September 17, 2024 • 43 mins
James Mackey, CEO of a leading RPO provider, SecureVision, and Elijah Elkins, CEO of Avoda, a highly rated global recruiting firm, co-host hollyhires.ai CEO, Jacob Claerhout in our special series on AI for Hiring.
Jacob shares how his company is transforming recruitment with AI. Since its launch, Hollyhires has focused on automating candidate vetting, managing databases, and running personalized campaigns for staffing companies. He explains how AI boosts recruitment efficiency and quality, aiming to create a more balanced, value-driven process for both employers and candidates.
0:00 Jacob's journey and Hollyhires' origin
10:48 AI Technology in staffing industry
23:59 Future of AI in career management
33:58 Future of AI in talent matching
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Our host James Mackey
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hello, welcome to the Breakthrough Hiring Show.
I'm your host, james Mackey.
Thanks for joining us today.
I am joined by Elijah Elkins,our co-host.
Elijah, what's going on?
Doing well, doing well, good.
And we're also joined today byJacob Klerhout.
Jacob is the founder and CEO ofHolly Hires.
Jacob, it's great to meet youand thanks for joining us today.
Speaker 2 (00:20):
No, thanks a lot for having me.
It Thanks a lot for having me.
It's a pleasure being here.
Speaker 1 (00:22):
Yeah, it's going to be a great episode, I guess,
just to kick us off, are youbased out of London or where are
you based right now?
Speaker 2 (00:27):
Yeah, so I'm, let's say, a Belgian, spent some time
living in Paris, currently livein London and actually spend a
lot of time in San Francisco,because that's where things are
happening when it comes to AI.
Speaker 1 (00:43):
Everything try and spend as much time as possible
on American soil.
Okay, cool, nice.
Yeah, we're looking forward tolearning more about Holly Hires.
I saw that you started thecompany and it looks like around
December 2022.
So I would love to, just likeElijah, and I just want to learn
about what it is that got youto start the company and primary
value proposition of whatyou're building.
Just an overview to get usstarted would be great.
Speaker 2 (01:05):
No, happy to Myself.
I used to be an intercapitalistinvesting in early stage
businesses, which is an absoluteprivilege to have as a job.
Before that, actually, togetherwith friends already, you used
to run a small recruitmentagency placing investment
professionals, which was a blast.
I learned a lot and also theregot the knack for the talents,
or the match between talent andopportunity.
(01:26):
While being a vc invested in acouple of really exciting hr
tech businesses that turned intounicorns, which was a real
privilege to to work withamazing founders this closely.
But for me the mission allalong was to go out and build a
business of my own and at somepoint after a couple years you
have to either, let's say, putyour money where your mouth is,
leave the cushy and goldenhandcuffs there and go and do it
(01:48):
, or you commit to theprofession of a venture
capitalist, because the time tofeedback cycles are infinitely
long, so you need to reallycommit to that.
I took a leap of faith there.
Together with my co-founder,who's a fellow Belgian, we first
got started building a talentmarketplace where on one side we
had freelance recruiters and onthe other side companies
looking to hire.
What we did was obviouslymomentum building on both sides,
(02:12):
and then quality control in themiddle.
Initially that was going well.
We managed to get a couple ofthousands of recruiters on board
.
We had a specific niche wherewe had worked for some of the
largest brands in the world,managed to make that profitable.
But after a while we came to theconclusion that, okay, quality
control needed, say, technicalsolutions.
We couldn't just keep on addingpeople to that equation.
(02:33):
And that's when we startedplaying with the back then
technology that was at itsinfancy, the GPTs of this world,
this world.
And it is at that point that werealized that this technology
would not only disrupt our ownbusiness but actually going to
reshape a large part of thevalue chain in the industry at
large.
And with that in mind, we said,okay, let's be the change we
(02:54):
anticipate, going for thisindustry and start building what
we think the future ofrecruitment looks like.
And that's how we got startedwith Holly Hires.
Speaker 1 (03:02):
Nice.
Okay, that's really cool, andusually I don't know I end up I
feel like monopolizing the firstseveral questions, so this time
I'm going to take the backseat.
Elijah, if you want to kick usoff some questions, that'd be
great.
Speaker 3 (03:11):
Sure, yeah, I would love to understand a little
better, jacob, what exactlyHolly Hire does, right In a
detailed way, and the threedifferent areas that it shows on
your website, right Like thedatabase and the outbound and
then the inbound.
Speaker 2 (03:27):
Yeah, totally.
So zooming out slightly fromthat is I believe that AI is
going to change the way we hirepeople, and not only on the
company side, but actually alsoon the candidate side.
And like listening to thepodcast, for instance, like I
feel there's a lot of focus thatgoes into the company side
because that's where talentprofessionals sit, but there's
real implications to having AIagents on the candidate side as
(03:50):
well and we actually play withthat.
If talent acquisition likematching talent and opportunity
changes to an agent, to agentworld, then all of a sudden both
companies and candidates haveAI agents optimizing for them.
Companies and candidates haveAI agents optimizing for them.
Basically, you have one of thetransaction function, the career
(04:12):
agents of a candidate thathelps you think through okay,
where do I want to be?
Like, let's filter theopportunities that I get spammed
with, but also make sure thatI'm always aware as to what the
most exciting opportunities forme could look like.
And on the flip side of that onthe company side you have an AI
recruiter.
The flip side of that, on thecompany side, you have an ai
recruiter.
And what an ai recruiter shoulddo is make sure that you
attract and the most exciting ofall individuals, just like you
would expect that from like yourbest recruitment efforts, right
(04:35):
so, and that's actually wherefirst we got started with an ai
agent called holly.
Holly is an ai recruiterspecifically built for staffing
and recruitment companies andwhat she does, indeed, is built
automatically, build a top-upfunnel for your, for your
company.
What happens as soon as aposition goes live in your ats
whether that's yeah, bullhorn ora job diva, like a position
(04:55):
goes live, ollie picks it up anddoes one of three things, as
you alluded to.
The first thing is inboundvetting.
As we all know, like everybodyis getting spammed, a lot of
platforms have one-click applybuttons, which means that the
inbounds you get signalovernoses is deteriorating
rapidly and staffing andrecruitment companies expect
(05:16):
solutions to help solve that andthat wholly helps mitigate.
I'll get into the how in asecond.
The second part is a lot ofcompanies, and especially those
large recruitment and staffingcompanies that we serve.
They sit on a lot of data.
Everybody always tells you datais the new oil, data is the new
gold.
Everybody invests in havingdata, but when it comes to
(05:37):
actually using that data, thenit's surprising how little If
you look at the placements thatrecruitment or staffing
companies make yeah, less than5% tend to come from internal
database searches, which isinsane because these are people
that you have consent to reachout to, that know your company
and your brand.
So what we do there is webasically let Holly search
through that data in a novel way, leveraging the latest
(06:01):
technology, and, by extension,she can also do that for the
outside world.
We have, let's say, a verylarge database of 750 million
profiles.
What Holly will do is, as soonas that position goes live,
she'll start working on thatposition.
She'll email the recruiter incharge saying, hey, I found 100
candidates.
If you're okay with that, I'llreach out to them automatically
(06:22):
In a hyper-personalized way.
She would drop connectionrequests, emails, linkedin
messages, emails all of thatwithout having to basically do
much.
And there it depends on, let'ssay, the setup and the
agreements we have withmanagement.
But either it happens bydefault, really trying to make
the process as seamless and evennot requiring any real
(06:43):
interaction, or recruitersindividually come and sign off
on certain campaigns for people.
Speaker 3 (06:51):
Nice.
So it sounds very comprehensivebeing able to handle all three
of those, because a lot of AIsolutions try to only do one of
those.
Is there any, I don't know?
Do you feel like the approachto all three has made it where
you can better serve customers,or do you feel like you do
(07:11):
struggle with any certain usecases?
Yeah, I'm just curious.
Speaker 2 (07:16):
That's an interesting question.
When buying solutions,especially like for our ideal
customer profiles, which are,like, let's say, mid-size
staffing companies, the level ofstakeholder management already
required with implementing onetool is insane.
What we're pushing for is,basically, you want to remove as
(07:37):
much friction from the processas possible, and that also means
buying five vendors to helpsolve one workflow, and that
also means, like buying fivevendors to help solve one
workflow.
Right, if you take the workflowof getting like interviews with
great candidates on that top offunnel, yeah, our clients were
pretty clear that, look, I don'twant to buy someone else in
doing this.
Please help me, please buildthis for us.
(07:58):
So we do a lot of, let's say,product development with our
customers and yeah, especially,we got started on the outbound
side of things, that's, let'ssay, where our bread and butter
first was.
Our strongest customers becamestaffing companies, and then
they said, hey, this analysisthat Holly does when presenting
candidates, could we also dothat for our inbound?
And then we said, hey, yeah, wehave all the flows already.
(08:18):
It's basically just pluggingthem in a separate entity and
with that we can serve thosedifferent streams.
Also, I know that some of thesestreams are not necessarily
built for longevity.
For instance, I would expectATS vendors to pick up and to
start doing a better job withsearch in their own database.
(08:39):
They have a very strongincentive on doing that, but at
the same time, the incentive hasbeen there for the last 10, 20
years as well.
And that hasn't changed thatmuch.
Yeah, I know, like we let's say, it's not easy to handle those
multiple use cases, but it doesget really appreciated by our
customers.
Speaker 3 (08:59):
Nice and have you?
I'm curious because that usecase for staffing and
recruitment companies right.
They do tend to probably havelarger databases than a lot of
just normal kind of corporatebusinesses, but it seems like
the solution would be relevantfor corporate recruiting as well
.
Is that something you guys areexploring or you just feel like
(09:20):
it's really better to focus onthe staffing industry right now?
Speaker 2 (09:24):
We do work for a couple of end customers.
It's just, if you think about,let's say, the go-to-market
motion as an early stage startup, it just makes more sense for
us or that's something we'velearned to focus on.
Businesses where hiring istheir bread and butter, where,
let's say, technology is, yeah,I wouldn't say sometimes
underserved, but if you look atlike how old school some of the
(09:46):
software, like the core ATSsystems, is, yeah, there's just
a very large opportunity andalso I would argue that there's
a larger willingness toexperiment with new technology
there.
If a lot of people are talkingabout like a downward pressure,
needing to do more with less,and if you're like recruitment
or staffing business, yourbusiness is very person, like
people intensive, needing to domore with less.
(10:07):
And if you're a recruitment orstaffing business, your business
is very people-intensive andeverybody who owns or runs a
staffing company knows thatthere's a lot of labor that goes
into building talent funnelsback and forth with those
customers and business ownersjust identify that AI can have
an almost transformative impacton that.
So that's where we got started,or that's where we decided to
focus, not because we can'tserve end customers, but, yeah,
(10:28):
the level of pragmatism and theurgency is just larger.
And also, speaking like from alot almost vision perspective,
they know hiring really well andso that means that if you can
learn from them that it becomesalmost easier to then go back
and do it for in-house teamsafter that.
Speaker 3 (10:46):
Yeah, that's really interesting.
Thanks for sharing that.
Speaker 1 (10:54):
It's also like a consistency thing in my opinion,
right, like in any marketenvironment, staffing agencies
are going to be hiring, sothere's always going to be that
amount, like a certain amount ofdemand, but of course, like
that also is true of like uppermid-market enterprise customers
as well, there's always going tobe hiring happening.
But, yeah, I could see thatmakes a lot of intuitive sense
to me in terms of there's abigger push for productivity
(11:18):
gains and organization andsearch for databases for
candidates and whatnot through astaffing agency, just because
of how difficult it is from amargin perspective to run a
services company where youroverhead expense for databases
for candidates and whatnotthrough a staffing agency, just
because of how difficult it isfrom a margin perspective to run
a services company where youroverhead expense when it comes
to payroll is just massive rightTo have recruiters on payroll.
And then, particularly for thesestaff augmentation firms or
contingent agencies, which havethese contingent revenue models
(11:42):
that are difficult to predictout as well, just having a
solution where we almost like,regardless of the annual
contract value, it's probablythe efficiency gains are going
to outweigh what it couldpotentially take for to have
several junior recruiters doingthese database searches and
probably a lot more effectiveand then better.
Like it trickles down to likefaster placements, lower time to
(12:05):
fill, just probably likestarting top of funnel but looks
better on a pnl and then soit's more sustainable business.
But then it's also likesnowballs right down funnel into
revenue and growth.
Speaker 3 (12:18):
I would assume potentially so isn't that
similar to what when weinterviewed qual a few weeks ago
?
On the podcast they're runningsimilar motion like going after
staffing and recruiting.
I don't know, jacob, if you'veheard of Qual yet, but they do
more of the like a screening,yeah, like a voice agent, so
that's interesting too, offurther down funnel.
(12:39):
But they're doing recruitingand staffing, yeah.
Speaker 1 (12:41):
I think it's like a similar kind of motion where
it's like it's a different,completely different product.
But what I mean by that is Isee the appeal to go with having
a like a staffing, staffingcustomers particularly early
stage because, like, the demandis going to be there and is
essentially as long as they'regoing to be in business, they're
going to need your productright it's actually a good
product.
Speaker 3 (13:01):
They're going to stick with it.
Speaker 1 (13:02):
It's actually a good product, they're gonna stick
with it, it's like they need youconsistently.
It's not like these techcompanies where it's like 2021
they're hiring like crazy andthen they just cut off, like
their entire north america staff.
Speaker 2 (13:15):
No, totally and I see that actually in the
exploratory calls where, likeyou, you have those enterprises
and then they're like oh, we'reexploring tools for like next
year, and then like all that isgreat, I'm happy to be on a call
with with them and learn fromthem and see how they think.
But, yeah, I, I would preferworking with customers that need
our solution yesterday andthere, yeah, with staffing
companies.
(13:35):
The case is very obvious.
They want to move faster, notsaying that the sales cycles are
infinitely short.
Either it still requires, let'ssay, a good amount of
stakeholder management andmultiple meetings, but it is
interesting to see how staffingis catching cycles are
infinitely short.
Either it still requires, let'ssay, a good amount of
stakeholder management andmultiple meetings, but it is
interesting to see how stuff iscatching up and also knowing
that, um, yeah, that market,especially as it got like the
economy, starts lookingdifferently, or the outlook is
(13:58):
slightly more, let's say,pessimistic.
Like people need to compete, uh,even harsher.
It's like it's all about speeds.
Like you need to compete evenharsher, it's all about speeds.
You need to deliver really goodquality service at breakneck
speed, which, yeah, obviously,if you're marvelously set up
with amazing teams, then great.
But yeah, it's pretty obviousthat technology can do a
(14:19):
significantly better job.
Holly, there, in building leadlists, in reaching out to people
.
Like Holly does that in fiveminutes.
She does the work that arecruiter would need two days
for.
And that's also the type ofreporting that we do towards
those like the staffing ownersor managers, like heads of
delivery, where we say, look,this week Holly worked the
equivalent of seven full-timeequivalents for your team and
(14:41):
that, yeah, that doesn't.
Or in the beginning that mightfeel a bit scary, but at the
same time it's helping everybodyin those teams reach and crush
the targets and goals, and thatfor, let's say, a fraction of
the cost of hiring extraemployees to do it.
Yeah, I feel like the trade-offof hiring additional recruiters
to do better delivery andhigher speed versus investing in
technology is a very obviousone.
Speaker 1 (15:03):
So it's just to get a sense of the full workflow
because we covered a lot ofground pretty quickly.
So it's like creating, likepulling candidates from the ATS
to create like essentiallyshortlist for roles or whatever
else.
It's also then doing like thecustomized messaging and doing
the emails and then, from ascheduling standpoint, is it
also essentially schedulingscreens or how does that?
Speaker 2 (15:27):
For now we end when that first, whatever the first
step of the process looks likewhether that finding in your own
database and engaging withpeople, or doing outbound and
(15:54):
having multi-touchpoint dripcampaigns, through which then
Holly can also come back andanswer let's say, the follow-up
questions, gather resumes, thosetypes of things she does for
you and you do that byconnecting your LinkedIn account
and emails and all of a sudden,yeah, you have a meeting booked
with a great candidate, whichfeels pretty magical.
In the beginning it's a bitscary, but once you explain to
(16:20):
people how to manage therequirements and how to manage
the process, then they tend tobe very enthusiastic.
We see people now with highexpectations and that increase
the mandates that Holly gets ona weekly basis.
Speaker 1 (16:35):
So can you tell us like so in terms of your
products, like stack rankingcandidates, right?
So it's like when it'scompiling what's like, how is it
going about stack ranking andevaluating profiles for
relevancy?
Speaker 2 (16:47):
Yeah, so, what we do there is basically, we pull in
the candidates and then we makea list based on the job
description, we make a list ofrequirements.
So one of the things that wewanted to start implementing
relatively early on was, likemore declarative hiring.
You don't want to think insearch terms, but you want to
think in requirements, and whatwe always do is you bring in a
(17:08):
profile for a specific position.
That position has a shortdescription and a list of
requirements Must have two tofive years of experience, must
have a degree in computerscience, must have worked on
consumer-facing products.
Those are things that thosefirst two might be easy to boil
down into a Boolean, but thelast one is not and that
(17:30):
requires a level ofunderstanding.
So what we do is, for every like, holly will construct an entire
tree of options with likesearch parameters that shall all
run in parallel.
You can think of that as likethe equivalent of a couple hours
, if not days, of search workjust by filling in Booleans, and
she will vet the results.
(17:50):
So stack, rank the results thatcome up, all of that again in
parallel, against those criteria, saying okay, who here meets
the criteria?
And there we have some sort of,let's say, reinforcement
learning algorithm, where Hollybasically weighs the going
deeper down the tree that isworking for her versus exploring
new branches, and there whatyou end up with is a list of
(18:11):
candidates where you see yes,meets criteria one to five, yes
inferred.
Where she's, for instance, theconsumer arguments If somebody
works for Revolut and they workon the mobile team, then you
know that they've built productsthat have consumer facing.
That is not something that youcan boil down in a boolean, but
Holly understands that and willmake the case for that.
(18:32):
It will be question marks likeI can't possibly know this or
does not meet this, and then,based on how many of the
requirements are met, she willdecide whether or not somebody
should be pursued or not.
Speaker 1 (18:48):
So is this primarily on the resume or also just like
within the ATS?
If people have answeredscreening questions in the past
scorecards, things of thatnature is it pulling in data
from there as well?
Speaker 2 (18:59):
Yeah, we pull.
So for the internal search part, we pull data into our own
system and then we pull as muchas possible.
If people have prior relevantinformation, then great.
It's often, though, very messyand it's almost more worth.
It's just not worth the effort,because standardizing that
across different roles anddifferent systems.
(19:21):
Often people have switchedsystems, switched methodology,
so it's not always worth theeffort, but Holly can use any
information that is presentthere.
The most valuable source theretends to be the resume and the
notes that people have left oncandidates.
Speaker 1 (19:38):
Okay, Got it.
So notes too, All right, but myother question would just be
like for your staffing customers, what types of roles or
specializations do theytypically have?
Paul was saying the CEO ofDavid Tell was telling us that
he was seeing a lot of demandwithin light industrial staffing
agencies.
For light industrial, he justsaid, just due to a ton of
(19:58):
volume of openings that theyhave in the United States right
now.
Are you seeing differentspecializations really stand out
in terms of where you're seeingthe most demand?
Speaker 2 (20:07):
Yeah, absolutely, and that makes a ton of sense.
Also, if you think about thelike, which parts of the flow do
you automate?
First, that as a staffingbusiness is a question you need
to ask right, okay, where arethere obvious opportunities?
What are the most easiest?
Which ones affect my customersand my candidates?
And they are obviouslyintroducing voice agents
fascinating, but that that doeschange the experience.
(20:27):
For for your candidates inlight industrial, yes, there's a
lot of opportunity.
However, what are bread andbutter tends to be the highly
skilled, actually, like thereally white, like white collar
staffing companies, because forthem it's like the
identification matters, likeit's the difference.
That's also why they tend to bemore expensive.
(20:48):
Right, it's.
Not only is the salary of theperson significantly higher,
which makes it like they aremore demanding, they're harder
to find, harder to close.
So that's where we play.
We tend to do softwareengineering, anything that is
healthcare or pharmaceuticals,like the jobs that tend to have
advanced degrees, are the onesthat the staff and companies
that we focus on, mainly becausethere Holly's intelligence
(21:10):
matters, like she understandsthe difference between a C++
developer and a React developer,and it's that level of
understanding that yourcustomers expect from you or
demand from you.
So we yeah, that's the realmwhere we play and that's also
where Holly can make the biggestdifference, because judging,
yeah, if the quality is okay,you need to be able bodies and
(21:31):
be able to come and work thisshift.
That is obviously alsoimportant that you can still
validate, and there's a lot ofan entire, let's say, focus of
the market that needs to do that, but that's not where holly's
strengths lie yeah, that's.
Speaker 1 (21:43):
That makes a lot of sense too.
It's like where more nuance isneeded, like exactly okay, cool.
So what about futurefunctionality when you're
looking like in terms ofcustomer feedback right now, and
then just your own knowledgeand insights into what you've
seen on the market and what youthink functionality and features
are going to make the mostsense over the next six months
(22:05):
to a year?
Do you have a?
What are your top priorities interms of additional
functionality for your product?
Speaker 2 (22:11):
Yeah, the first thing there is the HR tech space, and
then, especially, like the coreinfrastructure.
It's such a like, such afragmented space that it's
insane the amount of coverageyou need to have if you want to
integrate just the five largestor the 10 largest, and every
time you meet the new excitingcustomer, they're on a system
that you don't get support.
So there's a lot of likegrounds that needs to be covered
(22:37):
there.
And then, additionally, likethe details matter when building
systems like this.
So you, you want to build inenough and I can refine enough.
Okay, the tweaks and like ofthe of the core of your flow.
It's sometimes like smallthings that like the way you
communicate towards therecruiter or create a buy-in
front that wholly creates buy-infor certain candidates, for
instance, like it matters.
(22:57):
We're now, for instance, workingon resume formatting.
Like a lot of customersmentioned that they spend like
hours on trying to formatresumes.
When we looked at that as acompany, we're like what, how is
this?
How are people like?
How can this be a job?
But, yeah, apparently, largetraffic companies have full-time
like people in like often noton the payroll, but very often
(23:19):
freelancers that do nothing butthat.
So there's a lot of.
As we further pull like on somethreads, we learn a lot of
additional functionalities whereholly could have a very big
impact.
But in in terms of the longerterm vision, I believe in that
agent-to-agent vision where notonly will we automate the hell
out of things on the companyside of things and primarily for
(23:40):
staffing companies, but if Ithink, okay, three to five years
, what excites me it's trying tomatch that with a consumer
angle.
If you think through, okay, the, the inefficiency of trying to
like, blast messages towards,like the whole world, everybody
who's high and blasting towardsthe whole world, and then on the
receiving end, like not evenseeing or hearing things anymore
(24:02):
, even great opportunity likeGoMist, because of the fact that
it's so hard to filter thatsignal from noise.
I'm really excited about beingable to match those two and I
think the new paradigm that isGen AI allows you to work with
unstructured data and interactwith software in novel ways, and
those are two things that withHolly we take, let's say, really
(24:25):
too hard.
But applying that on the flipside, on the, the candidate side
, is going to allow us to createfor our customers a channel
through which candidates can belike, reached and really reached
, but only if it makes sense.
Because that's the beauty ifyou can find a real match, then
you earn your spots to get theirattention.
And I feel like a lot of the oldschool companies, old school,
(24:47):
okay, everybody pays their taxto linkedin, right, but like
linkedin, you pay per email.
You don't pay per conversion,right, where you feel that
there's like an almost like awrong alignment of incentives.
So I'm really excited abouttrying to, let's say, correct
that wrong, but it's going totake more than a couple quarters
so what?
Speaker 1 (25:07):
I'm curious what do you guys think in terms of how
candidates are going to beleveraging AI?
What product functionality arethey really going to be using?
I guess there's optimization ofjob descriptions, I don't know.
I guess leveraging AI to maybefind jobs or apply to jobs.
Honestly, on the candidate side, I haven't given it as much
thought.
So I'm just like Jacob.
(25:28):
You're talking agent to agentexperience.
What do you think is going tobe like?
What are?
How are candidates going to beleveraging job seekers, going to
be leveraging ai over the nextfew years?
How's that going to change?
Speaker 2 (25:39):
I.
My bet there is that, likepeople will have an experience
similar to the ones thatsuperstars, like movie stars and
sports people have.
Like they have an agent.
Like they agent, they don'thave to think about their career
the whole time because somebodyelse is doing it for them, and
that is something reallypowerful.
With the democratization ofintelligence, we'll see more
(26:00):
people having access to what Iwould call a career agent, and
the idea there should be that acareer agent finds tempting
opportunities for you even whenyou're not actively looking.
That is how I think about it.
It should be quality overquantity and always on, so that
your agent always has your back,and that concretely will
translate in my head tosomething where you just like
(26:23):
you, working with the best humanrecruiter.
I think the process will lookvery close to what that is like.
You'll have a relationship withyour agent, which means that
agent needs to be close to you.
My bet would be that it willlive either in a messenger trend
like iMessage or WhatsApp,where you can interact through
text but, most importantly,through voice, and there I think
(26:46):
, like the other company that wewere discussing is on an
interesting trend that we've runsimilar experiments there,
where, if you can get to know acandidate not only their resume,
but actually also what they'reabout and what they might be
looking for, because a lot ofthings such a significant part
of, like job matching happensthrough things that are not
present on your LinkedIn.
Right, is it okay?
I want to move closer to my mom, I just had a second child, I
(27:08):
need better insurance or I needa higher pay and I'm willing to
work harder, or no, I'm towardsthe end of my career and I want
to start, let's say, taking moretime with my family.
So these types of things youdon't put on LinkedIn, but you
can tell your AI career agents,and what will happen in my mind,
is the two agents the one thatknows the company really well
will have an incentive to tryand get in touch, and it will
(27:30):
almost become like a protocolwhere, okay, you share an
opportunity, you, a company,shares one, a career agent
responds saying, hey, no, I'mnot open at all because you
don't meet any of the criteriathat my clients being like okay,
my boss has set for me or whatI understood from how we've
communicated prior, and it'sbasically that gliding scale
(27:52):
where, if you feel anopportunity, that does mean a
lot of it, that you will expectyour agent to run it by you and
say, hey, you know what, likeJacob, even though you're like a
great founder, but OpenAI isworking on a like a career agent
thing.
Would you want to chat?
Even though I'm definitely notleaving my startup, I would want
to know that.
So that's so.
That's the type of thing thatyou would expect your agent to
(28:13):
do, and it's that trust and thatproximity that will enable a
whole new way of matching andI'm very excited about that.
That would be my bet as to whatthe career side of things or
the candidates side of thisworld will look like.
Speaker 1 (28:26):
Yeah, that's going to be really cool.
That's a pretty compellingfuture.
Just essentially, that's goingto be really cool.
That's a pretty compellingfuture.
(28:46):
And to the extent, too, whereit's not just punching in
requirements but to the extentwhere it can be a guide as well,
would be pretty't necessarilysure, unless a candidate just
starts asking for advice and youhave you decide to take 10
extra minutes to try to, youknow, help somebody out and
you're like, okay, here we go.
It's like getting into thenuances of okay, maybe you can
get this jump in comp right now,but if you take this path, then
(29:08):
you're ultimately going tostall out two years from now and
it's going to be hard for youto have continued growth five,
10 years in the future.
Or thinking, yeah, basicallythose like decision mapping
where it's like all right, ifyou take this step short term
here, it helps you do this.
Long term, it's going to makethings challenging.
Where you take this other step,You're going to stay at a
similar conference for longer,but the experience you're going
to gather is going to be morerobust or helping you understand
(29:29):
like gaps in your skill set orexperience that could prevent
you from getting jobs and alignyou with roles that like can set
you up for future success.
This is stuff that like, quitehonestly, like top tier talent
in most industries.
Like this is the kind of waythey're thinking, but it's not
necessarily as intuitive as wemight think.
It is A lot of people, I feel,like their careers they're just
(29:51):
going with the flow.
They push out their resume to abunch of companies and whoever
responds like where there's theleast amount of friction is like
where they end up working andthere's a to be clear, there's a
fair percentage of folks in theworld maybe even the majority
of like people that they justdon't have options.
They have to do what they haveto do.
But when we're talking aboutlike your customers, where it's
like the white collar workers,it's people are fortunate enough
to be in this position wherethey could be more intentional
(30:13):
about their career and there'sjust a lack of intention.
It's like you look at the numberone hated interview question
and it's like what's your threeyear plan, five year plan?
It's people hate that question.
It's like why have you notthought about that?
I think it's I honestly peoplewho don't like that question.
I don't want to hire them, butI think it's just interesting
(30:34):
right, like helping you bringstructure to what's your
long-term goals.
Your long-term goals mightshift, but for the time being
what your long-term goals areand helping you map toward that,
I think would be really cool.
Maybe that's like a furtheriteration of just like matching,
but that would be awesome.
Speaker 2 (30:51):
I had an amazing experience back when I was a VC
and like the I'm not going toname them, but like there,
there's some amazing recruitersout there that in order for them
to make the placement fee money, they know that they have to
play the real long game.
Where they're like you knowwhat?
We'll get to know you now.
We'll help you think throughyour career, like your
deal-making, like yourpositioning.
How do you market yourself as aprofessional?
(31:12):
What should you be focusing on?
Where should you be spendingtime?
Like all those conversationsthey were having with me and I
was amazed but like, how muchamazing value do I get?
And they never made money offof me yet.
Like I don't think they everwill.
But it's amazing that if youhave somebody that is willing to
play that long game, sharethose insights, share also their
contact.
It's fascinating.
(31:33):
The only problem often with realrecruiters is that they work
for both sides, which makes,let's say, it's hard if you have
two bosses or let's say, twothings to keep in mind.
The true beauty of having acareer agent.
And that's why I believe theworld with agents is going to
move towards a better internet,because you can serve one master
truly, for instance, where yousay, okay, I have this job offer
(31:57):
or somebody wants to hire mefor a project that I know that
I'm not qualified for, should Ido this?
You could never ask your realrecruiter that, because then the
decision is made for you versusan AI agent that you know and
trust and that you know that issecure and would never share.
That you can reason throughthat, and there's a lot of
people that make poor decisions.
Right, they don't run a properprocess, which means that they
only hire for three.
(32:18):
They apply for 10 companies,get interviews at three and take
the first one, the first offerto land, which is insane.
Right, that's one of the thingsthat they teach you at business
school, which costs a lot ofmoney just to to learn that, and
there's such an opportunity totry and instill better practices
for a wider audience there.
And, yeah, this new softwareparadigm might just provide the
(32:41):
platform for it.
Speaker 1 (32:43):
Yeah, that's really cool, elijah, do you have any
thoughts on that?
Speaker 3 (32:46):
I'm just curious how you think that companies like
OpenAI will respond.
I know there's agents, but as Ifind myself using GPT and other
Gen AI tools, I don't reallywant to pick an agent for this
question or that question.
I just want to ask it to GPTand if I could share my resume,
(33:11):
share different pieces of datain a secure way, right, that
wouldn't be used to train theirmodels or whatever.
I would rather do that.
This is just personal, right,Then have an agent for
everything.
I have 40 different agents One.
I ask personal financequestions to one, I ask career
questions to one, I ask likerecruitment thought leadership
(33:32):
questions to, and I always haveto figure out which one I should
ask what question to.
Does that make sense?
Yeah, totally.
Yeah, I think it helps out ofthe user.
Speaker 2 (33:43):
No, it is a fascinating one.
I don't have the answer.
I don't think anybody has.
Speaker 1 (33:47):
What.
Speaker 2 (33:47):
I do know is that right now, people for the
technology come to chat GPT,right, that's where they go and
that's where they expect thingsto live.
The bet that even OpenAI istaking is that.
No, we just need to get thistechnology everywhere so that it
becomes the go-to in any pieceof software and therefore in any
product or service.
My bet there for now is thatpeople will have, for certain
(34:10):
functions in their life, youwon't mind the structure and the
format of a certaincommunication channel, like
iterations, where you say, okay,a recruiter should not bother
you every week, right, if you'renot actively looking, you
should have a call every quartermaybe.
So a lot of that is contextdependent and context switching
(34:32):
is expensive.
So if you can do that in a flowthat makes sense, then that's
fine.
If you zoom out from a companybuilding perspective and that is
also a view that I think isshared by OpenAI they want
different people like myself tocare about one problem and build
solutions for that one problem.
It's true that a lot of thoseproblems and solutions might
(34:53):
have touch points with consumers, and what I anticipate
happening there is then forthere to be a meta agent where
if there's too many agentsdealing with too many things,
then you have a personalassistant that deals with your
career agents, and that is whatsuperstars, again, also do.
Speaker 3 (35:07):
An agent for your agents right.
Speaker 2 (35:10):
And I don't know, but that would be one of the bets
that I could foresee.
Obviously, having the attentiondirectly as a business with
consumers is more valuable, butthat might be the world that
we're evolving into Changingconsumer behaviors.
It takes a while, but ChatGPThas shown that it can actually
go pretty rapidly, so I'm veryexcited to see what it will look
like.
But I do know that, yeah, thefuture of talent and opportunity
(35:34):
matching will need to, let'ssay, reinvent itself within,
let's say, within that paradigmshift.
And, yeah, like happy to, as asmall startup, take on that bet
against giants that are thelinkedins and the indies of this
world, who obviously sit on amajor advantage but who also
have legacy.
So, yeah, I'm stoked about whatthe next 18 to 24 months will
(35:54):
bring for our space yeah, it's a.
Speaker 1 (35:57):
It's definitely a pretty, pretty cool time here
and we've had probably six sevenceos on the show thus far
specifically to discuss how aiis being incorporated into
recruitment at different stagesof the funnel.
So definitely been learning alot here.
And, jacob, I just want to saythank you so much for coming on
to the show today with us andsharing your insights Any like
(36:20):
kind of parting thoughts ofanything we didn't cover yet
related to AI.
It's cool.
If not, I'm just wondering ifthere's anything else you want
to share with the audience, andwe have a couple of minutes here
.
Speaker 2 (36:29):
No, maybe a last thought there is actually to.
I would challenge, indeed, thewider recruitment industry to
think beyond just like how canwe spam more at like cheaper,
because that in itself cannot bethe long-term vision Like what
will continue to happen andwe've seen that now with, for
instance, google and Microsoft,like they're now making it
(36:52):
harder to land in inboxes, andso we'll see a shift away from
that.
Like we need to have the realdiscussion of like how can we
drive value both for ourcustomers, like our stocking
companies and therefore theirend customers, and for
candidates.
And therefore, I think we needto sometimes just zoom out from
okay, like only candidateidentification and then spamming
(37:12):
?
No, it needs to go beyond that.
And that's why I feel like youfeel me being riled up about
some of the discussions we'vehad.
That doesn't negate the factthat there's a lot of
productivity to be gained, butwhat I believe and what I want
to do is we start on theproductivity side and change it
to an access game.
And yeah, and those are some ofthe thoughts that I feel like
(37:37):
not enough people are havingthat conversation as to what the
five-year plan looks like.
But, yeah, happy to try andchange and influence that
narrative, because it mightactually be coming quicker than
we all think.
And then, obviously, on theshort term, if you're a staffing
company and you're working tofuture-proof your business, then
yeah, we're happy to partnerwith you, because it does start
(37:58):
with a mandate.
If you want to drive value forcandidates and your end
customers, then having a mandateto fill positions is incredibly
powerful, and that is somethingthat staffing agencies know
really well, and recruitmentagencies as well is getting
closing clients and gettingthose open positions.
It's impressive how muchhustling goes around in that,
but it's a big shame if yoursales team works so hard to get
(38:22):
a client and you lose it becauseyou didn't deliver quickly
enough or at high quality, andthat's where Holly can make a
very meaningful difference.
Speaker 1 (38:29):
Yeah, I love it.
That's a great summary there.
In conclusion, elijah, anyother follow-up thoughts on your
end?
Speaker 3 (38:34):
Just the last thing I would mention, going off what
you just said, jacob, is I don'tknow if either of you have
heard of Mark Kosoglow.
He was the, I think, svp ofglobal sales at outreach during
a lot of their scaling, and thenCRO at Catalyst.
Anyways, really recently, likewithin the last six months, he
started a company calledOperator and they're talking
(38:56):
about the great ignore, right,they're in the sales space and,
as you're saying, jake, it's notabout just sending more emails.
A lot of times, recruitmenttools are either trailing behind
and looking to what's happeningin like the sales space and
sales automation, outreach, etc.
I'll be curious to see whatsome of the thought leaders in
the sales space do, wherethey're trying to strip things
(39:19):
back and focus more on likehuman connection and meaningful
conversations to see what we canlearn for recruiting, because
it feels like recruiting isdoing what you're saying, jacob,
right.
Like how do we send moremessages to more people that are
more personalized to get, like,more interested candidates?
And I think there's a couplethought leaders in sales that
(39:40):
are realizing the sales emailsare being ignored and we may be
on their precipice in the nextsix to 12 months.
You have similar thingshappening for recruitment.
Just too many emails that peopleare getting so anyways just
wanted to throw that out thereas something to keep an eye on
is how the sales space combatswith that Gen AI kind of hitting
(40:02):
massive amounts of emailoutreach.
Speaker 2 (40:06):
Fascinating.
But that's where I see thedifference, actually, and that's
why I'm actually moreenthusiastic about the space
we're in than the sales spacePeople.
I don't anticipate selling tomove to an agent-to-agent world
anytime soon, because nobodysets up an agent that says you
know what, please sell me, likeyou might have a more secondary
(40:31):
effect which is hey, I want torun a better business, I want to
become a better human, I wantto become a healthier.
No, you don't.
But the career function is morestraightforward Our entire
industry in the HR space.
What we do is we match talentand opportunity, and that is a
fascinating match where you canhave a real deep impact on
people's lives.
But it's more constraints,which means that transforming
that into an agent-to-agentworld in which we can imagine an
(40:54):
AI recruiter and imagine an AIcareer agent is more
straightforward and therefore,like the fighting, the noise and
the signal-to-noise ratio beingmanaged on both ends is
something that I see happening,first in recruitment and maybe
at a later date in sales.
So, yeah, I'm actually veryexcited about that and I think
that recruitment might actuallylead the way for a change, maybe
(41:16):
.
Speaker 1 (41:16):
Oh, yeah, that'd be amazing.
That would be a nice change tosee more of that, but anyways,
yeah, this has been a greatepisode.
Jacob, thanks for coming on.
Speaker 2 (41:25):
No, all pleasure.
Speaker 1 (41:31):
Super cool.
Thanks for having me and it'sbeen a pleasure getting to know
you.
That's great.
Yeah, likewise, If everybodytuning in, we have many more
great episodes coming up todiscuss AI and hiring probably
close to at least 10, 15 moreepisodes.
So make sure to continue tocheck us out.
Thank you so much for joiningus today.
Take care.
Hello, welcome to the Breakthrough Hiring Show.
I'm your host, james Mackey.
Thanks for joining us today.
I am joined by Elijah Elkins,our co-host.
Elijah, what's going on?
Doing well, doing well, good.
And we're also joined today byJacob Klerhout.
Jacob is the founder and CEO ofHolly Hires.
Jacob, it's great to meet youand thanks for joining us today.
Speaker 2 (00:20):
No, thanks a lot for having me.
It Thanks a lot for having me.
It's a pleasure being here.
Speaker 1 (00:22):
Yeah, it's going to be a great episode, I guess,
just to kick us off, are youbased out of London or where are
you based right now?
Speaker 2 (00:27):
Yeah, so I'm, let's say, a Belgian, spent some time
living in Paris, currently livein London and actually spend a
lot of time in San Francisco,because that's where things are
happening when it comes to AI.
Speaker 1 (00:43):
Everything try and spend as much time as possible
on American soil.
Okay, cool, nice.
Yeah, we're looking forward tolearning more about Holly Hires.
I saw that you started thecompany and it looks like around
December 2022.
So I would love to, just likeElijah, and I just want to learn
about what it is that got youto start the company and primary
value proposition of whatyou're building.
Just an overview to get usstarted would be great.
Speaker 2 (01:05):
No, happy to Myself.
I used to be an intercapitalistinvesting in early stage
businesses, which is an absoluteprivilege to have as a job.
Before that, actually, togetherwith friends already, you used
to run a small recruitmentagency placing investment
professionals, which was a blast.
I learned a lot and also theregot the knack for the talents,
or the match between talent andopportunity.
(01:26):
While being a vc invested in acouple of really exciting hr
tech businesses that turned intounicorns, which was a real
privilege to to work withamazing founders this closely.
But for me the mission allalong was to go out and build a
business of my own and at somepoint after a couple years you
have to either, let's say, putyour money where your mouth is,
leave the cushy and goldenhandcuffs there and go and do it
(01:48):
, or you commit to theprofession of a venture
capitalist, because the time tofeedback cycles are infinitely
long, so you need to reallycommit to that.
I took a leap of faith there.
Together with my co-founder,who's a fellow Belgian, we first
got started building a talentmarketplace where on one side we
had freelance recruiters and onthe other side companies
looking to hire.
What we did was obviouslymomentum building on both sides,
(02:12):
and then quality control in themiddle.
Initially that was going well.
We managed to get a couple ofthousands of recruiters on board
.
We had a specific niche wherewe had worked for some of the
largest brands in the world,managed to make that profitable.
But after a while we came to theconclusion that, okay, quality
control needed, say, technicalsolutions.
We couldn't just keep on addingpeople to that equation.
(02:33):
And that's when we startedplaying with the back then
technology that was at itsinfancy, the GPTs of this world,
this world.
And it is at that point that werealized that this technology
would not only disrupt our ownbusiness but actually going to
reshape a large part of thevalue chain in the industry at
large.
And with that in mind, we said,okay, let's be the change we
(02:54):
anticipate, going for thisindustry and start building what
we think the future ofrecruitment looks like.
And that's how we got startedwith Holly Hires.
Speaker 1 (03:02):
Nice.
Okay, that's really cool, andusually I don't know I end up I
feel like monopolizing the firstseveral questions, so this time
I'm going to take the backseat.
Elijah, if you want to kick usoff some questions, that'd be
great.
Speaker 3 (03:11):
Sure, yeah, I would love to understand a little
better, jacob, what exactlyHolly Hire does, right In a
detailed way, and the threedifferent areas that it shows on
your website, right Like thedatabase and the outbound and
then the inbound.
Speaker 2 (03:27):
Yeah, totally.
So zooming out slightly fromthat is I believe that AI is
going to change the way we hirepeople, and not only on the
company side, but actually alsoon the candidate side.
And like listening to thepodcast, for instance, like I
feel there's a lot of focus thatgoes into the company side
because that's where talentprofessionals sit, but there's
real implications to having AIagents on the candidate side as
(03:50):
well and we actually play withthat.
If talent acquisition likematching talent and opportunity
changes to an agent, to agentworld, then all of a sudden both
companies and candidates haveAI agents optimizing for them.
Companies and candidates haveAI agents optimizing for them.
Basically, you have one of thetransaction function, the career
(04:12):
agents of a candidate thathelps you think through okay,
where do I want to be?
Like, let's filter theopportunities that I get spammed
with, but also make sure thatI'm always aware as to what the
most exciting opportunities forme could look like.
And on the flip side of that onthe company side you have an AI
recruiter.
The flip side of that, on thecompany side, you have an ai
recruiter.
And what an ai recruiter shoulddo is make sure that you
attract and the most exciting ofall individuals, just like you
would expect that from like yourbest recruitment efforts, right
(04:35):
so, and that's actually wherefirst we got started with an ai
agent called holly.
Holly is an ai recruiterspecifically built for staffing
and recruitment companies andwhat she does, indeed, is built
automatically, build a top-upfunnel for your, for your
company.
What happens as soon as aposition goes live in your ats
whether that's yeah, bullhorn ora job diva, like a position
(04:55):
goes live, ollie picks it up anddoes one of three things, as
you alluded to.
The first thing is inboundvetting.
As we all know, like everybodyis getting spammed, a lot of
platforms have one-click applybuttons, which means that the
inbounds you get signalovernoses is deteriorating
rapidly and staffing andrecruitment companies expect
(05:16):
solutions to help solve that andthat wholly helps mitigate.
I'll get into the how in asecond.
The second part is a lot ofcompanies, and especially those
large recruitment and staffingcompanies that we serve.
They sit on a lot of data.
Everybody always tells you datais the new oil, data is the new
gold.
Everybody invests in havingdata, but when it comes to
(05:37):
actually using that data, thenit's surprising how little If
you look at the placements thatrecruitment or staffing
companies make yeah, less than5% tend to come from internal
database searches, which isinsane because these are people
that you have consent to reachout to, that know your company
and your brand.
So what we do there is webasically let Holly search
through that data in a novel way, leveraging the latest
(06:01):
technology, and, by extension,she can also do that for the
outside world.
We have, let's say, a verylarge database of 750 million
profiles.
What Holly will do is, as soonas that position goes live,
she'll start working on thatposition.
She'll email the recruiter incharge saying, hey, I found 100
candidates.
If you're okay with that, I'llreach out to them automatically
(06:22):
In a hyper-personalized way.
She would drop connectionrequests, emails, linkedin
messages, emails all of thatwithout having to basically do
much.
And there it depends on, let'ssay, the setup and the
agreements we have withmanagement.
But either it happens bydefault, really trying to make
the process as seamless and evennot requiring any real
(06:43):
interaction, or recruitersindividually come and sign off
on certain campaigns for people.
Speaker 3 (06:51):
Nice.
So it sounds very comprehensivebeing able to handle all three
of those, because a lot of AIsolutions try to only do one of
those.
Is there any, I don't know?
Do you feel like the approachto all three has made it where
you can better serve customers,or do you feel like you do
(07:11):
struggle with any certain usecases?
Yeah, I'm just curious.
Speaker 2 (07:16):
That's an interesting question.
When buying solutions,especially like for our ideal
customer profiles, which are,like, let's say, mid-size
staffing companies, the level ofstakeholder management already
required with implementing onetool is insane.
What we're pushing for is,basically, you want to remove as
(07:37):
much friction from the processas possible, and that also means
buying five vendors to helpsolve one workflow, and that
also means, like buying fivevendors to help solve one
workflow.
Right, if you take the workflowof getting like interviews with
great candidates on that top offunnel, yeah, our clients were
pretty clear that, look, I don'twant to buy someone else in
doing this.
Please help me, please buildthis for us.
(07:58):
So we do a lot of, let's say,product development with our
customers and yeah, especially,we got started on the outbound
side of things, that's, let'ssay, where our bread and butter
first was.
Our strongest customers becamestaffing companies, and then
they said, hey, this analysisthat Holly does when presenting
candidates, could we also dothat for our inbound?
And then we said, hey, yeah, wehave all the flows already.
(08:18):
It's basically just pluggingthem in a separate entity and
with that we can serve thosedifferent streams.
Also, I know that some of thesestreams are not necessarily
built for longevity.
For instance, I would expectATS vendors to pick up and to
start doing a better job withsearch in their own database.
(08:39):
They have a very strongincentive on doing that, but at
the same time, the incentive hasbeen there for the last 10, 20
years as well.
And that hasn't changed thatmuch.
Yeah, I know, like we let's say, it's not easy to handle those
multiple use cases, but it doesget really appreciated by our
customers.
Speaker 3 (08:59):
Nice and have you?
I'm curious because that usecase for staffing and
recruitment companies right.
They do tend to probably havelarger databases than a lot of
just normal kind of corporatebusinesses, but it seems like
the solution would be relevantfor corporate recruiting as well
.
Is that something you guys areexploring or you just feel like
(09:20):
it's really better to focus onthe staffing industry right now?
Speaker 2 (09:24):
We do work for a couple of end customers.
It's just, if you think about,let's say, the go-to-market
motion as an early stage startup, it just makes more sense for
us or that's something we'velearned to focus on.
Businesses where hiring istheir bread and butter, where,
let's say, technology is, yeah,I wouldn't say sometimes
underserved, but if you look atlike how old school some of the
(09:46):
software, like the core ATSsystems, is, yeah, there's just
a very large opportunity andalso I would argue that there's
a larger willingness toexperiment with new technology
there.
If a lot of people are talkingabout like a downward pressure,
needing to do more with less,and if you're like recruitment
or staffing business, yourbusiness is very person, like
people intensive, needing to domore with less.
(10:07):
And if you're a recruitment orstaffing business, your business
is very people-intensive andeverybody who owns or runs a
staffing company knows thatthere's a lot of labor that goes
into building talent funnelsback and forth with those
customers and business ownersjust identify that AI can have
an almost transformative impacton that.
So that's where we got started,or that's where we decided to
focus, not because we can'tserve end customers, but, yeah,
(10:28):
the level of pragmatism and theurgency is just larger.
And also, speaking like from alot almost vision perspective,
they know hiring really well andso that means that if you can
learn from them that it becomesalmost easier to then go back
and do it for in-house teamsafter that.
Speaker 3 (10:46):
Yeah, that's really interesting.
Thanks for sharing that.
Speaker 1 (10:54):
It's also like a consistency thing in my opinion,
right, like in any marketenvironment, staffing agencies
are going to be hiring, sothere's always going to be that
amount, like a certain amount ofdemand, but of course, like
that also is true of like uppermid-market enterprise customers
as well, there's always going tobe hiring happening.
But, yeah, I could see thatmakes a lot of intuitive sense
to me in terms of there's abigger push for productivity
(11:18):
gains and organization andsearch for databases for
candidates and whatnot through astaffing agency, just because
of how difficult it is from amargin perspective to run a
services company where youroverhead expense for databases
for candidates and whatnotthrough a staffing agency, just
because of how difficult it isfrom a margin perspective to run
a services company where youroverhead expense when it comes
to payroll is just massive rightTo have recruiters on payroll.
And then, particularly for thesestaff augmentation firms or
contingent agencies, which havethese contingent revenue models
(11:42):
that are difficult to predictout as well, just having a
solution where we almost like,regardless of the annual
contract value, it's probablythe efficiency gains are going
to outweigh what it couldpotentially take for to have
several junior recruiters doingthese database searches and
probably a lot more effectiveand then better.
Like it trickles down to likefaster placements, lower time to
(12:05):
fill, just probably likestarting top of funnel but looks
better on a pnl and then soit's more sustainable business.
But then it's also likesnowballs right down funnel into
revenue and growth.
Speaker 3 (12:18):
I would assume potentially so isn't that
similar to what when weinterviewed qual a few weeks ago
?
On the podcast they're runningsimilar motion like going after
staffing and recruiting.
I don't know, jacob, if you'veheard of Qual yet, but they do
more of the like a screening,yeah, like a voice agent, so
that's interesting too, offurther down funnel.
(12:39):
But they're doing recruitingand staffing, yeah.
Speaker 1 (12:41):
I think it's like a similar kind of motion where
it's like it's a different,completely different product.
But what I mean by that is Isee the appeal to go with having
a like a staffing, staffingcustomers particularly early
stage because, like, the demandis going to be there and is
essentially as long as they'regoing to be in business, they're
going to need your productright it's actually a good
product.
Speaker 3 (13:01):
They're going to stick with it.
Speaker 1 (13:02):
It's actually a good product, they're gonna stick
with it, it's like they need youconsistently.
It's not like these techcompanies where it's like 2021
they're hiring like crazy andthen they just cut off, like
their entire north america staff.
Speaker 2 (13:15):
No, totally and I see that actually in the
exploratory calls where, likeyou, you have those enterprises
and then they're like oh, we'reexploring tools for like next
year, and then like all that isgreat, I'm happy to be on a call
with with them and learn fromthem and see how they think.
But, yeah, I, I would preferworking with customers that need
our solution yesterday andthere, yeah, with staffing
companies.
(13:35):
The case is very obvious.
They want to move faster, notsaying that the sales cycles are
infinitely short.
Either it still requires, let'ssay, a good amount of
stakeholder management andmultiple meetings, but it is
interesting to see how staffingis catching cycles are
infinitely short.
Either it still requires, let'ssay, a good amount of
stakeholder management andmultiple meetings, but it is
interesting to see how stuff iscatching up and also knowing
that, um, yeah, that market,especially as it got like the
economy, starts lookingdifferently, or the outlook is
(13:58):
slightly more, let's say,pessimistic.
Like people need to compete, uh,even harsher.
It's like it's all about speeds.
Like you need to compete evenharsher, it's all about speeds.
You need to deliver really goodquality service at breakneck
speed, which, yeah, obviously,if you're marvelously set up
with amazing teams, then great.
But yeah, it's pretty obviousthat technology can do a
(14:19):
significantly better job.
Holly, there, in building leadlists, in reaching out to people
.
Like Holly does that in fiveminutes.
She does the work that arecruiter would need two days
for.
And that's also the type ofreporting that we do towards
those like the staffing ownersor managers, like heads of
delivery, where we say, look,this week Holly worked the
equivalent of seven full-timeequivalents for your team and
(14:41):
that, yeah, that doesn't.
Or in the beginning that mightfeel a bit scary, but at the
same time it's helping everybodyin those teams reach and crush
the targets and goals, and thatfor, let's say, a fraction of
the cost of hiring extraemployees to do it.
Yeah, I feel like the trade-offof hiring additional recruiters
to do better delivery andhigher speed versus investing in
technology is a very obviousone.
Speaker 1 (15:03):
So it's just to get a sense of the full workflow
because we covered a lot ofground pretty quickly.
So it's like creating, likepulling candidates from the ATS
to create like essentiallyshortlist for roles or whatever
else.
It's also then doing like thecustomized messaging and doing
the emails and then, from ascheduling standpoint, is it
also essentially schedulingscreens or how does that?
Speaker 2 (15:27):
For now we end when that first, whatever the first
step of the process looks likewhether that finding in your own
database and engaging withpeople, or doing outbound and
(15:54):
having multi-touchpoint dripcampaigns, through which then
Holly can also come back andanswer let's say, the follow-up
questions, gather resumes, thosetypes of things she does for
you and you do that byconnecting your LinkedIn account
and emails and all of a sudden,yeah, you have a meeting booked
with a great candidate, whichfeels pretty magical.
In the beginning it's a bitscary, but once you explain to
(16:20):
people how to manage therequirements and how to manage
the process, then they tend tobe very enthusiastic.
We see people now with highexpectations and that increase
the mandates that Holly gets ona weekly basis.
Speaker 1 (16:35):
So can you tell us like so in terms of your
products, like stack rankingcandidates, right?
So it's like when it'scompiling what's like, how is it
going about stack ranking andevaluating profiles for
relevancy?
Speaker 2 (16:47):
Yeah, so, what we do there is basically, we pull in
the candidates and then we makea list based on the job
description, we make a list ofrequirements.
So one of the things that wewanted to start implementing
relatively early on was, likemore declarative hiring.
You don't want to think insearch terms, but you want to
think in requirements, and whatwe always do is you bring in a
(17:08):
profile for a specific position.
That position has a shortdescription and a list of
requirements Must have two tofive years of experience, must
have a degree in computerscience, must have worked on
consumer-facing products.
Those are things that thosefirst two might be easy to boil
down into a Boolean, but thelast one is not and that
(17:30):
requires a level ofunderstanding.
So what we do is, for every like, holly will construct an entire
tree of options with likesearch parameters that shall all
run in parallel.
You can think of that as likethe equivalent of a couple hours
, if not days, of search workjust by filling in Booleans, and
she will vet the results.
(17:50):
So stack, rank the results thatcome up, all of that again in
parallel, against those criteria, saying okay, who here meets
the criteria?
And there we have some sort of,let's say, reinforcement
learning algorithm, where Hollybasically weighs the going
deeper down the tree that isworking for her versus exploring
new branches, and there whatyou end up with is a list of
(18:11):
candidates where you see yes,meets criteria one to five, yes
inferred.
Where she's, for instance, theconsumer arguments If somebody
works for Revolut and they workon the mobile team, then you
know that they've built productsthat have consumer facing.
That is not something that youcan boil down in a boolean, but
Holly understands that and willmake the case for that.
(18:32):
It will be question marks likeI can't possibly know this or
does not meet this, and then,based on how many of the
requirements are met, she willdecide whether or not somebody
should be pursued or not.
Speaker 1 (18:48):
So is this primarily on the resume or also just like
within the ATS?
If people have answeredscreening questions in the past
scorecards, things of thatnature is it pulling in data
from there as well?
Speaker 2 (18:59):
Yeah, we pull.
So for the internal search part, we pull data into our own
system and then we pull as muchas possible.
If people have prior relevantinformation, then great.
It's often, though, very messyand it's almost more worth.
It's just not worth the effort,because standardizing that
across different roles anddifferent systems.
(19:21):
Often people have switchedsystems, switched methodology,
so it's not always worth theeffort, but Holly can use any
information that is presentthere.
The most valuable source theretends to be the resume and the
notes that people have left oncandidates.
Speaker 1 (19:38):
Okay, Got it.
So notes too, All right, but myother question would just be
like for your staffing customers, what types of roles or
specializations do theytypically have?
Paul was saying the CEO ofDavid Tell was telling us that
he was seeing a lot of demandwithin light industrial staffing
agencies.
For light industrial, he justsaid, just due to a ton of
(19:58):
volume of openings that theyhave in the United States right
now.
Are you seeing differentspecializations really stand out
in terms of where you're seeingthe most demand?
Speaker 2 (20:07):
Yeah, absolutely, and that makes a ton of sense.
Also, if you think about thelike, which parts of the flow do
you automate?
First, that as a staffingbusiness is a question you need
to ask right, okay, where arethere obvious opportunities?
What are the most easiest?
Which ones affect my customersand my candidates?
And they are obviouslyintroducing voice agents
fascinating, but that that doeschange the experience.
(20:27):
For for your candidates inlight industrial, yes, there's a
lot of opportunity.
However, what are bread andbutter tends to be the highly
skilled, actually, like thereally white, like white collar
staffing companies, because forthem it's like the
identification matters, likeit's the difference.
That's also why they tend to bemore expensive.
(20:48):
Right, it's.
Not only is the salary of theperson significantly higher,
which makes it like they aremore demanding, they're harder
to find, harder to close.
So that's where we play.
We tend to do softwareengineering, anything that is
healthcare or pharmaceuticals,like the jobs that tend to have
advanced degrees, are the onesthat the staff and companies
that we focus on, mainly becausethere Holly's intelligence
(21:10):
matters, like she understandsthe difference between a C++
developer and a React developer,and it's that level of
understanding that yourcustomers expect from you or
demand from you.
So we yeah, that's the realmwhere we play and that's also
where Holly can make the biggestdifference, because judging,
yeah, if the quality is okay,you need to be able bodies and
(21:31):
be able to come and work thisshift.
That is obviously alsoimportant that you can still
validate, and there's a lot ofan entire, let's say, focus of
the market that needs to do that, but that's not where holly's
strengths lie yeah, that's.
Speaker 1 (21:43):
That makes a lot of sense too.
It's like where more nuance isneeded, like exactly okay, cool.
So what about futurefunctionality when you're
looking like in terms ofcustomer feedback right now, and
then just your own knowledgeand insights into what you've
seen on the market and what youthink functionality and features
are going to make the mostsense over the next six months
(22:05):
to a year?
Do you have a?
What are your top priorities interms of additional
functionality for your product?
Speaker 2 (22:11):
Yeah, the first thing there is the HR tech space, and
then, especially, like the coreinfrastructure.
It's such a like, such afragmented space that it's
insane the amount of coverageyou need to have if you want to
integrate just the five largestor the 10 largest, and every
time you meet the new excitingcustomer, they're on a system
that you don't get support.
So there's a lot of likegrounds that needs to be covered
(22:37):
there.
And then, additionally, likethe details matter when building
systems like this.
So you, you want to build inenough and I can refine enough.
Okay, the tweaks and like ofthe of the core of your flow.
It's sometimes like smallthings that like the way you
communicate towards therecruiter or create a buy-in
front that wholly creates buy-infor certain candidates, for
instance, like it matters.
(22:57):
We're now, for instance, workingon resume formatting.
Like a lot of customersmentioned that they spend like
hours on trying to formatresumes.
When we looked at that as acompany, we're like what, how is
this?
How are people like?
How can this be a job?
But, yeah, apparently, largetraffic companies have full-time
like people in like often noton the payroll, but very often
(23:19):
freelancers that do nothing butthat.
So there's a lot of.
As we further pull like on somethreads, we learn a lot of
additional functionalities whereholly could have a very big
impact.
But in in terms of the longerterm vision, I believe in that
agent-to-agent vision where notonly will we automate the hell
out of things on the companyside of things and primarily for
(23:40):
staffing companies, but if Ithink, okay, three to five years
, what excites me it's trying tomatch that with a consumer
angle.
If you think through, okay, the, the inefficiency of trying to
like, blast messages towards,like the whole world, everybody
who's high and blasting towardsthe whole world, and then on the
receiving end, like not evenseeing or hearing things anymore
(24:02):
, even great opportunity likeGoMist, because of the fact that
it's so hard to filter thatsignal from noise.
I'm really excited about beingable to match those two and I
think the new paradigm that isGen AI allows you to work with
unstructured data and interactwith software in novel ways, and
those are two things that withHolly we take, let's say, really
(24:25):
too hard.
But applying that on the flipside, on the, the candidate side
, is going to allow us to createfor our customers a channel
through which candidates can belike, reached and really reached
, but only if it makes sense.
Because that's the beauty ifyou can find a real match, then
you earn your spots to get theirattention.
And I feel like a lot of the oldschool companies, old school,
(24:47):
okay, everybody pays their taxto linkedin, right, but like
linkedin, you pay per email.
You don't pay per conversion,right, where you feel that
there's like an almost like awrong alignment of incentives.
So I'm really excited abouttrying to, let's say, correct
that wrong, but it's going totake more than a couple quarters
so what?
Speaker 1 (25:07):
I'm curious what do you guys think in terms of how
candidates are going to beleveraging AI?
What product functionality arethey really going to be using?
I guess there's optimization ofjob descriptions, I don't know.
I guess leveraging AI to maybefind jobs or apply to jobs.
Honestly, on the candidate side, I haven't given it as much
thought.
So I'm just like Jacob.
(25:28):
You're talking agent to agentexperience.
What do you think is going tobe like?
What are?
How are candidates going to beleveraging job seekers, going to
be leveraging ai over the nextfew years?
How's that going to change?
Speaker 2 (25:39):
I.
My bet there is that, likepeople will have an experience
similar to the ones thatsuperstars, like movie stars and
sports people have.
Like they have an agent.
Like they agent, they don'thave to think about their career
the whole time because somebodyelse is doing it for them, and
that is something reallypowerful.
With the democratization ofintelligence, we'll see more
(26:00):
people having access to what Iwould call a career agent, and
the idea there should be that acareer agent finds tempting
opportunities for you even whenyou're not actively looking.
That is how I think about it.
It should be quality overquantity and always on, so that
your agent always has your back,and that concretely will
translate in my head tosomething where you just like
(26:23):
you, working with the best humanrecruiter.
I think the process will lookvery close to what that is like.
You'll have a relationship withyour agent, which means that
agent needs to be close to you.
My bet would be that it willlive either in a messenger trend
like iMessage or WhatsApp,where you can interact through
text but, most importantly,through voice, and there I think
(26:46):
, like the other company that wewere discussing is on an
interesting trend that we've runsimilar experiments there,
where, if you can get to know acandidate not only their resume,
but actually also what they'reabout and what they might be
looking for, because a lot ofthings such a significant part
of, like job matching happensthrough things that are not
present on your LinkedIn.
Right, is it okay?
I want to move closer to my mom, I just had a second child, I
(27:08):
need better insurance or I needa higher pay and I'm willing to
work harder, or no, I'm towardsthe end of my career and I want
to start, let's say, taking moretime with my family.
So these types of things youdon't put on LinkedIn, but you
can tell your AI career agents,and what will happen in my mind,
is the two agents the one thatknows the company really well
will have an incentive to tryand get in touch, and it will
(27:30):
almost become like a protocolwhere, okay, you share an
opportunity, you, a company,shares one, a career agent
responds saying, hey, no, I'mnot open at all because you
don't meet any of the criteriathat my clients being like okay,
my boss has set for me or whatI understood from how we've
communicated prior, and it'sbasically that gliding scale
(27:52):
where, if you feel anopportunity, that does mean a
lot of it, that you will expectyour agent to run it by you and
say, hey, you know what, likeJacob, even though you're like a
great founder, but OpenAI isworking on a like a career agent
thing.
Would you want to chat?
Even though I'm definitely notleaving my startup, I would want
to know that.
So that's so.
That's the type of thing thatyou would expect your agent to
(28:13):
do, and it's that trust and thatproximity that will enable a
whole new way of matching andI'm very excited about that.
That would be my bet as to whatthe career side of things or
the candidates side of thisworld will look like.
Speaker 1 (28:26):
Yeah, that's going to be really cool.
That's a pretty compellingfuture.
Just essentially, that's goingto be really cool.
That's a pretty compellingfuture.
(28:46):
And to the extent, too, whereit's not just punching in
requirements but to the extentwhere it can be a guide as well,
would be pretty't necessarilysure, unless a candidate just
starts asking for advice and youhave you decide to take 10
extra minutes to try to, youknow, help somebody out and
you're like, okay, here we go.
It's like getting into thenuances of okay, maybe you can
get this jump in comp right now,but if you take this path, then
(29:08):
you're ultimately going tostall out two years from now and
it's going to be hard for youto have continued growth five,
10 years in the future.
Or thinking, yeah, basicallythose like decision mapping
where it's like all right, ifyou take this step short term
here, it helps you do this.
Long term, it's going to makethings challenging.
Where you take this other step,You're going to stay at a
similar conference for longer,but the experience you're going
to gather is going to be morerobust or helping you understand
(29:29):
like gaps in your skill set orexperience that could prevent
you from getting jobs and alignyou with roles that like can set
you up for future success.
This is stuff that like, quitehonestly, like top tier talent
in most industries.
Like this is the kind of waythey're thinking, but it's not
necessarily as intuitive as wemight think.
It is A lot of people, I feel,like their careers they're just
(29:51):
going with the flow.
They push out their resume to abunch of companies and whoever
responds like where there's theleast amount of friction is like
where they end up working andthere's a to be clear, there's a
fair percentage of folks in theworld maybe even the majority
of like people that they justdon't have options.
They have to do what they haveto do.
But when we're talking aboutlike your customers, where it's
like the white collar workers,it's people are fortunate enough
to be in this position wherethey could be more intentional
(30:13):
about their career and there'sjust a lack of intention.
It's like you look at the numberone hated interview question
and it's like what's your threeyear plan, five year plan?
It's people hate that question.
It's like why have you notthought about that?
I think it's I honestly peoplewho don't like that question.
I don't want to hire them, butI think it's just interesting
(30:34):
right, like helping you bringstructure to what's your
long-term goals.
Your long-term goals mightshift, but for the time being
what your long-term goals areand helping you map toward that,
I think would be really cool.
Maybe that's like a furtheriteration of just like matching,
but that would be awesome.
Speaker 2 (30:51):
I had an amazing experience back when I was a VC
and like the I'm not going toname them, but like there,
there's some amazing recruitersout there that in order for them
to make the placement fee money, they know that they have to
play the real long game.
Where they're like you knowwhat?
We'll get to know you now.
We'll help you think throughyour career, like your
deal-making, like yourpositioning.
How do you market yourself as aprofessional?
(31:12):
What should you be focusing on?
Where should you be spendingtime?
Like all those conversationsthey were having with me and I
was amazed but like, how muchamazing value do I get?
And they never made money offof me yet.
Like I don't think they everwill.
But it's amazing that if youhave somebody that is willing to
play that long game, sharethose insights, share also their
contact.
It's fascinating.
(31:33):
The only problem often with realrecruiters is that they work
for both sides, which makes,let's say, it's hard if you have
two bosses or let's say, twothings to keep in mind.
The true beauty of having acareer agent.
And that's why I believe theworld with agents is going to
move towards a better internet,because you can serve one master
truly, for instance, where yousay, okay, I have this job offer
(31:57):
or somebody wants to hire mefor a project that I know that
I'm not qualified for, should Ido this?
You could never ask your realrecruiter that, because then the
decision is made for you versusan AI agent that you know and
trust and that you know that issecure and would never share.
That you can reason throughthat, and there's a lot of
people that make poor decisions.
Right, they don't run a properprocess, which means that they
only hire for three.
(32:18):
They apply for 10 companies,get interviews at three and take
the first one, the first offerto land, which is insane.
Right, that's one of the thingsthat they teach you at business
school, which costs a lot ofmoney just to to learn that, and
there's such an opportunity totry and instill better practices
for a wider audience there.
And, yeah, this new softwareparadigm might just provide the
(32:41):
platform for it.
Speaker 1 (32:43):
Yeah, that's really cool, elijah, do you have any
thoughts on that?
Speaker 3 (32:46):
I'm just curious how you think that companies like
OpenAI will respond.
I know there's agents, but as Ifind myself using GPT and other
Gen AI tools, I don't reallywant to pick an agent for this
question or that question.
I just want to ask it to GPTand if I could share my resume,
(33:11):
share different pieces of datain a secure way, right, that
wouldn't be used to train theirmodels or whatever.
I would rather do that.
This is just personal, right,Then have an agent for
everything.
I have 40 different agents One.
I ask personal financequestions to one, I ask career
questions to one, I ask likerecruitment thought leadership
(33:32):
questions to, and I always haveto figure out which one I should
ask what question to.
Does that make sense?
Yeah, totally.
Yeah, I think it helps out ofthe user.
Speaker 2 (33:43):
No, it is a fascinating one.
I don't have the answer.
I don't think anybody has.
Speaker 1 (33:47):
What.
Speaker 2 (33:47):
I do know is that right now, people for the
technology come to chat GPT,right, that's where they go and
that's where they expect thingsto live.
The bet that even OpenAI istaking is that.
No, we just need to get thistechnology everywhere so that it
becomes the go-to in any pieceof software and therefore in any
product or service.
My bet there for now is thatpeople will have, for certain
(34:10):
functions in their life, youwon't mind the structure and the
format of a certaincommunication channel, like
iterations, where you say, okay,a recruiter should not bother
you every week, right, if you'renot actively looking, you
should have a call every quartermaybe.
So a lot of that is contextdependent and context switching
(34:32):
is expensive.
So if you can do that in a flowthat makes sense, then that's
fine.
If you zoom out from a companybuilding perspective and that is
also a view that I think isshared by OpenAI they want
different people like myself tocare about one problem and build
solutions for that one problem.
It's true that a lot of thoseproblems and solutions might
(34:53):
have touch points with consumers, and what I anticipate
happening there is then forthere to be a meta agent where
if there's too many agentsdealing with too many things,
then you have a personalassistant that deals with your
career agents, and that is whatsuperstars, again, also do.
Speaker 3 (35:07):
An agent for your agents right.
Speaker 2 (35:10):
And I don't know, but that would be one of the bets
that I could foresee.
Obviously, having the attentiondirectly as a business with
consumers is more valuable, butthat might be the world that
we're evolving into Changingconsumer behaviors.
It takes a while, but ChatGPThas shown that it can actually
go pretty rapidly, so I'm veryexcited to see what it will look
like.
But I do know that, yeah, thefuture of talent and opportunity
(35:34):
matching will need to, let'ssay, reinvent itself within,
let's say, within that paradigmshift.
And, yeah, like happy to, as asmall startup, take on that bet
against giants that are thelinkedins and the indies of this
world, who obviously sit on amajor advantage but who also
have legacy.
So, yeah, I'm stoked about whatthe next 18 to 24 months will
(35:54):
bring for our space yeah, it's a.
Speaker 1 (35:57):
It's definitely a pretty, pretty cool time here
and we've had probably six sevenceos on the show thus far
specifically to discuss how aiis being incorporated into
recruitment at different stagesof the funnel.
So definitely been learning alot here.
And, jacob, I just want to saythank you so much for coming on
to the show today with us andsharing your insights Any like
(36:20):
kind of parting thoughts ofanything we didn't cover yet
related to AI.
It's cool.
If not, I'm just wondering ifthere's anything else you want
to share with the audience, andwe have a couple of minutes here
.
Speaker 2 (36:29):
No, maybe a last thought there is actually to.
I would challenge, indeed, thewider recruitment industry to
think beyond just like how canwe spam more at like cheaper,
because that in itself cannot bethe long-term vision Like what
will continue to happen andwe've seen that now with, for
instance, google and Microsoft,like they're now making it
(36:52):
harder to land in inboxes, andso we'll see a shift away from
that.
Like we need to have the realdiscussion of like how can we
drive value both for ourcustomers, like our stocking
companies and therefore theirend customers, and for
candidates.
And therefore, I think we needto sometimes just zoom out from
okay, like only candidateidentification and then spamming
(37:12):
?
No, it needs to go beyond that.
And that's why I feel like youfeel me being riled up about
some of the discussions we'vehad.
That doesn't negate the factthat there's a lot of
productivity to be gained, butwhat I believe and what I want
to do is we start on theproductivity side and change it
to an access game.
And yeah, and those are some ofthe thoughts that I feel like
(37:37):
not enough people are havingthat conversation as to what the
five-year plan looks like.
But, yeah, happy to try andchange and influence that
narrative, because it mightactually be coming quicker than
we all think.
And then, obviously, on theshort term, if you're a staffing
company and you're working tofuture-proof your business, then
yeah, we're happy to partnerwith you, because it does start
(37:58):
with a mandate.
If you want to drive value forcandidates and your end
customers, then having a mandateto fill positions is incredibly
powerful, and that is somethingthat staffing agencies know
really well, and recruitmentagencies as well is getting
closing clients and gettingthose open positions.
It's impressive how muchhustling goes around in that,
but it's a big shame if yoursales team works so hard to get
(38:22):
a client and you lose it becauseyou didn't deliver quickly
enough or at high quality, andthat's where Holly can make a
very meaningful difference.
Speaker 1 (38:29):
Yeah, I love it.
That's a great summary there.
In conclusion, elijah, anyother follow-up thoughts on your
end?
Speaker 3 (38:34):
Just the last thing I would mention, going off what
you just said, jacob, is I don'tknow if either of you have
heard of Mark Kosoglow.
He was the, I think, svp ofglobal sales at outreach during
a lot of their scaling, and thenCRO at Catalyst.
Anyways, really recently, likewithin the last six months, he
started a company calledOperator and they're talking
(38:56):
about the great ignore, right,they're in the sales space and,
as you're saying, jake, it's notabout just sending more emails.
A lot of times, recruitmenttools are either trailing behind
and looking to what's happeningin like the sales space and
sales automation, outreach, etc.
I'll be curious to see whatsome of the thought leaders in
the sales space do, wherethey're trying to strip things
(39:19):
back and focus more on likehuman connection and meaningful
conversations to see what we canlearn for recruiting, because
it feels like recruiting isdoing what you're saying, jacob,
right.
Like how do we send moremessages to more people that are
more personalized to get, like,more interested candidates?
And I think there's a couplethought leaders in sales that
(39:40):
are realizing the sales emailsare being ignored and we may be
on their precipice in the nextsix to 12 months.
You have similar thingshappening for recruitment.
Just too many emails that peopleare getting so anyways just
wanted to throw that out thereas something to keep an eye on
is how the sales space combatswith that Gen AI kind of hitting
(40:02):
massive amounts of emailoutreach.
Speaker 2 (40:06):
Fascinating.
But that's where I see thedifference, actually, and that's
why I'm actually moreenthusiastic about the space
we're in than the sales spacePeople.
I don't anticipate selling tomove to an agent-to-agent world
anytime soon, because nobodysets up an agent that says you
know what, please sell me, likeyou might have a more secondary
(40:31):
effect which is hey, I want torun a better business, I want to
become a better human, I wantto become a healthier.
No, you don't.
But the career function is morestraightforward Our entire
industry in the HR space.
What we do is we match talentand opportunity, and that is a
fascinating match where you canhave a real deep impact on
people's lives.
But it's more constraints,which means that transforming
that into an agent-to-agentworld in which we can imagine an
(40:54):
AI recruiter and imagine an AIcareer agent is more
straightforward and therefore,like the fighting, the noise and
the signal-to-noise ratio beingmanaged on both ends is
something that I see happening,first in recruitment and maybe
at a later date in sales.
So, yeah, I'm actually veryexcited about that and I think
that recruitment might actuallylead the way for a change, maybe
(41:16):
.
Speaker 1 (41:16):
Oh, yeah, that'd be amazing.
That would be a nice change tosee more of that, but anyways,
yeah, this has been a greatepisode.
Jacob, thanks for coming on.
Speaker 2 (41:25):
No, all pleasure.
Speaker 1 (41:31):
Super cool.
Thanks for having me and it'sbeen a pleasure getting to know
you.
That's great.
Yeah, likewise, If everybodytuning in, we have many more
great episodes coming up todiscuss AI and hiring probably
close to at least 10, 15 moreepisodes.
So make sure to continue tocheck us out.
Thank you so much for joiningus today.
Take care.
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