The Rise of Digital Workers: How 11x is Replacing SaaS with AI Agents

Hello and welcome back to another

episode of the GDM playbook podcast. I

am super excited to chat with our guest

today. This guy is a serial entrepreneur

who's founded multiple startups,

including a successful exit to the

multi-billion dollar fintech giant Brex.

He's also an active angel investor with

a personal portfolio of over 40

companies. And if that's not impressive

enough, he is now the CEO of 11X, an AI

startup that's building autonomous

digital workers with a mission to

completely change how go to market teams

operate. In today's episode, we're going

to unpack how digital workers are

reshaping the GTM playbook and what the

future looks like when AI isn't just a

tool to assist humans, but a co-orker

working alongside them.

[Music]

Prahav, welcome to the podcast. It's

great to have you on the show.

>> Thank you for having me. Pleasure to be

here.

>> All right. Well, let's kick off with

your story, which is a super interesting

one. From being an MIT graduate to a

founder to having a successful exit to

now leading one of Silicon Valley's most

talked about AI startups. keen to know

how did this whole journey unfold and

what led you into the world of building

and scaling tech companies.

>> Yeah, totally. I mean it's it's a great

question. You know, whenever you look

back at your your own kind of

background, it's always really

interesting to be like, how did I even

end up here? So, I guess for me, I've

always been a builder. Uh my dad was a

programmer. So, I started playing with

computers when I was really really

young. I was probably like um had my

first laptop when I was in I don't know,

kindergarten or first grade. Um, and so

pretty early on I was always like

dabbling with things, but I would say I

really got into like technology and

building things with technology when I

was in high school. So in one of the

first side projects I worked on when I

was in high school became like this

massive hit like had millions of users

and I was like this like little kid

sitting in his room uh you know in San

Diego, California made something put it

up because it was useful for me and now

suddenly all these people are using it.

I'm like, wow, like you have like a real

impact and actually build something that

uh affects a ton of lives. And I that

kind of insight is what led me to, you

know, after that I I um went to MIT um

and I spent a lot of my time there also

working on side projects or doing

research and spending not as much time

in actual classroom and you know um I

met a few really awesome friends in in

college and so I wanted to graduate

early to start working on my first

startup and you know as startups go we

had this really lofty lofty mission

which was we want to organize the

world's knowledge think like

uh cross with like a medium cross with

like a Google Docs, right? You know, we

ended up raising a pretty large uh seed

round with some amazing investors from

Silicon Valley and we're kind of off for

a racist but you know first startup

young inexperienced founder knew how to

build stuff but but nothing else, right?

Um and so I probably made every mistake

you can imagine in the books. Um I spent

a ton of time just like building cool

stuff and not enough time with customers

to make sure we're solving like really

big problems. You know, we're really

fortunate because we were a team of

builders to get kind of acquisition

interest, but we were kind of enamored

by this idea of organizing the world's

knowledge. So, we kept building.

Eventually, we pivoted that company

slightly to be more of like an AI

powered community discussion platform.

We felt that was the most frictionless

way to actually get knowledge into the

system. What we realized was that the

types of communities that were taking

off on our platform were learning

communities. So people were trying to

actually learn a specific skill

together. So we doubled down on that and

built found the best platform for

creating content um and learning. And

this is like pre-Gen AI. We had a bunch

of AI stuff into in our platform. And so

when we had this generative tech, we

started getting a lot of acquisition

interest again from a lot of folks in

the e-learning space. And that's

ultimately where Brex came in. Brex like

look, we're not in e-learning, but we

want you to come build a lending

business. And I'm sure you know we can

teach you everything you need to know

about finance but you know what we're

really looking for is like hungry

builders and hungry founders. So

ultimately we solar company to breed

launch our first capital products and

lending business and I ultimately grew

to leading all of engineering for

financial services. This is our credit

card product, our banking product, our

global products, our risk teams, our

money movement infrastructure,

onboarding rewards was a core part of

our business.

That was an insane journey, right? I

joined was a couple hundred people, left

when it was over a thousand people.

At this point, Brex had gotten really

big and I was really itching to kind of

go back to to to early stage. And so,

you know, when I look back, it's like

when I was a founder, I was really good

at building things and bringing these

products to life, but it was more

challenging for me to go to market

pieces. So, helping build these AI

agents that let companies grow by

automating a lot of the manual labor

that people have to do to grow was

really attractive to me on a personal

level. And so, the thing that got me

really excited and why I chose to join

Level X was that the second order

effects. So today a typical company

probably spends about 40% of their

entire revenue on sales and marketing.

And for me I was like okay if I'm able

to automate all this manual labor and

all these costs like what happens like

you actually can now pass on those cost

savings to end consumers. So today like

you know instead of something costing

thousands of dollars now it can cost

hundreds and so you open up a completely

new economic model of growth for

companies out there. It was the same

thing that like the cloud did for a lot

of companies. Like now we can pay

Netflix $15 and get access to like the

entire corpus of the world's content,

right? It's super cheap. There's no way

you could have done that and once cloud

became a thing. And that's the same

thing I think agents is going to do for

for go to market.

>> Yeah, absolutely. And was that that like

aha moment that you had when you know

you first came across X and you're like

you know this doesn't just look like

another product, another software tool,

but you know something that's going to

be much bigger.

Exactly. Exactly. It's also like the the

kind of problem technology fit was just

so clear, right? And and and the biggest

thing for me was like this technology

now enables all these things that just

weren't possible before and had been

bane for so many companies grow. Um and

so I think that fit was like the key

thing.

>> You mentioned before that you made every

mistake under the sun during those early

years and almost going through your own

business apprenticeship. keen to kind of

unpack like what were some of those key

lessons that you learned during those

early days that have shaped how you

operate today?

>> Yeah, you know, it's it's interesting.

One of the biggest things I learned was

how to dream really big and work

backwards to get there from where you

are today, right? Something I learned

from the from the founder of Brex and

that means that you take a bunch of baby

steps. you keep moving towards this end

really big lofty goal that you have and

you know the only people that have ever

achieved these massive unthinkable

things were like the crazy ones to try

right to try to do these things and so

in terms of like the challenges we faced

you know and the problems we had like

the biggest thing was just not giving up

because that means you have another shot

tomorrow that means you get to try again

right I remember across my first few

startups I probably tried so many

different ideas and pivoted for like

seven years right that's kind of the

length of time I did when I was trying

my first first batting at like these

startups. It just made me learn so much

about problem solving across not just

product engineering but sales, customer

success, marketing, communicating both

internally and externally. All these

skill sets I I would have never picked

up if I just went into you know

corporate job out of college, right?

Because you're forced to do everything.

And so I think the you know the journey

at Brex uh when I grew quite quickly

internally you know I started as like a

team lead of like three or four people

went to uh leading our most largest and

most critical engineering organization

the company. Um that growth also

prepared me because like okay like you

can just go and do things right as long

as you optimize for the business and for

your customers like you can get a kind

of success. And so I think like those

were the biggest lessons for me just

like never give up, keep trying, right?

Keep getting better every single day. Um

and then focus on the business.

>> Yeah. So so true. I speak to a lot of

founders and that never giving up piece

and that resilience I feel is the common

theme when it comes to those key

attributes in entrepreneurs. It's that

ability to push through when things get

tough and not you know you giving up in

those scenarios which what sets them

apart. Cool. Well, now keen to now kind

of transition into your time at 11x.

Like if you can walk me through like how

did you get started? Like you know, how

did you get involved with the company?

>> Yeah, you know, it was it was

interesting. Um actually had like an

executive recruiter reach out to me uh

of all things and you know, she had this

like interesting thing of like, hey,

this company doing something kind of

crazy, really small team based in

London, like you should talk to them.

I'm like, oh, okay, sounds sounds kind

of interesting. And as I dug in like

more and more, I just I realized like

how much time, effort, tooling, costs,

enablement, it took modern go to market

teams to be efficient. It kind of

reminded me back in the day when you had

these really large IT teams to manage

all these custom servers just to like

launch a website and then like AWS, you

know, Amazon Web Services came out and

suddenly like you could have like these

two people sitting in their room and

launch a website globally, right? And I

think that massive impact of that

technological change on the world like

we're still seeing that today. And I

think the liberalization for me was like

this is this is go to markets moment

right and so that's where this notion of

like X being like an engine for

company's growth really started to

hammer home for me because we've

consolidating not just all the software

that folks were using but all the manual

labor as well. So then became a platform

where you're only limited by your own

creativity. Um, and that was like the

big compelling thing that led me to

join.

>> And for anyone not familiar with X, if

you can just explain for us what exactly

does 11X do and what specific problems

does your product solve for GDM teams?

>> Yeah, totally. And you know, maybe maybe

to motivate this. Um, I I'll talk about

like like let's say you're a typical CRO

or revenue leader today, right? One of

the biggest things you have to do is

grow pipeline. If you don't have

pipeline, you don't have sales. If you

don't have sales, you don't have

revenue, right? And kind of the job of a

company is to grow revenue, right? And

so

growing pipeline through these

traditional channels has gone really

really really hard, right? Today every

company has some version of the same go

to market playbook, the same tools, the

same data, the same outreach tactics. So

what used to work at scale in the past

now just kind of blends in to the noise,

right? So today's go to market teams

they juggle 20 plus disconnected tools

to run their pipeline generation plays

across outbound across inbound and now

you need specialized

expensive teams to even orchestrate

these things like we have a new new role

in the market right the go to market

engineer and that's what's required

right to actually make these things work

and so you know every new SDR you hire

takes months to become productive they

need access they need training they need

context across all these systems before

they can even and an intelligent piece

of outreach, right? And let's say now

they're fully ramped, you know, a couple

months later, but your product and your

messaging is changing. So you have this

endless cycle of like enablement. It's

the same story for every product launch,

every pricing change, every go to market

pivot. Got to enable everyone all over

again. Um, and then every great idea you

have kind of just dies in this chain.

Like your CRO goes to the CMO, your CMO

goes to product marketing, then it goes

to enablement, then it goes to SDR. And

by the time you actually have something

on the market, like you've kind of lost

the ball already. And so, you know, what

we believe is to kind of break through

the noise, you really need research

driven like persona specific and

hyperpersonalized messaging to real pain

and value at the exact time when a buyer

is in market. So, they need to be able

to engage this buyer across a bunch of

different channels. and they need to be

able to run experiments in hours, not in

weeks. And so, you know, it's a long way

of saying, you know, what LENX actually

does, but you know, we're building the

first intelligent organization platform

across all the go to market stack. So,

Levenx automates how revenue teams

generate, qualify, and convert pipeline

by corning every workflow across all

your data, all your outreach and and

your CRM. So, Lebanon replaces all that

patchwork I mentioned earlier with a

coordinated system of AI agents that

work together like a digital team,

right? Um, we have two workers in the

market today. Alice is our digital

outbound SDR. Alice will find the right

leads, leverage data inside your CRM,

find the right intent signals, look at

our up-to-date, you know, third party

data sources, even search the web for

niche audiences, and look at visitors

coming to your website. And then Alice

will once he's found a set of leads to

go after, we'll do expert level

extensive research. They'll access

public information on the web. They'll

look at news, interviews, podcasts,

reports, and even social posts, right?

I'll combine all of that with knowledge

it has about your company's products,

your services, the case studies and

successes that you've gotten as a

business. And taking all those things

together, it'll generate these highly

relevant and personalized sequences

across multiple channels. and it will

scale that outreach, right? So, it'll

maintain all the email infrastructure,

it'll do all the deliverability, it'll

do everything to make sure that once

you've done all this work, that message

actually lands where your buyer is.

That's kind of Alice. Julian is our on

the flip side, our digital phone agent.

Julian handles inbound and consent to

outbound use cases. So, when someone

signs up for a demo on your website,

Julian calls them back within seconds,

qualifies them, answers questions, and

gets a sales meeting booked. the Jerro

account executive.

>> That's so cool.

>> All in an automatic fashion. Exactly.

Julian can even nurture and upsell your

leads, can help prospects navigate

onboarding, and it operates 247 across

many languages and is super super

integrated into your workflows. Um,

we're also releasing a new new uh new

chatbot soon. So, Julian is now

available not just through, you know, uh

voice, but also through a chatbot.

Underpinning this entire sort of all of

our digital workers is intelligence

layer. you know, you connect them both

together, you analyze what's working

across campaigns, you refine ICPS, you

improve results continuously. That's a

little bit of, you know, what Leex is

trying to do.

>> Yeah. It's so cool cuz like as a GDM

leader like this is so exciting to hear

and you know those pain points and

problems that you just explained is you

know what we've been dealing with for

for decades where you know you've got

these SDRs you're having to train them

up you know they typically have short

tenures and you know I don't think

anyone in sales really wakes up in the

morning and goes you know what I can't

wait to just go and build lists of our

TAM and start researching these like

most sales reps just want to be you know

demoing closing deals making money And

it sounds like your product solves those

problems, which is really exciting. Now,

it sounds like really sophisticated

technology. You know, you've got these

AI agents that are researching and being

able to personalize these email cadences

and messaging to your prospects, calling

up prospects, and being able to

represent your company. If you can just

walk me through like how do you actually

get these AI agents trained up knowing

your product, and what's involved in

that process? And more importantly, like

how long does it take for someone to set

up, launch, and actually start producing

results?

>> Early. I mean, we typically get teams uh

set up and running quite quickly. Uh

couple weeks, right? They can kind of be

fully ramped. And most of the time is

really just taken to like buy mailboxes,

warm them up, uh make sure we have um

all the enablement material. So the way

we describe it to our customers is let's

say you hire STR today. Like what do you

give them? You probably give them like

some enablement materials, some slide

decks, some call recordings, some case

studies, educate them about your

business and your services. So the same

kind of training, the same documents,

the same recordings you're giving to

your human rep, give the same things to

us. Now Alice will learn a lot faster,

right? Because you can ingest a lot of

this content very quickly. Um, you also

tell us about your brand voice, right?

like are you more like edgy or are you

more like empathetic or like give us

give us some more examples of like your

tongue and we'll make sure that Alice

and Julian follow that right so you know

once you give us all this data and like

this data is like I just want to stress

it's super important you put garbage in

you don't get garbage out just like if

you don't enable you know um a rep that

you hire they're not going to do well

right and so agents can run quite

quickly as long as they have the right

data being being fed in So, it's

actually interesting cuz the ramp up

time for an agent is actually much

faster than for a human because the

processing time is super quick.

>> So, it's very similar to just basically

hiring a a new human rep in your team.

Doesn't it doesn't allow for, you know,

poor onboarding. You need to still

onboard them properly, train them up,

but it sounds like at the end of that

process, you know, you've got this AI

agent that works 24/7, you know, doesn't

take sick days, doesn't take smoke

breaks, you know, doesn't take mental

health days and is working for you 24/7.

And in what you've trained it, it

memorizes as well.

>> Correct. And you know, we talked earlier

about this whole enablement piece. When

things change, if you want to change its

knowledge, you just give it new

documents and boom, it's off to a races.

There's not and there's not doesn't take

another 3 weeks to train them, another

month to train them. It takes half a day

now. You just give it a document, you

test it knowledge, and it's good to go.

>> Now, you've positioned 11X as replacing

software with digital workers. Can you

unpack what does that actually mean in

practical terms?

Yeah, you know, we we view ourselves as

a force multiplier on human labor. We

want humans to work on high leverage and

like creative tasks rather than the

wrote repetitive manual work that many

folks in good market organizations do

today. You know, SDRs and BDRs as you

mentioned earlier is a really high term

role, right? Um and it makes sense like

you said, no one gets out of bed

thinking, oh wow, I'm gonna do so much

research today. I'm gonna build all

these lists, right? Then go the emails

and phones. like it's not it's not a fun

repetitive thing to be keep doing kind

of every single day and so for the first

time instead of like you know SAS like

software as a service you have the other

SAS which is you know services of

software right and so you know at 11x we

don't have any BDRs or strs our sales

team can actually create campaigns and

our platform can autonomously build

pipeline you know including cold net new

leads as well as nurturing existing

prospects marketing campaigns and

handling all of our inbound leads right

anyone in our company that has an idea

can just go launch it and test it out

and see how it works, right? It's deeply

integrated with our CRM. So, we're not

reach out to any existing opportunities

or things in progress, right? Um, and

so, like I said, like your only cap on

growth is just now your your creativity.

Like there's no tools, there's no

orchestration, nothing's blocking you

from achieving like the full potential

of your your business.

>> Super interesting. And like now I know

the market is flooded right now with AI

tools. You've got Clay, Instantly,

Unifi, and hundreds of of others. And

everyone I speak to, whether it's at

conferences or webinars,

they tend to give the impression that

they're overwhelmed by the amount of

choice that's out there. And sometimes

that that choice gives a little bit of

AI paralysis and they don't actually

take any action because they don't know

where to start. Can you explain for us

how does a digital worker approach

different to those other tools? Uh, and

if you can walk me through what are some

of the real differentiators that make

11X stand out as well?

>> Totally. You know, if you think about

it, like if you think about just the

history of SAS in general, like today,

if you go to a typical company and ask

them like how many software or tools you

have, they'll probably say hundreds. In

some cases, thousands, right? Because

the way SAS evolved was like we'll do

this like one small thing really really

well, right? But to run a business, to

run a to do your job, you need hundreds

of those small things, right? Hummus

doesn't just do one task. They do an

entire workflow, right? And so today,

what you find is that most products in

the market are still focused on a very

specific slice, right? Maybe they're a

data vendor, right? Maybe they're an

enrichment vendor. Maybe they help you

activate your inbound leads or to just

manage your deliverability or automation

there. That's no different from SAS.

It's smarter, right? You have like the

new new AI intelligence to do it, but

it's the same thing. Now you have

hundreds of little AI agents you have to

orchestrate and put together. So that

burden, that work is still there. And so

we think of ourselves as actually

automating the work, not just automating

one small task, right? So you know,

you'll see that in the market, you have

a lot of these folks aiming to automate

all the work, but most of the time

they're kind of just shallow rappers.

The reason for that is it's very easy to

build a really cool demo, right? But

it's really hard to do it at scale in

production because that's where all the

messiness creeps in, right? For a lot of

these folks, you know, their emails have

like shallow personalization, their lead

data is out of date, their email

deliverability is terrible, their phone

calls quality of phone calls suck,

right? And they're limited to very

specific channels. I have to go buy a

bunch of tools to be like, oh, I got to

do like, you know, automation here. I

got to do automation here.

We've always thought about is like we're

on the business of helping our customers

generate ROI and outcomes. And to

generate ROI and outcomes, got to do the

entire thing. You got to orchestrate the

entire workflow. And so when we think

about 11x it's like okay what are all

various like motions and things a modern

go to market team needs to do to scale

growth. So for your outbound motion we

first start by helping you identify your

ICP when their propensity to buy is

highest by leveraging sensor first and

third party data. We then do a bunch of

research, right, to create these

hyperpersonalized sequences that are

battle tested to not hallucinate, right?

We automate this kind of multi-

channelannel sequence and manage all the

deliverability under the hood. And we

spend a bunch of time getting that

right. You can't build that, right? It

takes months and months and years of

engineering to get these systems to

become battle tested. And now for your

demand gen or marketing motion, we

optimize campaigns that drive event

attendance or traffic to your website or

to your, you know, case study page. For

inbound, we take visitors coming to your

website. We help you anonymize them. We

qualify them and help them book

meetings, whether it's through email

follow-ups or or voice or chat or SMS or

WhatsApp, multi- channelannel

approaches. And on top of all that like

we know today you know go to market

teams live and die by like their source

of truth which is in their CRM right so

you have to have really advanced

in-depth integrations lead routing

ownership mapping birectional syncs pull

in context into campaigns and all that

takes a lot of time to to to really get

right. So we you know what I've always

told the company here at 11x is like

we're going to do the core job really

really really well. We're not going to

focus on the flashy stuff, just to make

sure we do the core pieces and

orchestrate everything together um in an

incredible way. And I would say the

final thing is, you know, we're really

not focused on the SMB market. We're

really for focus on mid-market and

enterprise.

We want to help teams accelerate their

growth, you know, consolidate their tool

sprawl. So you can focus on being

creative rather than all the kind of

plumbing. And we found that typically a

lot of the very small companies, they

have never done outbound before. They

haven't done inbound. They don't have a

good understanding of their ICP and in

many cases they don't even know if they

have product market fit, right? Which

makes it really challenging for us if

we're in the business of helping our

customers generate ROI. It makes it

challenging for us to make them

successful.

>> And you mentioned just before around

some of the key differences between

those that digital workers mindset

versus some of those other tools on the

market. And it sounds like to me your

approach is where it's like you're

hiring a digital worker as opposed to

subscribing to software tools, AI

software tools that a human has to still

operate and piece together, you know, 10

15 different tools to do the job that

your digital worker just handles.

>> Correct. And so that so that our goal is

that instead of just being a little

orchestrator, the human cannot just

focus on like being creative director,

right? They're like, "Hey, I have this

idea. I want to go execute it and see

what happens in the market." They come

to our platform. They type something in

and boom, software races.

>> And you mentioned you you're focusing on

premium results as opposed to just, you

know, flashy AI features. Can you walk

me through some of those key

differentiators that you guys have like

when it comes to I know when it comes to

outbound you know email deliverability

is so important and you know making sure

you've got that right infrastructure in

place to make sure that that email

that's been crafted like you could come

up with the best email most personalized

email that's got all the hooks and

perfect call to action but if it doesn't

hit the person's inbox and ends up in

their spam box then it's kind of

pointless. So if you can walk me through

how 11x handles that.

>> Yeah, I mean it's it's where we spend a

bunch of time, right? It's not like a

sexy AI feature, right? But it's so

important, right? Like you said, you do

all this work but doesn't land, right?

So there's a lot of stuff we do under

the hood. Like when we buy these kind of

mailboxes and very premium mailboxes,

right? Like they're like we try to make

sure that they have very high

deliverability. We run deliverability

tests on them every single week. If they

start going sort of negative, we figure

out why. Like are we sending emails that

are not high quality? Are they not

converting? Like what's actually going

on? So it automatically triggers a deep

dive of the kind of content being sent

out. Then if you realize, hey, the

content is good, but maybe a few people

marked it as spam, we take that mailbox,

we take it out of the rotation and we

automatically add a new one, right after

it's warmed up, right? So all of this

system is automated just trying to

figure out, hey, how do we make sure

these mailboxes actually land these

emails actually land inside your primary

mailbox, right? And there's a lot of

sophistication that's kind of required

to this. think even like the server the

sending the request to Google to

actually send an email out even those

things we are kind of thinking at that

level of depth of like how do we make

sure we optimize that so you have the

best shot of getting in front of your

customers and and I think the thing that

you know we spent a ton of time on was

was automating this because in the past

people would have to do this manually

and that basically meant that you

wouldn't do it right

and so we've kind of taken that approach

across every channels right it's like

what can we do to make sure this thing

delivers and we track all of those

deliverability metrics like a

>> that's so useful. Now you guys are

leading a revolution with these digital

workers. So to make it real for our

audience keen to really dive into some

customer stories that you have and so if

you can just walk me through some of

those real life relatable stories that

you have and if you can share some

before and after wins that some of those

customers have had using 11X.

>> Totally. You know, for for many of our

customers, the status quo in the past

was using maybe like a lead database,

like hitting LinkedIn, using sales nav

or cold calling or having some generic

industry sequences that would kind of go

out. So in essence, tenn of software

large human team trying to hit pipeline

goals, right? So when we came in, so for

one of our customers, we increased kind

of SQLs by over 50%. You know, it used

to be a global team of 40 STRs, they

reduced it to 15, no impact in their

pipeline, right? they were using Alice

and the they focused their remaining

team on really higher value high

converting activities and kept

maintaining strong output with Alice

while reducing their operational

overhead.

another one of our customers in the kind

of media and events industry um

historically did not have nap on motion

for when this came on to 11x you know

for one of the first campaigns and then

we got them a 2.5% positive response

rate um on just 3,000 emails that were

sent and the first posit response came 6

days after launching the first campaign

right because we optimized even when we

send the emails out um another customer

fintech industry you know they had uh no

SCRs and it would be kind of outbound

sales motion

um like hey we want you want to try a

bunch of this cold outreach they came to

11x you know we sourced a couple

thousand leads for them 2% positive

pirate from that one campaign we ran a

re-engagement campaign for them we

sourced 300 leads right three contacts

that are kind of engaging 10% positive

pirate right and all these convert or a

large chunk of these convert into

meetings and qualified opportunities and

ultimately to to revenue and so what we

really found was that if you train the

agent well right if you give it the

right context

If you run the right types of plays, you

get a lot of success. But now you just

do it so much faster because we're doing

all the orchestration.

>> Yeah. So, so true. And if you can just

also walk us through what one of those

specific plays look like so the

listeners can kind of grasp and put

themselves in the shoes of one of your

customers and can almost visualize how

that would work for them. It could be

either your Alice or Julian product.

just walk us through what one of those

successful plays look like from you know

how let's just say outbound like what

does that look like from start to

finish?

>> Yeah. Yeah. So I think a couple

different things you know one of the

things that we think about is um one

play that works really well is someone

that visits your website right now

there's a lot of data you can capture

when someone's visiting your website.

What page are they on? How long are they

spending on those pages? You know if

someone's on your pricing page and

spends 10 minutes scrolling through

looking through everything that's pretty

high intent, right? or if they're on one

of your, you know, competitive battle

card pages, there's a lot of information

and what they're trying to do on your

website. What if they came in from a

specific ad that you've been running,

right? All of that contains kind of a

lot of context. So, we find that

customers that taken all that context

and run these website visitor plays on

our platform tend to do really well

because it's high intent, right? And

these customers haven't taken any action

on your website. They haven't signed up.

They haven't done anything, right? But

we can dean anonymize who they are when

they visit your website and enroll them

in these sequences. They're always on,

right? Anyone that visits your websites,

we deanmize and we kind of enroll them

and they're constantly getting these

outreaches, right? That are highly

personalized and highly relevant based

on the intent to display. That play

tends to work really, really well. Now,

for more cold plays, what we found work

really well has been things that don't

use the same signals that everyone else

uses, right? you raise funding, if

you're hiring for a specific role, if

you if you change roles, everyone has

access to the same signal. Everyone pays

the same vendors, right? So, you know,

when I changed my role, I got a thousand

emails in my mailbox. When we

responding, got a thousand emails. I

don't need any of them, right? And so,

those same like signals don't really

work. You have to find like what are the

creative signals for your business and

11x makes that really easy, right? So,

I'll give you an example. Play action

rand. We were finding that like hey

services businesses that have multiple

branches that have a lot of inbound

phone calls but that can't get to these

phone calls quickly enough they lose a

lot of business right so we ran this

play we're like all right hey Alice like

go help me find all these services

businesses that have multiple branches

that have a phone number on their

website and they have like Yelp reviews

or Google reviews not being responsive

right that's not you know it's not like

a signal you'll get from like a lean

database it's a very custom play right

and Alice LinkedIn did a bunch of web

research and gave us a bunch of leads.

And then the sequences that were sent

out were, "Hey, I tried visiting I tried

calling this phone number, the phone

number from their website. No one picked

up, right?" What the chat talk about how

Julian can automate this process for

you, right? And so these are kinds of

like signals that you can now create

campaigns you can now run and on our

team someone just had this idea and they

just put into our system and run it and

that become really awesome kind of play

for us. Um, and then, uh, you know,

we've been seeing on the Julian side,

what tends to happen is that someone

comes in with high intent. They fill out

a demo form, right, onto your website,

and then it takes you 3 days to get back

or 5 days to get back. In many cases,

they've gone somewhere else, filled out

some other demo form, and those guys

called them back. So, now they're, you

know, you've already lost the customer,

right? So, what we found was that how do

we capture this lead when they had the

highest intent? And so if you uh deploy

Julian, you you know come to the

website, you fill out a form, your phone

starts ringing and it's Julian calling

you back within a few seconds like, "Hey

Mark, I saw that you know you you you

express interest in our website. Mind if

I ask you a few questions about what

you're looking to accomplish here?"

>> Right.

>> Yeah. That speed to lead so important,

isn't it?

>> Speed to lead.

>> Sales managers are always talking about

speed to lead. And

>> with an AI agent that can call them at

any time of the day, it basically

eliminates the problem, doesn't it?

>> Yeah. Works 24/7, doesn't sleep on

weekends, right? Yeah.

>> Uh it's always there doing speak to

leads. So

>> a lot of inquiries come through after

hours as well. Like you know if if your

business that's that's selling on social

media, you know, if it's a diligent

worker, they're not on social media

during the workday. They're jumping on

at night seeing your ad, putting the

inquiry through. If it's having to wait

till the next morning before your sales

reps clocks on for a call, that person's

now back at work and and is unable to to

get in touch with that prospect.

>> Yeah. And you know, another another play

that works really well is like, you

know, prospects you've lost in the past.

So you close loss deals, right? We

automatically re-engage them say after a

few months, right? But like updates

about the product and ask them, hey, you

know, I know we things didn't work out

last time. Just to catch up and see how

things are going. You'll be surprised

how often that yields to re-engagements

and customers again, right? And again,

these things are always on, right? So

you don't have to keep running this

play. You don't have to like have a

reminder on your calendar. Okay, every

every month I'm going to go like find

all those leads and run this play. It

just runs always on, right? and

accessing data from your CRM highly

personalized and just keeps running.

>> So cool. And one of the cool features I

saw within your outbound agent is that

ability for that web search or that live

web search. Like I've looked at a lot of

lead database platforms in the past like

Zoom Info and the likes and they

typically have those traditional

filters. you know what what industry

size of company and

>> if you're selling enterprise SAS they

often work but in a lot of niche

industries those traditional filter

drop- down options don't really filter

it down to a correct list that ma

matches your ICP and within your product

I saw that you can actually just use

natural language and go hey I'm looking

for these type of people you can type in

specific niches like I know the company

that I work for we go after builders who

specifically have set designs and you

only really know this information if you

actually scan their website and look if

they've got set designs. And I know

within your product, you've got that

ability to to actually search and scan

their website and scrape their website

for keywords information. So then it

narrows down that that list of of

targets that it's going after.

>> Exactly. Exactly. And and that's where

we're like now you're now you're

creating alpha, you're creating like

intent where none existed in the past

because you couldn't get access to that

data. And that's kind of our thing of

like if you could remove all the

barriers now Mark if you have this idea

you can just go do it right.

>> Yeah. So cool. And now as you move

towards this vision of autonomous

outcomes how do you think about the

balance between automation and

oversight? I know this is a big deal for

a lot of enterprise clients where

reliability, security and control are

important factors. If you can just walk

me through how does 11X handle some of

these these concerns? Yeah, I mean you

know we we we have a lot of enterprise

customers, some really large enterprises

and you can imagine this is very top of

mind, right? They don't want their

brands misrepresented, right? And so for

us these guards are really really key

because if you think about AI agents,

the same thing that makes them

hallucinate is also what leads to them

being super creative, right? It's like

the same flip of the same coin, right?

And so what we do is we kind of employ a

very multi-step model to catch and

verify hallucinations. So once like you

know our our underlying models generate

content it goes through a bunch of

checks right to make sure that nothing

was said that it shouldn't have said

right and a lot of that comes down to

what information and context are you

actually giving these agents you put

garbage in you're going to get garbage

out right and so that's where we spend a

lot of time like packaging up all this

information all this research everything

we're doing on behalf of our customers

for a specific campaign making sure the

agent has exactly the information it

needs to craft like the perfect

messaging. Now, when it comes to

oversight, you need to make sure that

you have all the right security, infosc,

compliance requirements in place. You

know, it's really easy, like I said

earlier, to launch an MVP, but

enterprise grade software requires

enterprise grade controls. You know,

we're sock to type two. We're cast a

tier three certified. We do extensive

penetration testing. There's a lot of

stuff we have to do here to make

enterprise feel comfortable they can

trust us with their sensitive data. And

we have access to your CRM. The CRM is

like where all of your sales data lives.

That's sensor information, right? And so

we really have to prove to our customers

that we're, you know, being good

stewards of this data. And a lot of this

comes down to having like a really world

worldass engineering team like, you

know, built of just amongst our team. We

build like high-grade financial

software, right? Financial software has

some of the strictest regulations in the

world because we handle money, we move

money. And so taking those same

practices here, I think gives C our

customers a lot of trust that okay, like

these guys know what they're doing. They

know how to build these highly reliable

products. So, like you said, it's it's

it's it's pretty key for us to

demonstrate that to customers.

>> Now, we've talked a lot about what 11X

does. Curious to ask, and this might be

a bit more of a provocative question

that's been on my mind at X, do you eat

your own dog food? And what I mean by

that is in your own go to market

functions, is it powered by your own

digital workers?

>> Yeah, I mean, it's a great question. So,

we're we're very heavy heavy users of

our own product, right? We don't have

any SCRs or BDRs. uh at 11x, right? You

know, with with sales, we kind of grow

our outbound and inbound pipeline by

using using our own tool. So, every time

you go to our website and you talk to

Julian, Julian's trying to sell you.

They're trying to convert you into a

demo. And a lot of our bookings from

that come in through Julian talking to

you when you visit our website, right?

Anytime you visit our website, you don't

talk to Julian, you get automatically

enrolled in a sequence. It's like, "Hey,

Mark, I saw you visited Alexa. Mind if

I, you know, shoot you over a few ideas

or maybe you should get on a call and

discuss how we can help your company

grow?" Right? We we can hit you with

really highly targeted content and

messaging because we're always refining

kind of our research agents, right? We I

mentioned earlier, we're always running

these plays on top of our CRM data. So,

close loss plays or re-engagement plays.

All these things are being done on our

platform, even events, right? Like, hey,

we want to host this like dinner today

in San Francisco, right? Let's start a

campaign where we take highly targeted

leads, reach out to them, invite them to

the event, and get them to sign up,

right? there's all these kind of

campaigns that we can kind of do in one

place on our platform and you know I've

told the team internally that you know I

don't want to grow if you can't grow on

using our own platform. So if you want

to grow like build it into the product

and then we'll grow and so it makes a

limiting uh it makes it a constraining

factor which leaves us kind of grow a

lot faster because whatever ideas we

have we productize it and then we use it

internally to grow and if it works well

then we release it to our customers.

Super interesting. Now, the marketing

playbook's evolved a lot, especially

with the introduction of LLM. And so,

I'm curious to know like with 11X go to

market strategy. What are some of the

marketing plays you guys are running at

the moment that you're finding some

traction and success with?

>> Yeah. Yeah, totally. You know, I think

in the past, we're blessed to get a ton

of inbound, right? A lot of historic

customers have actually come knocking at

our door. Um, including some of the

largest enterprises in the world. And

you know for capturing that inbound

demand that like the the the kind of

demo we have with Julian trying to close

them trying to get them out of book

meeting really really helps kind of

juice that pipeline right and outbound

like I mentioned earlier you can't use

the same signals right so can't do the

same like company raises funding or

those types of things so we're always

trying to find the very specific signals

that matter for our business now it

could be you know company that's

aggressively growing and hiring SCRs

that makes sense right it could also be

like the example I gave earlier um

services businesses, right? It could

also be we're seeing a lot of traction

in

uh in companies that have a ton of

inbound. So, think, you know, uh a

company that has a lot of SMBs visiting

their website and they can't afford to

have a rep actually talk to them and

handle all of them. So, how do we

automate that? So, we're using that as a

play to reach out to these types of

companies. We do a lot of website

visitor re-engagement plays. We do a lot

of speed to lead. We do a lot of closed

loss campaigns. The biggest difference

here is that it only takes us minutes to

set these up instead of weeks, right? We

take our best customers, we run local

campaign, we run look like campaigns for

them to find other customers like them

and share those case studies, right? The

example I gave earlier of the services

businesses and it's literally just a rep

who had this idea and running further

campaigns. So kind of democratizes the

company's growth in some way. If you

have an interesting cool idea, you can

just go and test it uh on our platform.

>> And have you seen the strategy evolve

over time? you know as the market

evolves and starts adopting this

technology more and even your own

technology as that evolves have you seen

your go to market strategy evolve at

all? Yeah, I mean I think as most

startups do you we started out with

smaller companies that were looking to

grow quickly without building a large go

to market or and as I mentioned earlier

we learned we evolved from that to move

much more upm market you know and and

that required like you know we had to

come up with a lot of sophisticated

strategies to actually get in front of

our prospective buyers you know we had

to mature our own products to have the

kind of level of integration that our

large customers needed to to succeed

we've been I think the really fortunate

position that we've been in is that as

we make our product better, we grow

faster, which means we learn from more

customers. We what we learn from them,

we put back into our product, which

helps us grow faster, which means we get

more feedback from customers. And it's

like this kind of cycle kind of builds

and compounds on itself because our

product is intrinsically tied to our

growth, right? So if we don't make a

product better, we don't grow, right? I

think that kind of feedback loop is very

rare for companies only for companies

that are in the go to market space who

are kind of building these end to-end

digital workers. So yeah, we've

definitely moved a lot more up market

and use our product as a as a forcing

function for that.

>> Yeah. And the speed at which AI

technology is evolving is something I've

never seen before. And I'm sure for for

you at the helmet 11x it's probably

something that that keeps you up at

night just to keep up with that ever

evolving uh advancement in in AI

technology. I have a question just

around, you know, you guys are

pioneering a totally new category and no

doubt you've got those early adopters

and then you've got certain people who

might be, you know, late to the party.

What's been like the hardest part about

educating the market and and winning

some of those early adopters?

>> Yeah, it's been it's been interesting.

Typically, when new technology comes

out, it has a lot of its kinks and

issues. So, people kind of like, you

know, cautiously optimistic investing in

experimenting in it. The first big AI

application was chatbt. It was magical,

right? So that set the bar really really

high for what people expected these AI

agents to be able to do, right? The kind

of like videos it could generate, the

kind of images it could generate, the

kind of conversation you could have with

it, it's kind of insane, right? Train on

the entire world's knowledge. And so,

you know, what we saw was that, you

know, the first wave of agents, people

expected them to be perfect, like

perfect and better than their humans.

You know, we would we would talk to

these customers like, "Yeah, we want you

to, you know, book all these things for

us like build a kind of pipeline." Okay,

but what are you getting today? It's a

fraction of that, right? So, they

expected this like these AI agents with

this magical magical thing. And as an

industry over the last one year, I think

people have realized, you know, this is

not some magical panacea. You have to

put in the reps, you have to experiment,

you have to train the outcome. So, I

think a lot of what we do when we sort

of sell to customers is we're actually

doing kind of like a reverse interview

like are you even ready to have the

agents deployed, right? Because it's not

something you can just kind of like, you

know, have someone else manage. Like you

have to own it. It has to be a key part

of your strategy. You know, someone has

to be responsible for making you

successful because if they're not, we

won't be able to do that for you, right?

Like you have the most context, the most

knowledge and learnings about your

business, right? And you bring that to

our agents, we can help you use our

agents in the best way, right? So I

think a lot of training has been like,

hey, you need the strong ownership in

your site. This needs to be a key part

of your strategy and it's going to take

a little bit of time to make it work

perfectly, right? But if you put in that

investment, it will literally compound.

Used to be how things were done in the

past, but because the first real big

application with chat was so good,

people were like, "Oh man, this can do

anything and everything."

>> So, it's more that education, setting

those expectations, making sure you're

getting that buy in from those that are

investing in this type of technology.

>> Exactly.

>> All right. Well, let's now shift gears

for a moment cuz I saw that 11X recently

raised over $70 million from two

absolute heavyweights entries in

Hollywood and Benchmark. And for those

not familiar, these are the same venture

capital firms that back the likes of

Airbnb Facebook Figma Instagram

Pinterest, Slack, basically any well

recognized brand, they're probably

behind it. So, they know how to pick

winners and now they're backing 11x. So

if you can take us just behind the

curtain like how did you first get

connected with Andre and and and

Benchmark?

Yeah, you know, the cool thing here was

that Lebanon was the first company to

actually create a category for digital

workers for revenue teams. And this is

back in the day before, you know, GP

like 3 and 4 had just come out, right?

And so we were lucky to be quite early.

And because we were early, we kind of

catapulted that into a lot of demand.

And so a lot of this demand actually

started coming inbound into us, right?

We started having this insane growth

curve before any of these, you know,

verticalized AI companies had really

taken off, right? I think the thing that

I think convinced you know A16 to really

lead our series B which was you know our

latest round was I think twofold. One

was the quality the tenacity like the

hyperfocus of the team on how do we grow

very quickly and capture this market.

The second one was our unique vision for

the space.

Our vision was never just build Alice

and Julian and had just have these two

digital workers in the market. The

vision was to have an entire go to

market digital workforce, right? To help

automate all of the laborious work and

ultimately become a system of

orchestration and a record, right? If

we're already doing all the actions on

behalf of our customers, then it's much

easier to replace underly system of

record as well, right? Because we're

replacing all the inputs and outputs

into it. And so in that vision of like

imagine having this system where like

everything feeds to each other like our

our STR agent talks to our AE agent

talks to our RevOps agent talks to our

marketing agent. They're all learning

and feeding back insights from

everything they're seeing and the entire

system keeps getting better and better

and better. Like that's what I think was

a really compelling vision because we

didn't want to create just like the best

like phone agent or best like SDR agent

or the best marketing agent. going to

create this entire team that works

together and that was kind of the nasty

vision we had when we raised you know

>> and having gone through that capital

raising process myself through VCs with

my own startups I know that they're

notorious for deep due diligence

technical audits team reviews scenario

modeling how was that process like for

you guys

>> you know it's it's basically what you

imagine we went through sort of all of

that uh our investors did very very deep

customer diligence to talk to a huge

chunk of our customers understood, hey,

what's working, what's not working, why

are you betting on this team, how can

this team improve and shared all those

insights back to us actually as part of

due diligence, right? Which is actually

fantastic.

They asked our product road maps, why

the decisions we were making, how we

were actually going to get to our

vision, right? What are all the baby

steps you're taking now to actually make

that a reality? Um, and then how you

think about hiring attracted talent,

right? The company started in London,

moved to San Francisco and so how are

you going to attract the best talent?

How you going to hire leaders and what

evidence do you have of that? So our

company went from like series A to

series B in a matter of months, right?

So it grew very very quickly. And so

these are all the pieces we dug into to

make sure that you know this team had a

path to get towards that crazy vision.

It's interesting you just mentioned, you

know, they were asking all these

hard-hitting questions. And I find that

process of going through raising

capital, speaking to VCs. It almost

creates accountability for founders and

leaders within companies cuz typically

you keep your team accountable. But

there's normally no one that keeps you

accountable to make sure you're taking

all the right steps. you know, you've

dotted the eyes, crossed the tees, and

it sounds like you had a similar

experience where going through that VC

process, it almost makes sure you know

you've got your house in order as well.

>> Yeah, totally. Totally.

>> Yeah. And having now got backing from

you, the most well-known VC firms in the

world like what has that meant for X

from like a validation perspective?

You know, it's been it's been really

amazing to have that validation because,

you know, in in our space, there's like

hundreds and thousands of startups,

right? All trying to compete for this

really big pie. And if you're

prospective buyer, there's so much noise

in the market to like who should you use

like you do a search and you see a 100

startups, like who do you who do you bet

on, right? They're all, you know, saying

the same thing. So, how do you actually

realize what's what's true and what's

not? I think having the credibility of

some of the largest investors in the

world backing us gets us in the door at

these larger companies that are moving

up market. And once we're in the door,

we're able to do a pretty good job of

closing. So, you know, huge shout out to

A6MZ and Benchmark really helping open

these doors, right? Uh and getting us in

front of these like really large

companies so we can demonstrate

everything we're doing and kind of the

the shift in mindset that we're causing

in the space.

>> Yeah, absolutely. And I think from

someone who's gone through the process

of vetting different software for my own

companies, I know that one thing that

always goes through my mind, especially

with some of these newer tech companies,

you're always thinking, is this company

going to be around in 6 12 months? Like

if I'm going to integrate this across my

whole organization, you put my

reputation on the line to vouch for this

software like is this software company

going to be around in 6 months? And I

think, you know, having backing like

what you guys have done gives a lot of

confidence to those people looking at

choosing a software vendor. Now, you've

also personally invested in over 40

startups yourself. So, you've sat on

both sides of the table. Keen to

understand like what's the number one

mistake you see founders make when

raising capital?

>> Yeah, you know, in the earliest stages,

all that matters is the team and is a

problem worth solving in a big market,

right? Investors know that teams

frequently change ideas. So in fact some

of the largest companies we know today

started out as something completely

different right. So too often I'll see a

team focus too much on like the specific

solution to the problem or specific like

feature set compared to a comp

competitor

without really grinding the conversation

in these the two things that I mentioned

above because you know building a

product is in your control and should be

a focus but you need to answer these

bigger meta questions like what happens

if you build the best product like is

that even a problem or a product that

people will pay for will they pay a lot

of money for it how big is that market

right is it going to

support the returns you need for these

VCs to actually invest in your business.

Can you make billions of dollars in

revenue? If your vision is right and you

execute well, right? Too often people

like, oh, like, yeah, we're going to

launch this thing cuz like this other

product is not doing this one thing

well. Okay, but if you did that one

thing well, what happens? Like paint for

me a world. What does the world look

like if you exist? Right? And so that's

kind of what I always recommend to

founders like, hey, you need to focus on

these things and really sell your team,

right? your team is like who's gonna

actually do all this work. I can come

here and say, "Hey, I'm going to make a

cure for cancer, but I I don't have any

medical background, so it's out of the

work, right?" So, it's like, how are you

going to actually your team to make

something happen? So, true. And we've

seen that the investment landscape

evolve over recent times. You know, it

used to be all about scale at all costs,

huge amounts of money from Silicon

Valley getting poured into companies

that, you know, could be burning

millions, billions of dollars. What have

you seen based in Silicon? Have you seen

this be the mindset shift within VC

companies or is it now shifting more

towards trying to find companies that

are more profitable or is it still this

scale at all cost? It's still scale at

all cost I think because with uh with AI

you can build and grow a lot quicker

right so now the revenue growth that you

know metric capital is expecting to see

needs to be much much higher than it

used to be in the past right people able

to grow a lot quicker and and and

leverage and compound much faster but

smaller teams right AI is rewriting like

how things are done you can build a lot

faster you can hire a lot less you can

uh you can automate a lot of things

internally so small teams can massive

massive impact and what that means is

that you know venture capitalists are

betting on a lot more different bets

because of the transformation

technology. It feels like, you know,

1990s era all over again, right? Take a

bunch of bets. Some of them will

survive. There'll be a huge graveyard,

but the learnings that come out of this

period would be really, really

important.

>> So, you're seeing this almost like a

full reset and this whole AI era is now

basically brought it back to that, you

know, that internet boom era of new

startups popping up and this this hyper

risky environment where they're just

throwing money into these companies.

>> But I think here's the thing, right?

These companies are generating real

revenue. The difference is in the late

1990s when we got the internet era these

companies just throwing money but not

generating any revenue here like you

have these two person startups

generating tons of revenue right so

there's something real there right

people will pay for the value they're

getting which makes it really exciting

time like like never before

>> now let's look ahead a little you know

if digital workers evolve the way you

envision keen to hear from yourself

which DTM role do you see changing first

is it the SDR is it the AE is customer

success or is it something else? You

>> know, frankly, I think all of these

roles are going to evolve massively and

they already are, right? We feel that,

you know, as a company, we feel that the

SCRs a lot of the efforts will kind of

be shifted towards higher, more creative

campaign creation rather than focusing

on things that we automate such as

account research or cold emailing,

right? In fact, we expect that most STRs

will become like either junior account

executives or junior growth team members

or junior marketers right off the bat.

and companies will invest a lot more in

training them early on rather than

having them first kind of BSDRs. I think

you'll see the same thing in sales. The

number of AI tools that exist today to

help reps get better faster. You'll see

the rise of like these superellers that

become a supereller very very very

quickly. Given all the tools that are

helping, you no longer need to have, you

know, each rep be the best uh I don't

know at giving a demo. You have they'll

have a sub agent that can go and jump

into a call and give a demo, right?

It'll be the best at giving a demo. Now

they can go in and like work on the

strategic deals, build the relationships

while the heavy sub agents help them

with their work.

Customer success I think will become

full stack. What we started seeing was

that the customer success role was

getting like parcelled out. So you'd

have people that help you like onboard,

implement, support, then like do

renewals and expansions and it's really

kind of becoming like this giant

conglomerate. Whereas I think now it'll

be compressed and become much more full

stack. The CSMs, you know, can do

everything. They'll be able to do

onboarding support renewals PC

conversions because not all these

different pieces of data are flowing

together and they have a lot of agents

helping them various pieces, right? And

that's how we operate our internal CS

team today. Like we don't have four

different compartmentized roles. It's

the full stack CSM. That's what we call

it internally.

>> So you don't see it as these AI agents

are going to completely take over all

human jobs. Do you see it more as like a

co-worker relationship where humans will

be elevated to be able to work on, you

know, more meaningful work within the

organization and kind of consolidating

rather than having these specialized

roles per se for these different

functions being able to limit the number

of stakeholders that the customer has to

deal with.

>> Yeah. I mean, I think I think we've

typically seen that with kind of every

technology shift that's happened in the

past, right? Like it doesn't like it may

like kill certain jobs or make certain

things redundant, but it creates so many

more

Right? Because now what's possible, what

you can actually do is just so much more

massive. And so that's kind of what I

expect. I expect like everyone, every

single IC or individual contributor in

the world out there to basically become

like a like a manager, like a director

of these agents to get work done, right?

And as these agents keep getting better

and better, they keep directing higher

and higher level things, right? So today

it might be like do the small workflow.

Tomorrow it might be like all right,

let's figure out how to like make a ton

of revenue. And later on might be like,

hey, let's figure out how to run this

company, right? will keep getting better

and better as these underlying models

get better and better. Now, if we get to

AGI, like all bets are off like I don't

know what's going to happen, but that's

my current view.

>> Yeah. Well, on that same train of

thought, like let's just fast forward 3

to 5 years from now, AR agents are now

part of the normal org chart. All the

companies are adopting it. Like what do

you see our go to market teams actually

looking like at that point?

>> I think you'll have uh you'll have these

generalists. you'll have these really

smart generalists that are looking

across like entire end to end things. So

instead of just being like, "Hey, I just

do like paid ads, right? Or or I just do

like these marketing things or I just do

like this STR stuff." Now they can look

across entire pipeline and be like, "All

right, like I need to like get more

revenue. Here's all the tools and sub

aents at my disposal. How can I make

that happen?" Right? And so I think I

think each person will now just have so

much more leverage. It's like every

person can kind of be the mini CEO,

right? and make things happen because

now they have all these little agents

that can help them with various pieces

that work well work well together and so

you know why do they do these things

manually when there's a lot of pieces

you can just just automate and so

>> I think people will be able to like kind

of get elevated and think through the

entire end to end of whatever business

workflow or process or objective they're

trying to solve for and those things

will just keep getting bigger and bigger

and bigger and so I'm I'm really excited

about what what teams and companies look

like in a couple years. Yeah, it's going

to be so interesting because it's almost

going full circle, isn't it? Like before

the industrial revolution, you know, you

had these generalist artisans that were

jack of all trades and then and then the

introduction of the machine worker, you

know, everyone started becoming

specialized roles with middle management

overlaid on that. And from what you're

saying, it sounds like it's almost going

full circle where generalists will start

rising up again, but the difference this

time is they've got a team of these AI

agents or digital workers that they can

empower.

>> Yeah. And they'll just have much more

visibility, right? So instead of just

focus on one slice to look at the entire

business problem, be like, "All right, I

can solve this problem."

>> So interesting. Now, finally, what's on

the horizon for 11X? if you can share

some of the exciting new features, new

markets, or maybe even new categories of

digital workers that you're planning on

launching soon.

>> You know, the one of the things that we

we really invest in at 11x is building a

world-class team. And so our team ships

that kind of break that speed and we're

always thinking about, you know, what's

next, where's the future, what what do

we need to build to get to the future.

And so, you know, we already have uh

this our chatbot coming out of beta. You

know, we'll hook very nicely to to

Julian to our voice product um as well

as our email agents. You know, we're

working on syncing your entire CRM kind

of our system. So, agents can get these

really unique insights about all that

rich data that's kind of inside your

CRM. all your past interaction with a

prospect or customer be able to sort of

construct an entire engagement history

of every interaction you have with a

prospect and use that when you're

reaching out to them again. Right? We're

working on these autonomous agents that

like really help you with your ICPS and

create your entire campaigns kind of end

to end and like net new digital workers

to help sales teams close deals or

revops optimize the revenue engine and a

whole lot more. So very very excited

about what's coming up in the next

couple months. It sounds exciting. And

so it sounds like you guys are really

doubling down on that, you know, the

more the revenue side of businesses. Is

that correct?

>> Yeah.

>> Correct.

>> Yeah. Fantastic. All right. Last

question, and this is how we wrap up

every episode. If you can add one new

page to the GTM playbook, whether it's a

tactic, a mindset, or or a principle you

now swear by, what would it be and why?

>> The thing I'm going to pick is the is

the principle. And this might sound a

little cliche, but experimentation is a

muscle. It's a true competitive

advantage today, right? You need to be

patient to train these systems, these AI

agents to actually start seeing the

compounding benefits, right? You don't

hire an STR, expect them to be the best

from day one, right? And once you make

that investment, now you kind of have

this always on digital worker that works

for you 24/7. You want to go after a new

market, you want to launch a new

product, just create the marketing

material and boom, upload it and it's

good to go, right? But that initial uh

learning, the initial experimentation

needs to happen. Not everything you do

will work from day one. In fact, a lot

of it won't, right? But you get those

reps in now, uh it's going to be much

better than getting those reps in six

months from now when all your

competitors are already doing it and

you're already behind the curve, right?

If you look at every technology shift

that's happened in the past, it's always

been people who like jump on it early,

learn how to harness the power are the

ones that end up surviving, right? So

all the customers I talk to, I'm like,

"Hey, like treat this like an

existential threat to your business and

learn, experiment, and see what's

working. Don't just give up after a week

because these systems need time to bake

and learn and help your business grow

effectively."

>> Prahav, this has been a super

interesting conversation. and I could

probably talk to you for hours, but

we're going to have to wrap it up there.

Now, if people want to learn more about

X or even connect with yourself, how how

should they go about that?

>> You can find me uh on LinkedIn or or

email me at dj1x.ai.

>> Fantastic. Well, thank you so much,

Bahala, for jumping on the the podcast

today and look forward to to catching up

next time.

>> Perfect. Thank you for having me, Mark.

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