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Grok Bot for Marketing

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Grok Bot for Marketing

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0:00

All right. Hello. Hello.

0:03

Hi everyone. My name is Josh Kim and I'm

0:06

so thankful for all of you for joining

0:07

us here and I'm excited to share how we

0:11

on the SpaceX AI team use Grockbot for

0:14

marketing.

0:16

Here's our runner show for today. Uh

0:19

I'll be sharing what Crockpot is, how we

0:21

use it internally, uh to market and grow

0:24

the product and most importantly how you

0:27

all can start using Grockbot within your

0:29

teams. Let's jump in. So let's start

0:32

with the context. Um the way we all

0:35

started using AI was pretty simple. Uh

0:38

many of you may still be using AI today

0:40

just like this. Uh and I certainly was

0:42

in this camp uh before I started on the

0:44

SpaceX AI team. The typical pattern is

0:46

that you have one or two AI chat bots

0:49

that you really use and leverage as your

0:51

thought partner. Meaning, you chat with

0:53

them, you ask questions, you spar on

0:55

strategy, maybe you edit copy. Um, but

0:58

they're really there as your thought

0:59

partner and not a doing partner.

1:02

As AI has started advancing, there's

1:04

been this rise of generalized and

1:06

specialized agents that can start to do

1:09

tasks with you. Um, we refer to these

1:12

internally as co-pilots because while

1:15

they can get those tasks done with you,

1:17

they still typically require you to

1:19

babysit them, push them along,

1:21

particularly for those complex tasks

1:24

rather than truly being able to delegate

1:26

your work.

1:28

And that's the reason why we're so

1:29

excited about Grockbot.

1:32

With Grockbot, marketing teams can now

1:35

actually start to automate away true

1:37

pieces of their work. You can think of

1:40

Grockbot as always on asynchronous AI

1:43

teammates that actually do and finish

1:46

the work on your behalf. And most

1:48

importantly, they'll do it the way that

1:50

you do it.

1:54

And today I'm excited to demo how on the

1:56

SpaceX marketing team, we not only use

2:00

bots to automate jobs and tasks, but we

2:03

actually use them to staff up functions

2:05

and create teams of bots to actually do

2:08

the work for you.

2:11

But first, let's do a quick intro of the

2:12

product. For those of you who haven't

2:14

tried it out yet, this is Grockbot. And

2:17

now some of you may be wondering how is

2:18

Grockbot different from all the other AI

2:21

tools and chat bots that I might use

2:23

today.

2:25

What's different about Grockbot is that

2:27

rather than working with one agent or

2:29

one chat with multi-threaded

2:31

conversations,

2:33

you create individual bots for each job.

2:36

And what that means is you think of one

2:38

bot to be a singular teammate that you

2:41

then delegate away a single task or a

2:43

set of related tasks.

2:46

What this also means is that you can

2:48

actually message your bots and talk to

2:49

them just like you would Slack or

2:52

message someone on Teams. Uh, and to

2:54

take it a step further, bots can start

2:56

to talk to each other and actually

2:57

collaborate with each other within group

2:59

chats as well.

3:01

And as you continue to work with your

3:03

bots, they'll learn how you work.

3:05

They'll learn your preferences. They'll

3:07

learn your memory. And they'll get

3:08

smarter and smarter and get closer to

3:11

the way that you actually do the job

3:13

yourself. So, similar to someone on your

3:16

team or someone that you collaborate

3:17

with, the more feedback you give and the

3:19

more you invest in your bots, uh, the

3:22

more they'll be able to do for you in

3:23

the long term.

3:26

And what makes bot especially unique is

3:29

that while it can hook up to all the

3:30

MCPS and APIs that you're currently

3:32

using today, it also has its own

3:35

computer. And that's a bit of a novel

3:37

paradigm shift from how you might be

3:38

using other AI tools today. And what it

3:42

simply means is that because it has

3:44

access to its own browser and its own

3:46

computer, so long as you give it access

3:48

to it to tools that you use, it can

3:50

actually use those tools just like you

3:52

would.

3:55

So what does this all mean for

3:56

marketers? If we talk about how it can

3:59

use tools just like you, that means that

4:03

your bot, you can teach it specific ways

4:05

that you like to optimize your bidding

4:07

strategy in ad platforms or the nuances

4:11

and how you put together a campaign

4:12

brief or maybe just how you like to

4:14

manage your computer. But ultimately,

4:16

what's really unique and valuable about

4:19

bot is that it becomes customized and

4:21

flexible to the way that you work.

4:24

And with bot, you'll also find that

4:27

you're no longer having to babysit and

4:28

push along and really, you know, remind

4:31

the bot to keep working. And rather,

4:34

Grockbot is extremely ambitious and it's

4:36

also very proactive. And so now you'll

4:38

be working with a team of bots that

4:40

actually want and will finish the work

4:42

for you. Um, and that's quite different

4:44

from other tools you might be using.

4:48

Because bot is hosted in the cloud, that

4:50

also means that they're running 24/7. No

4:52

more keeping your laptop open or needing

4:54

a Mac mini setup. And for marketers,

4:56

that means if you have reporting or

4:59

metrics that you're you're looking at on

5:01

a regular basis, you can trust that

5:03

Grockbot will be able to pull those down

5:05

for you.

5:07

And the best of all, as you might have

5:08

noticed, it's really simple to use. This

5:10

UI is as familiar and intuitive as

5:13

iMessage, which really lowers a barrier

5:15

to entry for any marketer, no matter

5:17

what their specializ specialization is

5:19

to weave agents into their daily

5:21

workflows.

5:24

Okay, so let's actually dive into what

5:27

we're going to do today during the demo.

5:30

Uh what we're going to do together is

5:31

actually launch a marketing campaign

5:33

from scratch from end to end. Um,

5:36

meaning we're going to start from the

5:38

first task that we typically take on,

5:40

which is market research analysis. We're

5:42

going to go all the way through to

5:44

ideulating and betting on positioning,

5:46

uh, updating a landing page,

5:49

starting to build and monitor ad

5:52

campaigns, draw that analysis, and then

5:54

actually end with automation. Now, this

5:57

is a lot of work. Uh, there's a lot of

5:59

things that happen behind the scenes.

6:01

For all of us in the room as as

6:03

marketers, you know that this slide

6:05

might look simple, but actually it

6:08

actually spans across many different

6:10

teams, functions, disciplines within a

6:13

typical marketing or meaning the person

6:16

who conducts market research is, you

6:18

know, having to work with a product

6:20

marketer to identify and best

6:22

positioning who then has to pass off a

6:24

task to the web team and so on and so

6:26

forth. And for anyone who's done

6:28

marketing before, that context

6:31

management, the coordination, the

6:34

orchestration of a campaign like this,

6:36

that's truly where the craft of the work

6:37

happens because it's the crux of our

6:39

job.

6:41

So today, I'm going to introduce you to

6:43

my marketing team of bots. And I would

6:46

be remiss to say that I built all these.

6:48

I was crowdsourcing these across the

6:49

entire SpaceXi team, uh, which is a

6:52

feature I'll talk about. But I'm excited

6:54

to show you how you can orchestrate an

6:56

entire campaign build across the entire

6:59

flow. So you can say hi to our market

7:01

researcher, our product marketer, our

7:03

website ops performance marketer,

7:05

marketing analyst, and lastly our

7:08

project manager.

7:11

So with that, let's dive into our demo.

7:15

Now for the sake of our demo we have uh

7:17

launched a brand new product and it is

7:21

called XAIR.

7:23

So this is an airline product that we

7:26

built as something that we can use to

7:28

build a net new campaign for. And you'll

7:31

see that this landing page is set up.

7:34

It's our homepage. People can do some

7:37

airline route searches, look for fairs,

7:40

and then we have some positioning and

7:43

value proposition, value propositions

7:45

currently in place. So, I'm going to

7:47

navigate to my Grockbot instance. And

7:51

just to walk through what you see on the

7:53

screen on the left side, sidebar, that's

7:55

where the bots live. I've pinned them to

7:57

the top, similar to what you might do in

7:58

iMessage. And I'll be flipping through

8:01

each bot and I'll explain what I'm doing

8:03

as I'm going through it. But let's get

8:05

started with the market research bot. So

8:07

what I'll say first is, hey market

8:10

researcher, what I'd like you to do is

8:13

study the X error website. Get a deeper

8:16

understanding of what the product is,

8:18

what market we're operating in. And now

8:21

I want you to go do a competitive

8:22

analysis.

8:24

identify and deeply understand our

8:26

competitors. Look at their marketing

8:28

websites. understand their positioning

8:29

and then importantly identify the gaps

8:32

and opportunities that we have to

8:33

actually strategically

8:35

um competitively position against them

8:37

within our marketing strategy.

8:41

So just dictated a prompt. I'm going to

8:44

set this off. Now the market researcher

8:47

bot is actually going to go and scrape

8:49

the website. It's going to understand

8:50

the product and then it's actually going

8:52

to go find the competitor competitors

8:55

their landing pages and start performing

8:57

this analysis.

8:58

So, while that's running, let me just do

9:00

a quick walkthrough of the additional

9:02

bots that we have. Um, we have a product

9:04

marketer bot, website ops performance

9:06

marketer,

9:08

marketing analyst, and a project

9:10

manager.

9:11

And

9:13

importantly, what I'm about to show is

9:15

that as this works, you can actually

9:17

kick off jobs asynchronously. Meaning,

9:20

you might have one bot that you work

9:21

with uh as your main point of contact,

9:23

but you can actually kick off work in

9:27

parallel. across a team of bots and that

9:29

means that orchestration is happening in

9:31

the background uh because the product is

9:33

always on. So market researcher is

9:35

saying it's pulled xair the competitive

9:38

asset is being identified. It's going to

9:40

show us a screenshot first of the

9:42

website and then go through gaps and

9:45

positioning.

9:49

Great. So it has its first output of an

9:52

analysis. It's talking about the

9:54

product. It's talking about the market.

9:56

is has identified key competitors. These

9:59

are all airlines that we're all familiar

10:00

with. Um I think most importantly it's

10:03

identify the gaps and where to lean in.

10:05

So similar to how you might work with a

10:07

market researcher, you ask, "Hey, I'm

10:10

launching this new feature. I'm going to

10:11

have this new exciting campaign launch.

10:13

Help me understand what's currently in

10:15

market." So we un we are optimizing for

10:18

breaking through the noise and actually

10:20

landing and resonating with our target

10:21

audience. So I think the most important

10:23

note here is you know these gaps around

10:26

useful time day design uh long hauls and

10:30

then really leading every message with

10:32

useful time which is something I think

10:34

is resonating at least with me and it's

10:37

also shown me that it's pulled up the

10:39

website and this is actually a view of

10:41

its browser that it has access to and

10:43

that it controls and it's showing me

10:46

progress updates of it working in the

10:47

background and being able to actually go

10:49

to the website itself, pull down a

10:51

screenshot and show to me uh how it's

10:53

progressing.

10:55

Now, marketer researcher has done one

10:57

task, and that's great. What I could do

10:59

is actually kick off another one, but

11:01

what I'm going to do instead is actually

11:03

go to the next bot, and that's the

11:04

product marketer. And I'm going to have

11:06

the product marketer actually do a

11:07

handoff of that work that the researcher

11:10

just did and take that into their work.

11:15

Okay, product marketer, what I'd like

11:16

you to do is now go to the market

11:19

researcher bot, do a handoff of the

11:22

analysis that just performed and I want

11:25

you to draw up a draft of a positioning

11:28

brief where you identify how we should

11:30

go to market, what our one oneliners

11:32

are, our positioning and packaging, um

11:35

some value statements, and then also

11:37

show me some examples of how this should

11:40

come to life across two or three

11:42

different marketing services.

11:47

So, as this is running, what you'll see

11:50

is in the chat, the product marketer bot

11:53

is starting to kick off this work. I

11:54

told it to actually go and speak to the

11:56

market researcher and actually grab that

11:58

context and information. Um, as it's

12:02

working, you'll see there's a visual

12:03

indicators. It's, you know, doing

12:04

things. It's running in the background.

12:06

Um, and then it'll actually show you,

12:08

hey, I exchanged a few messages with the

12:11

market researcher bot. And that's

12:13

showing that they're starting to

12:14

collaborate. And that's something that

12:17

you can tell it to do in the beginning,

12:18

but over time, it gets smarter and

12:20

smarter and smarter. And it will

12:22

actually do it proactively, meaning you

12:24

have to be less involved in doing the

12:25

orchestration of context and knowledge

12:27

between your bots, and rather they

12:28

actually start to work with each other

12:30

organically.

12:31

So, it's telling me it's grabbed the

12:34

market researcher analysis. It's

12:36

drafting the positioning brief. Um, it's

12:39

created a Google doc where it's actually

12:42

starting to draft that position brief

12:43

which we'll jump into. And inside it's

12:45

telling me what exactly it did.

12:48

So,

12:50

let's bring this up.

12:55

And if we go through this, this is

12:57

looking like a solid first draft.

13:00

Um I think what what I will do is start

13:04

to read through this. It has a research

13:06

handoff that I got from the market

13:08

researcher is identify the target

13:10

audience long haul travelers who want

13:13

useful time back. I'm going to leave a

13:14

comment and say this is great. Lean into

13:17

this in our messaging.

13:23

It's talking about positioning and

13:24

packaging and how we should be thinking

13:26

about our marketing strategy and the way

13:27

go we go out with messaging.

13:30

And it's also left some notes on go to

13:31

market, some additional oneliners about

13:34

different types and angles to lean into

13:37

and then some value statements and

13:38

examples of how it shows up. So there's

13:41

a paid landing page here that is

13:42

drafted. I think what we'll do for our

13:45

campaign is actually take this page,

13:47

shove it up into the website, launch the

13:50

landing page, and actually start

13:52

directing and building an ads campaign

13:54

to do a messaging test to see what's

13:56

landing the most and what's resonating.

13:59

So, I'm going to close this and I'm what

14:02

I'm actually going to do is tell it,

14:04

"Hey, product marketer, I've just left

14:06

some comments inside of the Google doc.

14:09

What I want you to do now is go through

14:11

the Google doc, take the comments and

14:13

the feedback, incorporate it into an

14:15

updated draft. And while you're at it, I

14:17

also want you to build out a full

14:19

outline of the landing page. And then I

14:22

also want you to ideulate and draft some

14:27

Google search campaigns to do variant

14:30

testing between the copy angles that you

14:32

drafted.

14:37

Now again, this is all happening within

14:39

one bot right now, but what it's doing

14:41

is flipping it back and forth between

14:44

market researcher bot to make sure that

14:45

it has the right context. is going into

14:48

the Google Docs which I've connected

14:49

through uh the MCP to be able to

14:52

actually look at the comments, look at

14:54

the feedback and incorporate into a new

14:56

draft. So, it's telling me, okay, it's

14:58

I'm reading your comments now. I'm going

15:00

to update the brief, expand the landing

15:02

page outline, and then start drafting uh

15:05

search ad variance inside the sheet,

15:07

which is great because that's typically

15:08

how performance marketers work.

15:12

Now, while this is happening, it's

15:14

reddrafting the file. I'm actually going

15:16

to flip over to my performance marketer.

15:18

I'm going to say, "Hey, performance

15:21

marketer. Uh, I would like you to start

15:24

creating a shell campaign inside of

15:26

Google Ads. And what I want you to do is

15:28

build it so that it's optimizing for

15:30

clicks because we're going to do some

15:31

copy and messaging testing that's being

15:33

drafted by the product marketer right

15:36

now.

15:37

So, before this demo, I actually hooked

15:40

up um this bot into my our Google Ads

15:44

account. What's happening is it now has

15:45

access to it. And when I kick this off,

15:48

it'll actually go into it and you'll be

15:49

able to see because it'll show

15:51

screenshots of how it's starting that

15:52

build and it'll be able to actually do

15:54

the clicks for me um and start the shell

15:57

campaign that can start uh trafficing

15:59

the ad copy into.

16:03

So, let's flip back to product marketer.

16:06

There's an updated brief. We can open

16:09

it. Comments are resolved.

16:14

Looks like it's in a good state. It has

16:16

a fuller landing page outline uh that we

16:20

can implement. It also has more built

16:22

out campaign variants which I believe

16:24

are also inside this sheet where it has

16:28

variant name, hypothesis, ad group name,

16:30

etc. as well as the URLs and then it's

16:34

also built some additional copy variants

16:36

here. So all this is happening in the

16:38

background. You know I've kicked off two

16:39

or three jobs in parallel. Um, but the

16:42

best part is that they're all sharing

16:43

context with each other while not

16:45

tripping over themselves to get their

16:46

work done.

16:49

Okay, this is feeling pretty good. What

16:50

I'm going to do now is I'm going to go

16:52

to website ops and I'm going to tell

16:54

them, okay, so landing page outline is

16:58

drafted. What I want you to do now is

17:01

take the landing page from the latest

17:03

brief that the product marketer just

17:04

drafted and spin up a PR to actually

17:07

push that as a new landing page into the

17:09

website and send me screenshots as

17:11

you're working so I can keep monitoring

17:13

your progress

17:18

on the back end. Again, this bot is

17:21

hooked up into our repo. It has access

17:24

right access to our landing page and our

17:26

marketing site. So, it's now able to

17:28

actually leverage what's under the hood

17:30

is cursor to be able to go write the

17:32

code, look at the copy, get the handoff

17:34

from the product marketer and actually

17:36

ship a new landing page to the marketing

17:38

site.

17:41

So, it's going to pull down the latest

17:42

product marketer brief. It's going to

17:44

open the PR. It's also going to show me

17:46

progress screenshots as it works.

17:50

Meanwhile, if we go back to performance

17:52

marketer, um, it's successfully gone and

17:55

found the copy that was drafted. Uh, it

18:00

has shown me some screenshots of it

18:03

actually starting to build the campaign

18:05

inside of the platform. And we'll let

18:07

this keep running as we finish up the

18:09

landing page.

18:13

Okay.

18:15

So, you can see how it's working

18:17

through. uh it is going to take a

18:20

landing page, it's going to update it

18:21

with the latest full uh paid landing

18:25

page outline that's passed off from the

18:26

product marketer and we'll actually be

18:28

able to ship this and you know ship it

18:31

to production um and see the updates

18:33

come to life.

18:37

Okay. So, while this is running, um I

18:39

would would like to show a feature that

18:43

uh I think is really special. It's quite

18:44

unique from the way that you might be

18:46

using other a AI agents now, which is

18:48

our sharing feature. Um, so something

18:52

really unique about Grockbot is that

18:54

while you can create these really

18:56

robust, powerful bots within your

18:59

workflow that are customized to the way

19:01

you work, you can continue to feed it

19:03

context and memory and build routines.

19:06

You can also turn those into templates.

19:09

And this is where I'll show you. You

19:11

share as a template. You're prompting it

19:13

to say, "Hey, I want you to create a

19:15

template of yourself that I can then

19:17

share with someone else." And the

19:19

implications of that are pretty powerful

19:20

because that means you can not only take

19:23

a snapshot of your bot in time and turn

19:26

that into a duplicatable

19:29

uh bot and agent that you can share with

19:31

your team but also people externally.

19:34

And what that means is for the receiver,

19:36

they are then have access to literally

19:39

the way you work because you've injected

19:41

all this context, your expertise, your

19:44

specialization directly into this bot

19:46

and they can easily take it, copy and

19:49

paste it directly into their Grockbot

19:51

instance and then start using it uh

19:53

exactly the way you would.

19:58

All right. So, uh, looks like it is

20:02

working on getting this page up.

20:06

It's still writing the page in the PR

20:09

and it'll show me when the preview is

20:11

up. So, while that's working, what we've

20:13

done so far, just as a quick recap, we

20:15

started with the market researcher.

20:18

We asked it to do an audit of our

20:20

product page, understand the product,

20:22

identify identify competitors, and then

20:25

give us strategic guidance on the gaps

20:27

and opportunities. That was passed off

20:29

to the product marketer to then draft up

20:32

a positioning brief, which it did in

20:34

Google Docs. I was then able to go into

20:36

that document, leave comments and

20:37

feedback, and then go back to the bot

20:39

and say, "Hey, fix this." The same way

20:42

that you might give feedback to someone

20:43

on your team when they're drafting a

20:44

document. It's done that rev. and come

20:47

back and said, "Great, I did that. I

20:49

also created an outline for a paid paid

20:52

landing page, and I'm also drafted this

20:55

copy that you can then traffic into your

20:57

ads."

20:59

That outline is now being worked on by

21:01

the website ops, which I'll give it um

21:04

it's currently working through this, and

21:06

that is going to be turned into a

21:07

landing page update that I'll push up

21:09

and we'll be able to host on uh the main

21:12

site.

21:14

performance marketer has started to

21:15

build the campaigns, built the shell,

21:17

and that copy is being fed into the way

21:20

that the campaign will be structured so

21:21

that we're getting that message test

21:23

live. And as this is running, um, rather

21:27

than needing to actually push the

21:29

campaign live here, because that would

21:30

require obviously like some additional

21:32

guidance on spending the budget and

21:34

hooking up a credit card, um, I've

21:36

actually already launched a campaign uh,

21:38

this week. And so what I'm going to do

21:40

is actually tell my marketing analyst,

21:42

hey, you're already hooked up to my

21:44

Google Ads account. I want you to

21:45

actually pull down that data and give me

21:48

insight and analysis into how the test

21:50

performed.

21:52

Hey, marketing analyst, what I want you

21:54

to do now is go into Google Ads. I want

21:58

you to pull down the data from our last

22:01

uh experiment on messaging, analyze it,

22:05

tell me the TLDDR of the insights, and

22:08

then give me recommendations on how we

22:10

should incorporate it into our marketing

22:12

strategy as well as update the other

22:13

assets that you've seen.

22:26

Okay. So, what this is doing now, it's

22:27

actually going into uh Google Ads

22:30

platform. It has access through that

22:32

through the API. It's going to pull down

22:34

the information, pull down the data, and

22:36

it'll be able to structure it into an

22:37

analysis that's all going to be living

22:39

within this chat here.

22:42

So, it gives me the TLDDR. It's pulled

22:44

this copy test down from copy from the

22:47

Google ads. Um, it has a clear winner uh

22:50

that's analyzed across different

22:51

variants of brand, customer promise,

22:53

hours in between, cheap that cost a day,

22:55

etc. Um, it has key metrics, spend, CTR,

22:59

CVR, etc. All the things that we care

23:01

about. I think most importantly, what

23:03

it's done is it's actually made

23:04

recommendations. And this is obviously

23:06

where there's some debate of how much,

23:09

you know, liberty do you give your agent

23:10

to, you know, actually make those

23:12

decisions for you. But I think in this

23:14

case, it's making recommendations that I

23:15

can then intake, you know, discuss with

23:19

the team, but also guide it to actually

23:21

make decisions on my behalf. Um but it's

23:24

made that entire process smooth and

23:27

without any dependencies that you might

23:29

otherwise have uh in a traditional or

23:33

okay so now we've finally gone through

23:35

every single piece research positioning

23:38

landing page which I will nudge one more

23:41

time push the page to prod

23:45

uh building the campaign inside a bot uh

23:48

that has access into your account from

23:50

the Grockbot instance

23:53

We've run the analysis. Let's pull that

23:55

down. And you might have noticed that

23:58

during this entire demo, I have to be

24:00

the one actually orchestrating. And to

24:03

go back to my earlier point, that's

24:04

really where the taxes, right? It's a

24:06

context switching. It's a having to know

24:09

the players, understand who's good at

24:11

what, and sort of like trafficking and

24:13

managing that entire process across the

24:14

entire workflow. Um, and that is

24:17

actually something else that you can

24:18

dedicate or delegate to Grockbot.

24:22

So now with my next and final bot, which

24:25

is the project manager, what I'm going

24:26

to tell it to is to do is actually study

24:29

the entire orchestration flow that we

24:31

just went through and then automate it

24:33

so that I don't have to be managing the

24:36

context, information, and communication

24:37

between all the different bots all the

24:39

time.

24:41

Hey project manager, I want you to now

24:44

study and talk to each of the bots in my

24:46

team and understand what each of their

24:48

roles is in bringing a campaign to life.

24:51

I want you to also look at our

24:53

conversations and look at where I had to

24:55

interject or give guidance or give

24:57

feedback and weave that into the way

24:59

that you work with them. And I want you

25:02

to also now kick this off and automate

25:05

it completely with three new campaigns.

25:08

send me screenshots and progress updates

25:10

that can stay in the loop. And most

25:12

importantly, I want you to now be my

25:14

point of contact, meaning I don't want

25:15

to talk to any other bots. I only want

25:17

to talk to you to save myself the

25:19

context switching.

25:23

So, I've now delegated away the entire

25:27

process of a campaign build and

25:29

throughout that identified, okay,

25:30

there's like tax and additional work

25:33

needed to actually make a campaign

25:35

happen from start to end. And the final

25:37

piece is actually taking another step

25:39

back and saying I'm just going to have

25:42

Grockbot do that and play the role of

25:44

project manager, coordinator, handoffs,

25:47

sharing the context, pushing the team

25:49

along. And I think most importantly,

25:51

what's most valuable is the fact that

25:53

you no longer have to context switch and

25:55

be bombarded with five different

25:57

messages from different uh individuals

26:00

or bots on your team. And that gives you

26:02

the clarity to be able to zoom back out

26:05

and really start to direct and uh direct

26:09

your energy and time towards where the

26:10

most leverage is.

26:14

So you'll be able to see it's saying

26:16

that it's the only um this bot is now

26:18

the only point of contact here. It's

26:20

studying the five specialists and it's

26:22

going to create and kick off three net

26:26

new campaigns that it'll then show me

26:29

screenshots of. So, it's identified

26:31

these are the campaigns we're going to

26:33

do research, positioning, landing page

26:35

build, etc. That's all queued up. Um,

26:38

and it will continue to keep me in the

26:39

loop so that I can continue monitor, but

26:41

I don't have to be directly involved in

26:43

every step of the process.

26:49

All right. And finally, we have uh a

26:52

website that we built up and running.

26:56

It's shown that it's actually pushed it

26:58

to prod.

27:00

And if I ask it, give me the URL.

27:04

It'll also give me the URL

27:09

that we can open C. And so this is the

27:11

URL that we drafted, went through

27:13

positioning, etc., and actually pushed

27:14

up to prod all from the one place where

27:18

all the work is happening, the Grockbot

27:20

workspace.

27:24

Okay. And that's it. That's our demo.

27:28

[applause]

27:32

So, just to wrap that up, um, what have

27:34

we learned by going through an entire

27:37

campaign build from start to end?

27:40

The first point is, uh, what's really

27:42

important when you're starting off with

27:43

Grockbot is to ensure that you're

27:45

scoping your bots properly. And the way

27:47

that I like to think about this is that

27:49

when you identify a bot or a job that

27:51

needs to be done, it's almost like

27:52

crafting a job description. Meaning

27:55

you're identifying a new teammate that

27:56

you need help from. You understand the

27:59

swim lanes and roles and

28:00

responsibilities and you're ensuring

28:02

that it's scoped tightly to ensure that

28:05

they are specialized and they're able to

28:07

get that specific uh piece of work done.

28:11

Uh because that's the way you squeeze

28:12

the most efficiency out of your team of

28:14

bots.

28:16

Second, you want to trust your bots. Uh

28:18

as you might have seen, these teammates

28:21

are ambitious. They're proactive.

28:23

They're hungry. They want to do your

28:25

work. And that starts with giving them

28:26

the access they need. Meaning, one of

28:28

the first steps you might take is

28:30

hooking them up into your Slack

28:32

instance, your email, and actually maybe

28:34

asking it like, "Hey, go study all the

28:37

context, all the messages, all of my

28:38

organizational history, and tell me what

28:40

you can do for me and take a take a job

28:42

off my plate." Um, but I think if you do

28:44

that, you give them the access, you

28:47

throw ambitious tasks against them,

28:49

you'll be surprised uh by what they're

28:51

capable of.

28:53

And finally, I've said this over and

28:54

over, but you want to invest in your

28:56

bots. They really get better and better

28:57

over time. You know, the point of

28:59

collaboration between botto is something

29:01

that gets uh more organic, especially as

29:03

you prompt it. Um, but they also improve

29:06

steadily as you start to feed it more

29:07

feedback, more context, more memory,

29:10

similar to how you might work or manage

29:12

a teammate, where the more feedback you

29:14

give them, the more time you invest into

29:15

them, the more they'll compound in value

29:17

and be able to take more and more off

29:18

your plate.

29:20

Lastly, here's a plug. Uh, this QR code

29:24

goes to our bot marketplace. And the

29:26

marketplace is actually where we take

29:28

the very best bot templates like the

29:31

ones that I shared, um, and host them.

29:34

Meaning, you might be able to create

29:35

your own bots and prompt them and build

29:37

up, you know, really rich context and

29:39

memory, but you can also just copy

29:41

others. And that's what I did is when

29:43

building out this demo, I crowdsourced

29:45

across the entire team. I said, "Hey,

29:47

who has the best positioning bot? who

29:48

has the best ads bought, etc. Um, and

29:51

you can find all of those on our

29:52

marketplace. So, I can encourage you to

29:53

go here and be able to copy them down.

29:58

And with that, that's it for me. Thank

30:00

you so much for your time. And I believe

30:02

we have some time for questions.

Interactive Summary

Josh Kim from the SpaceX AI team introduces Grockbot, an AI agent platform that shifts the paradigm from simple chat assistants to autonomous, asynchronous teammates. He demonstrates how these agents can be specialized for specific roles like market research, product marketing, and web operations. By using their own virtual browser and computer access, Grockbot agents can execute complex tasks such as writing code, building ad campaigns, and performing data analysis. The presentation culminates in showing how a Project Manager bot can orchestrate these specialists, automating entire workflows and eliminating the need for human context switching.

Suggested questions

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