing

31:02

to all of the context of what I work

31:05

with. Now, this is the huge value of the

31:07

paid Microsoft 365 copilot license.

31:09

Whether you're in the chat or building

31:11

an agent, this is referred to as work

31:13

IQ. It has the context of everything

31:16

you're doing at work in the Microsoft

31:18

365 world of work. It knows who my boss

31:21

is, who my staff are, my collaboration,

31:24

who I collaborate with the most, the

31:26

documents I've worked on. It has access

31:27

to all of the documents that I have

31:29

access to in SharePoint and one drive.

31:31

It has access to everything I'm doing in

31:33

Teams. It has access to my email. So,

31:36

all of that is very, very rich. It's all

31:38

secure. So, you're bringing AI into that

31:41

work context, that work IQ. So, this

31:44

allows you to go much deeper and much

31:46

more contextual with the things that

31:47

you're doing at work. And that is

31:49

honestly what you're paying for over and

31:51

above having the free version. You can

31:54

also bring other data sources in here.

31:56

I'm not going to spend too much time on

31:57

this now, but you can see I've got

31:58

Confluence there. I've got another video

32:00

if you're interested in how to do that.

32:02

You need to be an admin and set up all

32:04

the right permissions to allow people to

32:05

use that. But the main thing that I want

32:07

you to focus on here is that in the paid

32:10

license, we've got access to all of

32:11

these things. You've also got this

32:13

reference or chart and profile info

32:15

option that wasn't there before. So,

32:17

let's work through this. If I come back

32:19

into this describe section here and say,

32:21

"Help me plan our pets at workday." Now,

32:24

this is something where I've given it a

32:26

fairly fairly basic prompt, but it's

32:29

going to take that and turn it into a

32:31

set of instructions. Again, if I was

32:32

doing this for real, I would be much

32:34

more specific with what I want it to do.

32:36

But have a look at what it's been able

32:37

to do just from that particular single

32:41

phrase. Right? Given me a whole lot of

32:43

various things in here. Now what I can

32:45

do now because I've got this as an

32:47

existing project and I can share this

32:50

with other members of the project team.

32:51

We'll come back to that in a moment.

32:53

I've got a PowerPoint deck. I've got a

32:55

budget. I've got a bunch of planning

32:56

documents that help me with this pets at

32:58

work planner. And I want to work in the

33:00

context of all of that stuff that I've

33:02

done at work. So, what we can do here is

33:04

that if you go into this box now,

33:06

instead of it just being a website URL,

33:08

you've actually got a whole lot of other

33:10

options. So, across the top here, I can

33:12

go into files, and this will show me my

33:15

recently used files. If it's something

33:17

you've recently used, you're making it a

33:19

whole lot easier for yourself cuz those

33:20

things are there. You can actually go

33:23

into SharePoint site. So, if you wanted

33:25

a whole site, you can come in here. Just

33:28

be aware of this. If you choose sites,

33:32

that is giving you the content on the

33:34

SharePoint site, not the documents. If

33:37

you want the documents for a SharePoint

33:39

site, you want to go in and choose

33:42

SharePoint files and folders or browse

33:44

for a specific one. Come back to that in

33:46

a second. So, you're going through

33:48

individual files that you can upload a

33:50

whole SharePoint site if you've got a

33:52

bunch of sites. You can go into Teams

33:55

chats and bring those things in there.

33:57

If you wanted to create an agent, let's

33:59

say you've got a group of colleagues

34:00

who's got a really long group chat with

34:02

a lot of answers and a lot of content.

34:04

You can actually create an agent that's

34:06

pointing to that specific team's chat if

34:08

you want. Uh you can also use it to

34:11

refer to meetings and the contents of

34:13

meetings. You've got a bunch of

34:14

different things that you can do there.

34:16

What I'm going to do here is just upload

34:17

these files. Now, if I didn't have them

34:19

in the recent files list, you can find

34:22

them by starting to type the name of it,

34:25

but you have to remember the name of it.

34:27

So, that makes it a little bit harder.

34:29

Uh, if it's in the recent list, it's

34:31

just a whole lot easier to grab. But, if

34:33

you want to browse for those files or if

34:36

you want to add a whole folder, this

34:38

little cloud icon at the side here will

34:41

open up the cloud drive so that you can

34:44

then go in and work with browsing those

34:47

things. So, let's say this is on my

34:48

communication site, uh, and I've got a

34:51

whole thing on responsible business and

34:53

I wanted to add every document from that

34:54

folder. That's how you can add a folder.

34:57

Or if you wanted to upload them from

35:00

your desktop, if you don't have them in

35:01

there, you can upload them using that

35:03

little upload arrow. So, you've actually

35:05

got a lot of options here. We're going

35:07

to come back to the email one in a

35:09

second. So, just remember when you're

35:11

creating an agent with the with the full

35:13

version of Microsoft 365 Copilot, when

35:16

you're in the main chat,

35:18

it's got access to that whole work IQ,

35:20

everything you're doing at work. When

35:22

you create an agent, you're actually

35:25

narrowing down that experience and being

35:27

more specific about what you want it to

35:28

do. So, the starting point is that if

35:31

you don't add any knowledge, it doesn't

35:33

use any of those things. So you're kind

35:35

of starting from blank and saying which

35:38

things that Copilot has access to do you

35:40

want this agent to use. So this again I

35:43

think I said at the start it's like we

35:45

talk about building an agent as if it's

35:47

adding something. Really what we're

35:49

doing here is focusing the attention.

35:51

The main co-pilot chat already has

35:53

access to all of that. When you build an

35:55

agent, you start from blank and say

35:58

these are the bits that you as my

36:00

subject matter expert on this particular

36:02

topic should refer to and should have

36:04

access to. So if you don't add anything,

36:06

it won't use all of that stuff. The

36:08

co-pilot chat will the main chat

36:10

experience will with the with the full

36:12

license, but not if you don't add it to

36:13

the agent. Just take a minute on that.

36:16

It does take a bit of of sort of getting

36:18

your head around it. So now what we've

36:20

got is um let's let's also allow this

36:24

one to create documents and charts

36:26

because we might want to be able to do

36:27

that. And I am going to create that

36:31

agent and put it in there. Now let's say

36:34

for this one that I am actually working

36:37

with a team. It's likely that let's say

36:39

I'm on a committee and I've got a pets

36:40

at workday committee that I'm working

36:42

with. When I create an agent to start

36:45

with, it is private only available for

36:47

me. But I can choose to share it with

36:50

other users. And then I can choose who I

36:52

want it to be available to. If I choose

36:54

anyone, then I can share it with anyone.

36:58

And some depending on your

36:59

organization's permission, that option

37:01

might not be available to you. I've got

37:02

a system here that's allowing me to do

37:04

anything. If I say specific users, then

37:07

I can add specific users in there, or I

37:10

can go in and say I just want a certain

37:12

security group. So this is my demo

37:15

account, which is um Miranda. I'm going

37:17

to go in and add me, my actual main

37:20

account, as somebody that I'm going to

37:21

share it with. Uh, and then what you do

37:24

to share it is copy the link. Select

37:26

continue. Now, the important thing to

37:29

understand is that me, in this case, the

37:32

Miranda version of me that's logged in

37:33

and created this, I have access to these

37:36

documents as the user. If I create this

37:40

agent, then this is going to affect what

37:44

the other person can have access to. So

37:46

if I share an agent and the underlying

37:49

data sources that other person doesn't

37:51

have access to them, they won't be able

37:53

to get to them that way. So what this is

37:56

doing is giving access to those

37:59

knowledge sources. So again, this is

38:01

going to really depend on whether or not

38:02

you as the loggedin user are allowed to

38:05

do that. Your IT admin will have set up

38:07

permissions to do those things. But just

38:09

be aware that it especially if you

38:11

create something let's say I create

38:13

something on my email and then share

38:15

that that is not giving someone else

38:17

access to my email and you can't

38:19

actually grant permission to your email

38:20

but this is what we've got with these

38:22

documents. So in this case the other

38:23

user is me and has access to everything

38:26

but Miranda sends me that link. I paste

38:29

that link into my browser and I get this

38:31

experience here where this agent comes

38:34

through to me and I can just click add

38:37

and that will add it into my list of

38:39

agents. So the next thing I want to talk

38:41

to you about is the out ofthe-box

38:43

agents. You can get there to the agent

38:45

store by clicking on this all agents

38:47

button on the lefthand side menu. Most

38:50

of these agents are available to you on

38:52

the free version of Copilot Chat, but

38:55

there are two very special ones in here,

38:56

researcher and analyst, which are only

38:59

available if you have got that paid

39:01

Microsoft 365 copilot license. So, we'll

39:03

have a look at both. Now, there's a

39:04

whole lot of different things in here in

39:06

the built by Microsoft section. If you

39:08

scroll down, there are some really good

39:10

ones in here like prompt coach, idea

39:12

coach, writing coach. The prompt coach

39:14

is actually one of my favorites. If you

39:15

like any of these, you can click on them

39:17

and just click add and it will add it

39:19

into the list. And this has got a whole

39:21

lot of again in the background a whole

39:23

lot of instructions to help you improve

39:25

your prompting skills. So if you go into

39:28

the main co-pilot chat and just say,

39:30

"Help me improve this prompt." Again,

39:33

like we saw right at the start, it's

39:34

going to give you that advice of a

39:36

general nature. This one has a bunch of

39:38

instructions behind it that are using a

39:40

framework of how to write a good prompt

39:42

that's actually going to give you a very

39:44

structured way of doing that. That is

39:46

much more valuable than just asking the

39:48

general chat. Again, it's the subject

39:50

matter expert on how to write effective

39:53

prompts. So, there's a bunch of things

39:54

in there that you can play around with.

39:56

I want to turn your attention now to the

39:58

researcher agent and the analyst agent

40:01

which are honestly very very high value

40:03

agents that you get with that paid

40:04

Microsoft 365 co-pilot license and they

40:08

are sitting in this agent section if

40:10

you've got access to them. So let's

40:12

first take a look at the researcher

40:13

agent. This agent uses what's called

40:16

chain of thought reasoning. It's a much

40:18

deeper reasoning. So you've seen with

40:20

the other agents we've used so far they

40:22

sort of take a question and just respond

40:23

fairly quickly. This one actually kind

40:26

of goes, how should I solve that

40:27

problem? What should I do? And it works

40:30

with everything on the web and

40:33

everything in your world of work. So,

40:36

it's got access to all of that work IQ

40:38

as well as everything on the web. And

40:40

this is like your research assistant.

40:41

It's going to go out and do some

40:43

research for you in depth. So, what

40:45

we're going to do here, you want to give

40:47

this a problem to solve rather than sort

40:49

of a specific question. I'm preparing a

40:52

pitch for pets at workday. Please put

40:54

together a briefing paper to help me

40:55

understand everything I need to know.

40:57

And this is something where if you've

40:59

been tasked with a new project, uh some

41:01

kind of presentation where you need some

41:03

background information, it's actually

41:05

quite good as a learning tool as well.

41:07

Help me learn about this new subject

41:09

from a specific level or a specific

41:11

point of view. These are all really good

41:13

ways of using the researcher agent. I

41:16

find especially people who are in more

41:18

sort of senior executive type roles,

41:20

this one is often the highest value

41:22

thing to work with in in Microsoft 365

41:24

Copilot. So, it's actually giving me um

41:28

you're preparing a pitch and you want a

41:29

briefing paper that covers these things.

41:31

So, it asks me some specific things. Is

41:33

it a specific industry? Would I like to

41:36

focus on small, medium, any of those

41:39

kinds of things? So, what I'm going to

41:42

do here is just give it a little bit

41:43

more context. you you can just not

41:46

answer these questions if it's not

41:47

helpful. So, I'm just giving it a little

41:49

bit more. I'm also very deliberately

41:51

choosing I'll press the button and then

41:53

show you what it does. I'm going to say

41:54

I want short rather than long because 1

41:56

to five pages is still quite

41:57

comprehensive. Long is like a really

41:59

deep research paper. But you'll see I'm

42:01

giving it specific things. I'm asking

42:03

about the Australian workplace and I'm

42:05

doing that to prove I'm in Australia. I

42:07

know most of you aren't, but I'm doing

42:09

that to prove how tailored this can be

42:11

to my particular work context that it's

42:14

not just giving me generic information

42:16

that it can really kind of be very

42:17

specific. Now, look at what it's doing.

42:20

Crafting a pitch, organizing key points,

42:22

it's thinking out loud here. And you can

42:25

expand this box to see the full history

42:29

of what it's doing. So, it starts to

42:32

work through how it should do these

42:35

things and any problems it finds or any

42:38

any rethinking. Oh, now that I found

42:41

this, I might also try that. So, it's

42:43

actually quite interesting to sort of

42:45

watch the thought process go through

42:47

here. Now, because this does take a

42:50

while, I'm going to show you one that

42:51

I've prepared earlier. Exactly the same

42:53

prompt, but it's got it sitting in

42:54

another open tab here. So, I've done the

42:56

same thing. Uh, actually, look it. So,

42:59

if you switch tabs, by the way, it

43:01

actually kind of encourages you to go

43:02

back and gives you a little

43:03

notification. So, it actually didn't

43:05

take as long. Oh, no. It's still it's

43:06

still going, but that's the experience

43:08

you'll get if you go away and leave it.

43:09

So, here is my report. Pets at workday

43:12

briefing, benefits, challenges. So, now

43:14

what I've got is some nice icons that I

43:16

can work with and sort of copy those.

43:19

We've got a table with an executive

43:21

summary, the benefits, and if I hover

43:24

over these

43:26

references, this is the ABC. This is the

43:31

uh the the official um broadcaster here,

43:34

like the Australian Broadcasting

43:35

Corporation. So, that is a very reliable

43:37

source. Uh the New Daily, I'm not

43:39

familiar with this one, I must confess,

43:41

but it's a.com.au, which is my area. Uh

43:44

pound pause. So this is something that's

43:46

clearly some sort of site that is

43:48

relevant to this topic and again locally

43:50

here. So I can see that it is actually

43:52

bringing things in from the specific

43:55

context that I asked for. And you go all

43:58

the way down like this is honestly

43:59

really really high value stuff to get

44:01

across something very big very quickly.

44:03

And then I've got options here to say

44:06

well let's open that in word because I

44:08

want to take it outside um and continue

44:11

working with it in Word. And then I

44:13

would need to go ahead and save that as

44:15

a document. But you'll see it's brought

44:17

that in. So I can go ahead and work with

44:18

that there. Or if I wanted to work with

44:22

it in here and make some edits. You've

44:25

also got this option to edit in pages.

44:29

And that opens a sidebyside editable

44:31

version of this. So now I can come

44:34

through and I could make some changes

44:36

and do some things. I could actually

44:38

share this with somebody else. This is a

44:42

Microsoft loop component. So, two of us

44:44

could be working on this in real time

44:45

and then I can take it out into Word or

44:48

wherever else I want it to be. So, we'll

44:50

just close that down. But either way,

44:51

you've got ways of taking that output

44:53

and putting it somewhere else. The

44:55

analyst agent is the other one that's

44:57

very high value, and this is designed to

44:59

help you with data analysis. Now, what

45:02

I'm going to do first here is add some

45:04

documents. I have actually downloaded

45:06

these from a a public website that is

45:09

about university admissions in

45:10

Australia. But grab whatever data you

45:13

can find. Hopefully, you've got a real

45:15

work scenario here where you've got a

45:16

spreadsheet with a whole lot of stuff or

45:18

just find some other kind of public or

45:20

government website and grab some

45:21

statistics. If I show you what this

45:22

looks like, this is a series of little

45:25

PDF documents here that talk about the

45:27

sort of application by gender and and

45:30

where they're from and age and so on for

45:32

applying for university study in

45:35

Australia. So, what I'm going to do is

45:37

come back into the analyst agent and

45:39

select add content. And if I choose the

45:43

paperclip, add work content, that allows

45:45

me to go to my SharePoint files. But

45:49

actually, I just downloaded these from

45:51

the web. So, I've got a whole folder

45:53

here of demo documents that I've

45:55

downloaded. So, I've actually just got

45:56

these three tables here. I'm going to

45:58

choose all three documents and add them

46:00

in there. And then my prompt here is

46:03

going to give it some context, which is

46:05

actually really important for getting a

46:07

good result. These files show

46:09

undergraduate applicants and offers for

46:10

tertiary study in Australia. Here is

46:12

what the data is and how it's arranged.

46:15

And then I'm giving it a problem to

46:17

solve. what trends or outliers do you

46:20

identify? Now, it goes through this same

46:23

chain of thought reasoning process. So,

46:25

it's actually kind of going through and

46:26

you'll see I've actually given this

46:28

these are PDF documents. They're not

46:29

Excel spreadsheets. So, it's actually

46:31

able to read that from the PDF document.

46:33

Uh it goes through and navigates and and

46:36

works through all of those different uh

46:38

different options. And again, I'm just

46:40

going to stop this one actually because

46:43

I did this one earlier because it does

46:45

take a little while. So here's the

46:46

response we get these files. So it goes

46:49

through and does that for a couple of

46:51

minutes and then provides me with these

46:55

kinds of trends and insights. So then

46:58

what I can do is ask it to say uh please

47:02

provide please generate

47:05

a chart showing the trend

47:10

of total applicants

47:13

over the last 3 years. Now this actually

47:17

uses a code interpreter capability. So

47:19

it is capable of creating quite

47:21

sophisticated charts. This one, I

47:23

haven't been very specific about it, but

47:25

it can plot all sorts of things and help

47:27

you analyze data. So, if you've got a

47:29

real world scenario where you've got

47:31

massive spreadsheets and you're in

47:32

charge of having to kind of interpret

47:34

things and write reports and so on, this

47:36

one is also again kind of at that at

47:38

that manager level, executive level, a

47:40

very very high value uh thing that you

47:42

can that you can do. So, while it's

47:44

doing that, if I just scroll back up the

47:46

chat, you've got examples of these are

47:48

quite basic ones, but if you're asking

47:49

it for other things, it can do that. You

47:52

can also ask it to say, "Please give me

47:55

a commentary that assign that that goes

47:58

with this." So, I'm imagine I'm having

47:59

to present these results back to an

48:02

executive board or something. It's

48:04

actually helping me with kind of giving

48:06

me a summary and giving me some visuals

48:07

that I can that I can use in there. And

48:10

again, we'll just stop that from working

48:11

because it's it's done its job. These

48:13

ones, researcher and analyst, do have a

48:15

cap on usage. Uh, at the time of

48:17

recording, that is 25 uses per month

48:20

across both of them. So this is not

48:22

something I would say not every day, but

48:24

most of us have 20 working days in a

48:25

month. So you could actually use it

48:26

every day, but it's not the default

48:28

option. It's not something you're using

48:29

several times a day. You want to think

48:31

through that this is something that you

48:33

need that deeper research or that deeper

48:35

analyst, but they are extremely high

48:37

value things for those use cases. You've

48:39

also got the ability to create and work

48:41

with agents on your data in SharePoint

48:44

and One Drive. Again, we're in the paid

48:46

Microsoft 365 Copilot license here. So

48:48

this is just helpful if you're working

48:50

somewhere else. So if I primarily work

48:53

in SharePoint rather than the main chat

48:55

experience, let's say I'm in human

48:56

resources, I've got all of these

48:58

documents on all our different policies

49:00

here. You can click on open agents at

49:02

the top. And this has got a readymade

49:04

knowledge agent that is working with the

49:07

documents that are sitting in here. So I

49:09

can ask, can I take a day off on my

49:14

birthday? We've got a birthday leave

49:15

policy sitting in there. and I haven't

49:17

had to build or do anything. This agent

49:19

is just existing in SharePoint against

49:21

this document library and it's able to

49:24

answer questions based on that document

49:26

library. If you want to narrow it down

49:28

to something more specific, you can also

49:30

do that from here. But let's uh give it

49:32

a second to answer this question. So

49:34

yes, according to the birthday leave

49:35

policy and it gives me a summary of what

49:38

that birthday leave policy is including

49:41

with the references to where that's

49:43

coming from. Let's say I only wanted to

49:46

do something on the birthday leave

49:47

policy. What I can do is select that

49:50

document and up on my menu here, I've

49:53

got AI actions and I can create an

49:56

agent. Now, when I go in here, you will

49:59

see an experience that hopefully becomes

50:02

quite familiar based on everything else

50:03

that you've seen so far. We've got a

50:05

name, we've got an icon, we've got a

50:07

purpose, which is the description, and

50:10

then we've got the sources. So instead

50:12

of having to create the agent first and

50:14

upload or point to that document, I've

50:16

just done it the other way round because

50:17

I'm starting from the document and

50:20

behavior is basically kind of the

50:22

starter prompts and some of the

50:24

instructions. So all of those elements

50:26

are there and you can have that agent

50:29

experience sitting sort of directly in

50:31

SharePoint for users who are working

50:33

with that. So I can actually do the same

50:34

in one drive. I've got a document set of

50:36

documents here that are related to

50:38

Contoso. I've uh borrowed these from a

50:40

Microsoft Learn site. Uh and you've got

50:42

the ability to come in here and create

50:44

an agent or to select documents and work

50:48

with Copilot there. That's all

50:49

relatively new. Let me know if you'd

50:50

like a deeper dive on the One Drive

50:52

SharePoint stuff. Just giving you a bit

50:53

of a a whistle stop tour of those things

50:55

as well. One last way I want to show you

50:57

that you can use your agents in context

51:00

then is working inside the application.

51:03

So working with Word and the idea here

51:05

is these agents follow you around

51:07

wherever you are. So the agents we

51:08

created earlier um are available. So

51:11

let's say I'm sitting in word and I have

51:13

got my something about premium t here.

51:16

What I can actually do this I've just

51:18

selected the co-pilot button on the

51:19

side. I'll close it down to show you

51:21

from scratch. I'm in word online but it

51:22

works in the desktop as well. You can

51:24

expand or reduce this to give yourself

51:26

more space. But this is exactly the same

51:29

as this main copilot chat experience

51:33

here. You'll see you've got the work and

51:34

the web. And what I can do is use this

51:37

menu to open the navigation panel and I

51:40

can use any of those agents including

51:42

researcher or analyst or one that I've

51:44

got in here that's called te assistant

51:46

um where I might you know be able to

51:48

sort of put something in and I'm in in

51:51

the context of working in my document. I

51:53

want to go back to that agent and get it

51:55

to help me answer some questions and

51:58

actually ask it to pull those things in.

52:01

Now you'll see it's picked up on the

52:03

context of my open document as well.

52:05

Suggest tea pairings for different

52:06

occasions. It knows I'm in the Mystic

52:09

Spice premium chai tea over here. So

52:11

it's giving me all of these things. And

52:14

if I want, I can just copy all of that

52:17

and put it in the Word document. So

52:18

you've got these things side by side. If

52:21

I go back into my chat and refresh this,

52:25

then you will find the T pairings for

52:28

various occasions chat that I just had

52:30

is sitting there. So it's actually just

52:31

surfacing that whole co-pilot chat with

52:34

those agents in a different surface. So

52:36

you can start to use these agents

52:38

wherever it is that you want to work. So

52:41

up until now we've been looking at

52:43

working with agents that are very

52:45

contained within this Microsoft 365

52:47

co-pilot experience or the co-pilot chat

52:50

experience. You'll see these are all

52:51

designed for everyday business users to

52:54

just make that experience better.

52:55

They're very clear guard rails. They're

52:58

very clearly constrained. There's no

53:00

code anywhere. There's not really that

53:02

many choices. This is all about working

53:03

with language, creating these subject

53:06

matter experts, and refining those

53:07

instructions. But I hear you ask, what

53:10

if you want more? What if you want

53:11

something that will run on a schedule?

53:14

What if you want something that can

53:16

connect to other data sources and where

53:17

you have greater control and you're

53:19

talking about the language models

53:20

underneath and you want to kind of get

53:21

right into it? If you want something

53:24

that can run on a schedule, at this

53:25

stage, these agents don't have that

53:27

option. But if you're in a Frontier

53:30

tenant at the time of recording or if

53:32

you're watching this later, maybe this

53:33

is available live, you will find that

53:36

there are options in here for things

53:39

called the workflow agent. I've got

53:41

another video that talks you through

53:42

what that does. That workflow agent will

53:45

allow you to create scheduled

53:46

automations. But if you want a true

53:48

agent that runs on a schedule or that

53:50

gives you far more options for things,

53:52

that's where Copilot Studio, the full

53:55

version of Copilot Studio comes in here.

53:57

What we're doing with this agent

53:59

building experience in Microsoft 365

54:01

Copilot is effectively working with a

54:03

light version of Copilot Studio. Whereas

54:07

if I want to go into the full version of

54:09

Copilot Studio, then I've got a whole

54:12

other set of skills that I'm going to

54:13

need and you've got a whole other set of

54:16

capabilities. And this is much deeper.

54:18

We're shifting the user persona here.

54:20

Everything up till now is an everyday

54:22

information worker, business user.

54:24

Copilot Studio is getting into a low

54:26

code maker actually through into prodev

54:28

makers as well. You can start from

54:30

scratch over there. But if you've got an

54:31

agent you like here and you're hitting

54:33

the limits of this and you want to take

54:34

it further, you've actually got an

54:36

option in the three dots up the top here

54:38

to say copy to Copilot Studio. It gives

54:42

you a bit of a briefing on what that's

54:44

going to do. And we click get started.

54:46

And this is where you're starting to

54:48

work with environments, application life

54:50

cycle management, all sorts of other

54:52

things in here. You will have to have as

54:54

a user the permission to use C-pilot

54:56

Studio. Your organization will need a

54:58

license. But essentially what this does

55:00

is takes the work you've done so far

55:01

with all of the instructions and all of

55:03

that information that's in there and

55:06

moment in time copies it across. It

55:08

doesn't it's not connected anymore. It's

55:10

it's genuinely like cloning it and

55:12

taking it off on its own path. So you'll

55:14

see this is the T assistant copy. All of

55:16

those things that we had in there are in

55:18

there including the knowledge source.

55:20

I'm just going to click create on this

55:21

so that you can see what happens. And

55:24

this now takes this agent into a world

55:26

of many, many more things that you can

55:29

do. Now, forgive me here. This is my new

55:32

book. I wrote a book. This is how big

55:35

the book is on things that you can do

55:37

with Copilot Studio. I wrote this thing

55:39

and I can't believe how big it is. It's

55:41

like 550 pages. So, there are plenty of

55:44

resources online. I've got a tutorial

55:46

here and I'm updating more tutorials,

55:47

but just to give you a sense of how much

55:49

there is to know and honestly there's

55:51

still more than I could fit in one book.

55:54

So that's a reference if you want to get

55:55

deep into it in a very structured way.

55:57

But essentially what this will allow you

55:59

to do is connect to all sorts of

56:02

enterprise knowledge, take control of

56:04

the conversation with workflows and

56:07

topics, trigger the agent based on uh

56:10

specific trigger points of data points

56:13

that happen or running on a schedule

56:15

more than I can possibly do justice to.

56:17

So if you'd like to learn more about

56:18

Code Pilot Studio, check out my tutorial

56:20

here or there's a link in the

56:22

description if you would like to get a

56:23

copy of my book in old school print or

56:25

ebook format. Thanks for watching.

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