May 29, 2025 • 42 mins
With markets reacting to global uncertainty and AI transforming the hiring landscape, both job seekers and recruiters are recalibrating their strategies.
Join host James Mackey and Steve Bartel, CEO of Gem, as they discuss how automation is changing resume screening, interview prep, and rediscovery of existing talent. As companies look to cut costs and boost efficiency, the challenge becomes clear: how do you hire smarter without losing the human signal in all the noise?
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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.
We got Steve Bartell back withus today.
Steve, what's going on?
Speaker 2 (00:06):
Hey, good to be here.
Speaker 1 (00:09):
And for everybody tuning in that hasn't heard one
of Steve's past episodes Steve,would you mind just doing a
quick introduction on yourself?
Speaker 2 (00:17):
Yeah, sure, I'm Steve .
I'm the co-founder and CEO atGEM.
I've been building G Gem forabout eight years.
At Gem, we're building the onlyAI-first all-in-one recruiting
platform.
So what that means is we takeyour sourcing, your CRM, your
ATS scheduling, plus full funnelanalytics and a database of 650
(00:41):
million public profiles thatyou can source from and then
thread AI through the entireproduct.
But yeah, that's what we're upto Over to you, james.
Speaker 1 (00:50):
Cool.
Today.
We have, I think, a veryaction-packed episode.
A lot of stuff to cover Beforewe get into some really cool
things regarding AI howcandidates are leveraging it in
the interview process and whatthat's going to look like as
candidates are, companies areleveraging it and then get into
(01:11):
that.
We also discussed talking alittle bit about what you're up
to at Jim, some of the morerecent product and feature
releases.
We want to talk a little bitabout candidate rediscovery,
which I think would be reallyinteresting as well, and making
that whole process a lot moreeffective and valuable to
organizations.
I think there's a lot left onthe table when it comes to
(01:32):
rediscovery, so that'll be coolto dive into that as well.
Speaker 2 (01:37):
Sounds good, let's do it.
Speaker 1 (01:38):
Yeah, so let's just start out with the market.
Last thing I checked, as of anhour ago, I think, trump's
threatening it like anadditional 50 percent tariff on
China due to the fact that theyput out reciprocal tariffs of 34
, 36 percent or whatever it is.
Of course we saw a massivemarket contraction and then
within that like tech, of course, being one of the most volatile
sectors, I think the wholemarket was down like five
(02:00):
percent ish.
Don't quote me, but it's likebasically.
And then I think tech was atleast temporarily down closer to
12 last week or something crazylike that, if I remember
correctly in the journal.
So I'm sure hopefully, maybesome of that's just like
temporary, just shock right tothe market and tariffs.
But it's definitely a reallyuncertain time right now.
And I'm curious if you'rehearing anything from customers.
(02:22):
I know like we have earlyearnings call coming out,
probably in a few weeks.
Ceos are going to be talking,but just, is there any kind of
word on the street, jim,customers, or your advisors or
VCs, or what are you hearing outthere?
Speaker 2 (02:35):
Yeah, totally so.
First of all, I think it'sreally hard to know how this
stuff shakes out.
I do think that the marketcorrection has probably been an
overcorrection.
When you think about theoverall GDP of the US,
interestingly, we're a veryheavy services country as it
relates to GDP.
I think 70% of our GDP is fromservices industry and I think
(02:59):
only 10%, 20% or something likethat is from trade, and a lot of
that is actually between Canadaand Mexico and the US, and so
when you take that factor out,it's even less.
And so when you think about themarket correction, that's
happened.
What did you say?
10, 12% or something like thatIn?
Speaker 1 (03:19):
tech.
I think I saw that Like it wasone of the hard graph things.
Speaker 2 (03:21):
I think the overall market lost like 5% and wiped
out like 6 trillion ish orsomething in market value and so
I think that's like anovercorrection, because when you
just do the simple math on thisstuff, tariffs aren't gonna
reduce that gdp down to zero oreven half of what it is.
They're gonna add some friction.
(03:42):
But so, first of all, I thinkit's, I think it's like an
overcorrection.
The second thing is it's reallyhard to know how this stuff is
going to shake out, because alot of people believe that the
administration is doing this toset them up for like
negotiations.
Yeah, there's a lot of likeimbalance in terms of how
tariffs work when you lookacross different countries, and
(04:04):
actually a lot of the tariffsout there are pretty unfair to
the US, in the sense that the UShas a much lower tariff on
these countries than they haveon us when they're importing our
goods, and so a lot of peoplethink these across-the-board
tariffs are just to get peopleto the negotiating table to
negotiate tariffs that are morereciprocal across the board.
(04:25):
It's really hard to say howthis stuff's going to shake out
until another few weeks or amonth or a few months pass and
we can actually see what's thestrategy behind this and does it
work or does?
Speaker 1 (04:38):
it not?
Yeah, it's interesting becauseyou're right, like it could be
temporary.
But I'm wondering, like it isto some extent the we did this
once before the united states.
It was like in it was a reallylong time ago.
The president called I think itwas like mckinsey, I would have
to or I'd have to go doublecheck.
But there was one time maybenot mckinsey I'll have to go
back and double check and I'llput it in the notes of the
(04:59):
episode.
Cool, I forget his name, Ithink it was that.
But he did a tariff strategywhere essentially the United
States was in a lot of debt andimplemented a tariff strategy
and back in the day beforeincome tax, that's actually how
the government collected.
A lot of income was throughtariffs and then, as essentially
we implemented the income tax,tariffs went down, income tax
(05:20):
went up and that is essentiallymodern day United States.
That's how we collect, thegovernment collects.
The revenue is income tax.
So this has been done before inthe past and it actually did
take the country from being in asignificant amount of debt to a
surplus and to a point whereit's like almost like you don't
necessarily want a country to bein too big of a surplus,
(05:42):
because what are they doing withthat money?
Right, like the money should be, you should be taxing just
enough to essentially providewhat you need to.
So you don't necessarily want asurplus, but you definitely
don't want the debt that we havenow, and so back in the day,
when they did this, it did work,but then, essentially in the
second term, this president didaway with it.
It was no longer working, butthese things are so complicated.
(06:05):
From what I was researchinginto it, it really wasn't clear
if it wasn't working becausethey were at a surplus and it
just changed the market dynamicsand it just wasn't valuable
anymore.
It was just hurting them orsomething else.
The thing is, though, againthis happened.
This was over 100 years ago.
The economy is obviouslycompletely different these days.
(06:25):
There's a lot more tradeoccurring, even if it's a
minority of our GDP, and thenthere's a connectivity of
globalization and otherindustries or, excuse me,
countries I don't know thepercentage of GDP for them and
then there's the whole.
There's so much of the marketon confidence, right, and if
people pause spending even more,how that could impact things.
(06:48):
And then, even short term, ifMexico, canada, prices are
increased on, goods become moreexpensive for Americans if that
heats up inflation.
I'm not an economist, but I'mjust wondering does that just
stop when you lower the tariffs?
You know what I mean.
No, it's a really interestingquestion.
Speaker 2 (07:06):
I think these things are super complex and that's why
there's not a clear-cut answerto foreign policy or tariffs and
stuff like that, and somethingthat happened 100 years ago
might not play out the same waytoday, like you mentioned.
And so I think all of this isto say people are feeling a lot
of uncertainty right now to youroriginal question, because it's
really hard to know how thisstuff shakes out and it's still
(07:28):
early days.
We're trying to keep a pulse onthis with our customers and
then also our prospects folksthat are considering looking at
JEM.
Whenever we see uncertainty wethink all right, how can we best
serve our customers?
How can we best serveprospective buyers who might be
(07:49):
thinking about Gem?
And the good news is we've beenthrough a few of these cycles
as an industry and so we'velearned a lot.
We've learned that when there'smore uncertainty in the market
or when companies are reallyslowing down down hiring, that
there's a much stronger need forlower cost all-in-one
consolidation.
They can save companies money,also help unify their stack.
(08:14):
There's a lot of benefits tohaving everything under one roof
, and we've even come up withsome pretty creative ways for
companies that wanna embark onthis longer term journey of
moving towards all in one to getstarted today with a nominal
amount of spend and then onlystart paying us as, like, their
different renewals come up forthe pieces that are on their
(08:38):
current stack and in this way,people can benefit from having
the all in one platformoneplatform out of the gate, but
like never be double paying forthe different line items that
they already have.
So that's not how we thinkabout it.
Internally is like how can webest serve our customers and the
market when there's a lot ofuncertainty, because no one
wants to be the last thingsomebody wants to be doing is
(08:58):
double paying for tools whenthey're headed into a lot of
uncertainty.
Speaker 1 (09:03):
Yeah, it's definitely for sure.
By the way, I just fact-checkedmyself.
I don't.
I think I saw McKinsey.
I was thinking the consultingfirm was saying McKinley, ah
yeah, 1890s, and he was a hugeadvocate of tariffs.
So I recommend people look itup.
It's really, it is fascinating.
I've wrapped my head around it,I think, as much as I have time
for interesting stuff and yeah,yeah, for sure.
(09:24):
It's getting to terms like oh,that's like a simple thing,
right, like it's prettystraightforward, and then it
turns out no, not really, butbut yeah, in terms of how I'm.
I think people are thinkingabout the market right now is
people are a lot of.
I think a lot of folks are in aholding pattern, right,
particularly in in theindustries that are directly
affected, in fact, likemanufacturing, for instance but
not just going out like, hey,let's open up plants.
(09:45):
That's like a massive, multi,multi, multi million dollar
endeavor that takes one to threeyears to even get them
productive.
So, yeah, but it's kind of okay, we just have to, we just have
to wait.
Nobody really knows, and Ithink it's just it.
Just for me, it's like I runtwo, two companies I have a
recruiting services company andI have the software company June
(10:06):
for Secure Vision it's.
I don't really know how it'sgoing to impact us.
I can say right now, ourcustomers with different
industries really nobody.
The only customers of companiesthat are pausing and not making
decisions are reallymanufacturing supply chain, like
they're at a standstill, likeany kind of deals and pipeline
related to that they're notconsidering, they're just not
(10:28):
moving forward.
But you know, in otherindustries it's essentially it's
weird, it's like business asusual, almost, despite all of
this stuff happening in thebackground.
So I guess that's good, right.
And I think, though, like, interms of customers thinking
about, like spending all in one,that's still been the trend for
the past few years, right, Ithink that in the markets going
(10:51):
into that direction andconsolidation, which is, I think
, it's a good thing, so, from afor customers.
I think that they still wantcompanies still want that.
When it comes to hiring and techstacks consolidation, I think
also this idea of being able toaccess gym, like different
products, like just to getonboarded yeah, started to start
(11:13):
adding value, pull up, givethem help, help them where they
need it and then transition theminto a full stack or a full
product suite customer yeah,definitely the way to go,
because I think folks are likelooking for all-in-one, they're
looking for flexibility, butthis is a macro trend,
regardless of what happens right, even if autonomy gets hit mid
(11:35):
to long term because of this, itreally doesn't change.
I don't think too much howcompanies are going to think
about hiring or particularly thetechnology that they're going
to be using.
If anything, it's just furtherreinforcement that we need to
optimize tech and be very leanas an organization.
Now we think about talentacquisition.
Speaker 2 (11:53):
That's right.
If anything, I think it justaccelerates that trend.
Speaker 1 (11:55):
Yeah, it's just like the same thing, but it's not
like pivoting.
I don't think really.
Speaker 2 (11:58):
Yeah, that's right.
Speaker 1 (11:59):
Yeah, so that'll be really interesting to see what
happens here.
But I and I think just to it'sinteresting that all this market
uncertainty and consolidationand cost scrutiny and all these
types of things is taking placealongside a lot of innovation in
the AI space, which actuallyenables companies to be a lot
more effective with their spend.
But I guess, before we get intothe company side of AI, we
(12:22):
wanted to talk about howcandidates are leveraging it and
the interview process.
Speaker 2 (12:26):
Yeah.
Speaker 1 (12:27):
So this isn't actually a side that I've done
as much research into.
I'm curious if you wouldn'tmind just sharing with me and
the audience, like what are thebiggest use cases that
candidates are leveraging for AIand they're for applying to
jobs and things like that?
Speaker 2 (12:42):
Yeah.
So the two biggest things thatI'm hearing from like the market
, from customers when I'm atconferences and things like that
talking to folks in theindustry are one some candidates
are starting to adopt toolsthat make it really easy to
apply to hundreds of roles allat the same time while still
personalizing their cover letterand their resume to the
(13:03):
opportunity, and so it'sbasically reducing the friction
dramatically to apply to roles,and we can talk about that in a
sec.
The second is I was speaking ona panel at Transform and I
think the moderator asked sowhat does everybody think about
candidates using generative AIin the hiring process, like for
actual interviews, and so Ithought that was a fascinating
(13:25):
question.
But yeah, I'm really curious toget your take on that one too,
james, in terms of yeah.
Speaker 1 (13:30):
So when they were talking about candidates using
generative AI in the interviewprocess, what were they?
Did they give any more like?
What specifically were you guystalking about there?
Speaker 2 (13:41):
Well, yeah, I think a lot of companies, so a lot of
candidates.
First of all, if they're onZoom, they're realizing they can
, like, use Gen AI to supportthemselves in the interview
process and a lot of companies.
Speaker 1 (13:52):
Yeah, I guess they just sign ChatGPT at the same
time.
Speaker 2 (13:55):
Yeah, how do you think about that?
How do you feel aboutcandidates using Cloud or
ChatGPT or something like that?
And my somewhat spicy take iswe want candidates to be AI
fluent.
Speaker 1 (14:11):
Yeah, you don't want somebody who doesn't know how to
use it, right.
Speaker 2 (14:13):
Yeah, we want them to be using AI in their jobs, and
so let's find a way for them touse AI in their interview
process.
In fact, maybe let's actuallyencourage it in certain ways.
I actually heard of this reallycool interview.
I forget which company this was.
It was one of the leading AIcompanies.
A friend of mine was on BizOps.
She's never coded in her lifeand this company said hey, use
(14:38):
GenAI to code something up.
It's like really simple, butlike just do some pair
programming with GenAI and we'lldo it with you, and I thought
that was the coolest interviewever.
She actually realized that shecould code when she had never
actually tried coding before.
Speaker 1 (14:53):
Yeah, yeah, it's pretty wild, I think, frankly,
if there is a, what comes tomind for me as an employer is
okay.
Are we going to be able totruly evaluate somebody's
skillset or are they going toget past us?
I just don't think that's thecase.
If you're interviewingcorrectly, like even if
somebody's using, I think of somany of the questions that folks
should be asking is reallyparticularly if it's a role that
(15:16):
requires experience dialinginto past experience, like
walking you through projects,specific problems, how they
overcame them.
For sales, it's talking innumbers, right, you have to be.
You can't tell you your averagedeal size and sales length and
quote attainment and can you geta reference from the previous
direct manager to back that up?
And that chat gpt is not goingto help with those types of
(15:39):
things too.
Totally.
I think, too, with behavioralquestions, you could tie
behavior into and personalityattributes into, talking about
examples in the past, right,just really dialing into their
personal experiences, I think islike personal professional
experiences, like you can stillevaluate people.
I don't think that.
I think it would be a littlebit like if somebody was using
(16:02):
Chachi PT on an interview withme, like I would.
It's not that I would beworried that I was going to hire
somebody that's not actuallyqualified, but I it would still.
Honestly, maybe for me, I don'tknow, but I feel like it's
cheating, I don't know, I justwould be like weird.
It's how, like, I'm here tohave a conversation with you.
Yeah, I think that woulddefinitely be something that I
(16:22):
would consider a yellow flag,not because, like, I don't want
people to leverage chat, gpt,but it's okay.
Look, we both know that we'retrying to have a human to human
interaction here.
I don't know, yeah, I thinkit's okay.
Look, we both know that we'retrying to have a human to human
interaction here.
I don't know yeah, I think it'sweird I think it's weird if
somebody really used chat gpt onan interview I get it.
Speaker 2 (16:38):
I get it.
But on the flip side, if wewant our employees, our people,
to be using chat, gpt or claudewhen they get hired I don't know
, it's almost tough should weallow candidates to use
generative ai as an extension oftheir brain?
Here's an interesting analogy Iwas thinking about the other
day.
How old are you, james?
Speaker 1 (16:53):
33.
Speaker 2 (16:54):
33.
All right, so this might dateme a little bit.
I'm not sure if you had thisexperience growing up In grade
school when you did researchpapers.
Do you remember having to go tothe library and get citations
for your?
Speaker 1 (17:06):
book?
Yeah, you remember that.
And did your teachers ever sayno, don't use Google, don't use
Wikipedia?
Yeah, yeah, a little bit.
Speaker 2 (17:15):
I remember that.
Do you remember that?
That memory stuck with mebecause I was like I can get
this information so much moreeasily by going to Wikipedia or
doing a Google search, yet I'mlike being forced to go to the
library, look in these cards,these physical cards, to find
the book, then open the book andtry to find the information I
need, just so that I can have anactual citation from, like, a
(17:35):
physical book, instead of usingall the information at my
fingertips on the internet.
Oh, yeah, for sure.
I think of it in a very similarway of hey, jenny, I was just
going to be an extension of, solet's face that.
Speaker 1 (17:50):
Yeah, but, like also you, if you have somebody a
question on an interview 10years ago, you wouldn't want
them to google an answer and tryto find like an article.
You just want to know, okay,what do you?
And part of it's like hey, howdo you leverage ai?
How would you leverage ai?
Speaker 2 (18:04):
but I do think there should be some level of that's a
good limit, says actually, iffor the interview, depending on.
So for the interview, if it'ssomething where you'd want them
not to Google, maybe youwouldn't want them to use Gen AI
.
But on the flip side, what isthe rationale for that?
Because on our jobs we canGoogle things.
Speaker 1 (18:24):
Yeah that's true, I think.
For me, it's like the wholereason I'm talking to somebody
is to get a better understandingof their experience and skill
set.
It's like everybody has accessto the same GTP, chat, gpt.
So it's like I want to learnabout you, not.
Speaker 2 (18:38):
The thing I liked about this interview question
that this company had designedfor that candidate is they had
actually got folks usinggenerative AI and got them to
show how they think and how theyiterate.
Oh, I like that.
I like that a lot.
I like the idea of bringingpeople in.
Speaker 1 (18:56):
Hey, can you leverage this tool to help think through
this idea or to do this codingassessment?
I think that would show howtech savvy somebody is, how well
they can understand, likeprompt engineering or creative,
adaptable, general, maybe newintelligence tests.
I think that kind of stuff isreally helpful.
That's a cool motion.
I do like that.
Speaker 2 (19:14):
Here's maybe where I think I draw the line is yeah, I
wouldn't want candidates usinggenerative AI as a way to
substitute for learning how theythink, and then maybe we just
need to reimagine the questionswe're asking that understand
really understand how candidatesthink about a problem.
Maybe the difference betweenGoogling something and
(19:36):
generative AI is can actuallyspit out some pretty reasonable
answers.
You know, thinking throughthings in a way where a
candidate could just parrot itback.
Speaker 1 (19:45):
Yeah, yeah, for sure Fascinating.
Yeah, I don't really I don'tmind.
Yeah, I definitely want peoplewho are leveraging gen ai, I
guess, on the interview.
I like the idea of it beingsome kind of like assignment or
working session.
I think that's really cool.
Um, I think I definitely wouldwant to know how they would
think about leveraging it intheir job, but again, more of
like their thought process andhow they think about leveraging
(20:08):
it and using it as an extension,as you said, to like their
brain and their thought processand behind the scenes they're
just plugging that question intogen ai and it's parroting back
here.
Speaker 2 (20:13):
Think about leveraging it and using it as an
extension, as you said, to liketheir brain and their thought
process.
And behind the scenes, they'rejust plugging that question into
Gen AI and it's parroting backhere five ways you could use it
on your job.
Speaker 1 (20:20):
Yeah, I know Exactly, it's just yeah.
But yeah, I mean, I think, likethe other thing with the
applications is, I think that'sjust going to, that's just going
to happen.
I do think that's why there's alot of value in a product like
june, like with what I'mbuilding right, because there
are the markets going to beflooded with applications that
help people apply really fastand the market's going to be
(20:42):
flooded with a lot ofapplications that are reviewing
resumes and applications anddoing that motion as well.
So it's like both.
It's like an arms race of AI.
Which system can outsmart theother?
I think to the extent therecruiting industry can get away
from keyword-based matching orsearching for unqualified talent
(21:04):
pools is really important.
I think once you have some kindof evaluation step in place
whether through a recruiter orthrough or like a tool like June
I think then that kind ofmatching motion does become a
lot more valuable because, likeone of the issues it's like with
inbounds is you can doeverything right as a sourcer or
(21:27):
a product could do everythingright.
But then my concern would justbe like, like people have a lot
of access to tools and resourcesto put together resumes, put
together like the keywords tellthe story, but it's again, it's,
and I guess people could stilleven with an evaluation.
I'll tell you what you want tohear, I just think.
I think that the idea of havingsome kind of qualification step
(21:47):
in place is really important tomake those types of things
valuable step in place is reallyimportant to make those types
of things valuable.
Speaker 2 (21:57):
Yeah, totally yeah, and I could even see yeah, yeah.
First of all, I agree the armsrace was something I was just
reflecting on and a lot ofpeople are like, oh man, I wish
folks wouldn't be using these AItools, but the fact of the
matter is they make it so easyto apply.
Like, of course, over the nextfew years, like every single
candidate is going to be usingthese tools if it helps them get
more interviews and increasestheir chances even at all.
Speaker 1 (22:18):
I think I don't have an issue with that at all.
The noise to signal ratio, like, though, is just what is the is
clearly if it benefitscompanies, because maybe there's
people that wouldn't have foundyou or didn't have time to
apply.
Speaker 2 (22:34):
That's the really interesting thing is, I do
actually think that if companiesembrace AI as well so that they
can get to the most qualifiedfolks, then it benefits both
sides, because it essentiallyenables a much more efficient
marketplace of candidate jobopportunities.
Whereas previously, a candidatemight be able to apply to I
don't know five, 10 roles a dayIf they can apply to hundreds,
(22:58):
but then the AI can bubble upthe ones that are actually a fit
.
You remove all the human manualwork from the process.
Now you've got like anefficient marketplace.
Speaker 1 (23:08):
Yeah, I have no issue with it and I think it's just.
I think it's just going to makethe market, the economy, every
company in it, just moreefficient and effective and help
companies move faster.
It's I think, it's good.
I'm looking for.
These are the types of jobs I'minterested in.
(23:33):
And then how they go out and dothe applications like why
should somebody have to do thatmanual motion of applying and
applying when you know there's agood chance?
You're not even going to hearback from the company.
Yeah, you know what I mean, soI have zero issue with that.
Speaker 2 (23:48):
And maybe for candidates, they still the short
list of companies that theyknow they're really excited
about before interviewing.
They still do themselves to puttheir best foot forward.
Then they get like a longer tailof opportunities and interviews
.
Yeah, I think maybe the placewhere I do take issue is if any
of these AI tools I'm not sureif this is the case but if
they're actually misrepresentinga candidate's experience and
(24:10):
background and just jammingkeywords in there that aren't
actually relevant to theirexperience, because then I think
it's helping no one as soon asthey go through June or like a
actual recruiter interview,hiring manager interview, like
it's going to be so easy to telland it's just going to be a
waste of time for both sidesyeah, I think it's.
Speaker 1 (24:30):
that's why it's almost like if there's going to
be automation and AI leverage onone side in order for the other
side to actually absorb thatand process, that requires AI
and automation.
Yeah, it wouldn't like, becauseif a company is getting a
thousand more applicants everyweek, or more tens of thousands,
or whatever, and they're notleveraging AI or automation,
(24:52):
like how are they supposed toget through that?
Yeah, totally it's like it hasto be.
You have to leverage it like acompany.
But the other thing like youneed is you need, like the AI
that's generating theapplications, to be factual,
yeah, I think so, and that'speople will stack in keywords
and I think one of the mostcommon ways is oh, I did this
(25:13):
once in a project or I watched ayoutube video on it and there's
that kind of stuff, and so thatstuff's going to start to
happen at scale.
So you are going to have a lotmore resumes of people that
aren't qualified, but I don'tknow what it will actually do to
the ratio.
Maybe it's still okay if, forsome kind of skilled knowledge
(25:34):
worker role, if 3% of applicants, 5% of applicants are worth
screening, if you, if folks, areusing ai automation, will that
ratio stay the same?
It's just it's going to have alot more volume.
I don't know, but I don't knowif it'll get better, if it'll
get worse in terms of the ratioof like relevancy of the
applications.
Yeah, just don't know.
But I think it's a good thinghonestly.
(25:56):
I think it's.
I think it's good I think sotoo.
Speaker 2 (25:59):
I think once both sides of the market move towards
using ai, we're actually goingto end up in a more efficient
place, surprisingly.
Speaker 1 (26:08):
Yeah, I just don't have any issue with it, and I
think companies are obviouslygoing to be doing everything to
be efficient and effective withtheir process, and I would hope
you want to hire people thatthink the same way.
You know what I mean.
As we said, you want peoplethat know how to leverage
technology typically, or in alot of roles you do Not
necessarily for every role, butat least in a lot of circles we
run in right.
(26:29):
You want people that areadaptable.
Yeah, totally.
I want to talk about Gem alittle bit.
So really just on where theproduct is today.
What's coming up?
Some new, possibly futurereleases?
What do you have coming down?
What are you currently doingand what do you have coming down
the pipe right now with June,excuse me with Jim?
Speaker 2 (26:50):
Yeah, totally Happy to talk about a whole bunch of
different products, but I thinkspecifically on the AI front,
given that we were just talkingabout that so we've built out
like a really strong matchingand ranking engine which takes
in resumes on one side and thenfive to 10 criteria that the
recruiter specifies on the otherside for a job, and then uses
(27:11):
generative AI to rank and matchand score resumes based on those
five to 10 criteria, and sowe've applied that to AI
sourcing on top of 650 millionpublic profiles.
We've also applied that to yourinbound applicants.
So to our point earlier aroundcompanies getting inundated with
applicants, folks can find theones that are most likely to be
(27:36):
the best fit much, much faster,and then potentially they could
advance those folks immediatelyto recruiter screen or even
hiring manager screen if theyscore really high, and then they
could use June for either thelong tail or the mid tail to
screen the rest.
It's a cool tie back to whatyou guys are doing.
Next up, though, we're applyingthat same matching and ranking
(27:59):
foundation to candidaterediscovery.
Speaker 1 (28:02):
It's so funny, like how I was bringing that up
earlier.
It's like that's exactly whatI'm hearing from customers and
prospects is a use case they'rereally interested in.
Speaker 2 (28:11):
Yeah so it's cool.
Speaker 1 (28:13):
Sounds like you're hearing the same or thinking the
same way about it.
Speaker 2 (28:16):
Just based on what I know about June, companies can
only interview so manycandidates, right, so they have
to pick and choose.
We help them identify the onesthat are most likely to be worth
a recruiter's time or a hiringmanager's time.
Past that you got to imaginethat if June could do interviews
for a much broader set, thatmore great people would be in
(28:38):
the mix that maybe didn't knowhow to put their best foot
forward with their resume, orwho interview better than and
actually have other skills thataren't easy to demonstrate just
from a written resume.
No, I think it was a reallycool synergy between those two.
Speaker 1 (28:54):
Let's say, I was talking with the CEO of a
company called Recruit CRM,which is oh yeah, you know them,
okay.
Speaker 2 (29:00):
Yeah, oh, no, sorry, I was thinking about a different
company, but yeah.
Speaker 1 (29:08):
Okay, yeah, recruitcrm Sean, their founder
and CEO a pretty cool story.
They actually bootstrapped andthey have hundreds of customers,
I think around a couple hundredemployees.
At this time they might evenhave a thousand customers, I'm
not sure, but they do.
It's an ATS, but it's like arecruiting automation solution
for staffing companies, and thatwas essentially like the exact
use case we talked about,potentially with a partnership
with June and RecruitCRM wasthey already have?
(29:31):
They have a kind of like anautomation AI layer to identify
profiles, right, thatspecifically for staffing of
folks that are likely to be afit, and then for June to be
like the layer underneath thatto shorten that.
But that should make it alittle bit smaller from what
they so it's.
I think that there's and then Ithink, just too, it just
(29:52):
depends on, like the industry inthe use case.
Speaker 2 (29:55):
We're just gonna have to see where it seems to fit
the best but yeah, yeah, and Ican see the same thing applying
to candidate rediscovery stuffwe're working on.
In fact, there you have evenmore candidates or folks in your
CRM that you've identified thatcould be a good fit for a role,
because you're not just limitedto the applications for a one
or two week or three week periodfor this specific job that's
(30:16):
been opened up, because you canactually look across all
previous applicants, allprevious folks in your CRM that
the recruiting team hasidentified as a good fit, and so
there the volume's even higher.
So I think the idea that folkscould use, like GEMS AI to
identify, I don't know, maybethe 10, 20 GEMS, so to speak,
(30:39):
that they want a recruiter totalk to immediately, and then
they could use June to screenhundreds to see if they're a
good fit for this new role thatjust opened up, to broaden the
pool, maybe double the amount ofqualified folks they can bring
into the pipeline by seeing amuch broader view of candidates,
sounds really interesting.
Speaker 1 (30:58):
Yeah, tna Rediscovery is really cool.
I think it's just traditionallyan area that has been somewhat
underserved in the fromrecruiting technology.
I think that there's been.
There's a lot of area for justproviding a better experience
there for recruiting tech andmore value to customers.
And it's interesting it's likefor June.
We actually have a customerthat's starting with us and I
(31:19):
guess a week from today, whothey only want to use June for
candidate rediscovery Cool.
Actually, they're not to start.
They're actually not going tobe using us for inbound
screening, screening inboundapplicants.
It's going to be what's that?
Speaker 2 (31:35):
Yeah, why not also use it for screening?
Speaker 1 (31:38):
Because they're.
So this one is a it's a staffingcompany in the GovCon federal
state and it's like clearedtalent, and so it's a limited
talent pool.
It's still big, but it's likesomewhat it's not infinite, and
they're specifically theyrecruit for engineers, right,
like a specific type of engineer, like data engineers in this
(32:00):
case, and so what they'relooking for is of course, things
change over time, so they wantJune to be able to reach out
after six months and say hey, inFebruary you spoke with Debbie
and expressed interest in X, yand Z, or had mentioned that
you're currently doing this.
How are things going?
Are you actively looking atthis point?
(32:21):
Are you still looking for thistype of role or whatever the
kind of requalification is,because, of course, data in the
system may not be currentanymore.
It's a way to re-engage withthat talent, stay close to them,
stay in front of them.
So it's like an engagement andrediscovery kind of
requalification motion which islike exactly that's the use case
(32:43):
that they're going to be usingat first.
So they want to get that outfirst.
Speaker 2 (32:46):
And when the talent pool is more narrow, then you
know, maybe they're actuallyable to interview most of the
folks that come inbound thatmatch that very narrow
qualification.
But then they've got this poolof people already in their
system that they're just notengaging with because I think so
and I think there's also likethe relationship piece.
Speaker 1 (33:03):
I think specifically like they really want to speak
with everyone, build thatrelationship off the bat and
they're like they're willing tospeak with people that aren't
qualified, like they're justlike it's worth it because they
have to get to the select fewthat are.
So I think that just theirworkflow, it makes sense for
that.
But, yeah, it was a little bitsurprising because I got on the
(33:25):
discovery and to do a demo and Iwas ready to.
Of course, we bring uprediscovery, but I was also
expecting to talk about inboundand the CEO's.
Just no, I want to.
This is what we need.
We need rediscovery, we need tore-engage, we need to stay in
front of them consistently.
There's sometimes you speak tosomebody we may not place them
until two years later and I needa consistent way to engage with
(33:46):
them, to stay up to date withwhat they're doing, what they're
looking for and to remind themabout us.
Right, that's essentially whatthey're looking for.
Speaker 2 (33:54):
Cool good stuff.
Speaker 1 (33:55):
Yeah, yeah, I think Rediscovery is a really cool one
.
I think that's again.
Speaker 2 (34:10):
I think there's a lot of opportunity there for
companies.
Yeah, me too.
That's just a goldmine If I canput some stats behind that.
We definitely serve a decentnumber of staffing agencies.
A lot of our customers arein-house.
For in-house customers acrossthe board, 30 to 50% of folks
that are hired already existedin your CRM or ATS before you
hire them.
And then for enterprisecustomers, it's something like
60, 70% of the larger ones and,yeah, that's a goldmine.
But when you think about, like,how folks are actually entering
(34:32):
process, it's in reallyinefficient ways.
It's people going out and coldsourcing them again, or
companies running like Just soexpensive.
Right, yeah, you're buildingpipeline and 60, 70% of them, if
you're an enterprise customer,are already people that you have
relationships with, but you'repaying all over again to build
(34:52):
those pipes.
Speaker 1 (34:54):
Yeah, that's the whole thing.
One of the reasons of many thatI really like the idea of
optimizing inbound and kind ofrediscovery is because outbound
motions can be very expensivefrom a headcount perspective and
they're important and they'restill like probably the most I
would say for specifically forknowledge workers and specific
profiles.
I would say you need anoutbound motion right like at
(35:16):
secure vision.
Most of the hires we help ourcustomers with are still
outbound outbound sourcing butnonetheless that's because we
there hasn't been tech.
I think that has reallyoptimized inbound and
rediscovery very well.
There's just been gaps in thetechnology and I think that
those things are now like moreproducts are coming out to
(35:37):
essentially increasecontribution to hiring from
inbound, increase contributionto hiring from rediscovery and
make that a more significant ROImotion and that should help at
least balance out the cost wherethe sourcing efforts it's going
to cost more but you can bereally dialed in and get those
new profiles.
And that's really, if you'repaying a senior recruiter and a
(35:59):
recruiting tech stack foroutbound, which is expensive,
more expensive, like you shouldhave them laser focused on
building those net newrelationships, right.
Speaker 2 (36:09):
Yeah, exactly, you don't want them like exactly
reinventing the wheel with folksthat you already know about.
Same for inbound like companiesspend millions of dollars on
like job advertising and 60 70%of the people they hire are
people that are already in theirdatabase yeah, that's true no,
I think it applies to both.
It just across the board, likethe top of the funnel, is quite
(36:33):
expensive.
So if you can augment that withpeople you already know about,
no brainer yeah, yeah.
Speaker 1 (36:42):
Just one quick question on the rediscovery
motion that you're building out.
Essentially, it's going in andyou're able to search for folks
that match based on theirscreening interviews or their
resumes, or is it like acombination?
How is GEMS surfacing thecandidates that are the best for
a role?
Speaker 2 (37:00):
Yeah, so it's two things.
One is, on top of the resume,we'll use that same ranking and
matching engine and help youfind folks that best match those
five to 10 criteria that, likethe recruiter or hiring manager,
is defined for that job, andI'll look across your entire ATS
and CRM database for folks thatare the highest match.
(37:20):
But then on top of that, youcan also add some smart filters
so you can filter out folksbased on, like, how far they got
in the interview process, whatthe blend of scorecards was.
Speaker 1 (37:30):
Oh, okay, yeah, that's really cool.
Speaker 2 (37:32):
Yeah, folks out based on have you had a touchpoint
with them in the last three tosix months or were they rejected
within the last year?
A lot of the really commonrules of engagement that
companies might have about, likewhen they want to re-interview
folks.
And because GEM is anall-in-one recruiting platform
that covers sourcing, CRM,scheduling, even like talent
(37:56):
marketing capabilities, ATS likewe've got the most complete
source of truth for all thosedifferent touch points that you
can put on top of.
Speaker 1 (38:03):
Yeah, for sure it all , yeah, it's integrated, all
tied together.
Yeah, that's awesome, man.
Yeah, I got to get my hands onmore of the products that you
have right now Still using.
We're on the sourcing productof building cadences and
outreach campaigns, which is, Ithink, you're running butter at
least it was back in the day soit's the primary product and, of
course, grown so much sincethen.
Speaker 2 (38:24):
Yeah, let's get you set up on it, James.
I'd love to get you guys thefull, the full power of Jam all
in one.
Speaker 1 (38:30):
Yeah, we got to do it , man.
I actually have been meaning totalk to you about that, because
I'd rather, I just I do want todo everything through through
Jam at this point, just based onwhat you're building.
It's just.
It would make things a loteasier for us too.
Speaker 2 (38:41):
You got it.
I feel like we've had a reallyproductive pod.
We've we've figured outpotential partnership
opportunities between you andJem.
Yeah, yeah, we're going to getyou on to Jem all in one.
Let's do it, yeah.
Speaker 1 (38:52):
Hell yeah, man.
Yeah, as always, it's a.
It's been a lot of fun.
Thank you for joining us todayand sharing your insights, and I
always enjoy these episodes alot.
I'm happy we get to do them ona regular basis.
Hello, welcome to the Breakthrough Hiring Show.
I'm your host, James Mackey.
We got Steve Bartell back withus today.
Steve, what's going on?
Speaker 2 (00:06):
Hey, good to be here.
Speaker 1 (00:09):
And for everybody tuning in that hasn't heard one
of Steve's past episodes Steve,would you mind just doing a
quick introduction on yourself?
Speaker 2 (00:17):
Yeah, sure, I'm Steve .
I'm the co-founder and CEO atGEM.
I've been building G Gem forabout eight years.
At Gem, we're building the onlyAI-first all-in-one recruiting
platform.
So what that means is we takeyour sourcing, your CRM, your
ATS scheduling, plus full funnelanalytics and a database of 650
(00:41):
million public profiles thatyou can source from and then
thread AI through the entireproduct.
But yeah, that's what we're upto Over to you, james.
Speaker 1 (00:50):
Cool.
Today.
We have, I think, a veryaction-packed episode.
A lot of stuff to cover Beforewe get into some really cool
things regarding AI howcandidates are leveraging it in
the interview process and whatthat's going to look like as
candidates are, companies areleveraging it and then get into
(01:11):
that.
We also discussed talking alittle bit about what you're up
to at Jim, some of the morerecent product and feature
releases.
We want to talk a little bitabout candidate rediscovery,
which I think would be reallyinteresting as well, and making
that whole process a lot moreeffective and valuable to
organizations.
I think there's a lot left onthe table when it comes to
(01:32):
rediscovery, so that'll be coolto dive into that as well.
Speaker 2 (01:37):
Sounds good, let's do it.
Speaker 1 (01:38):
Yeah, so let's just start out with the market.
Last thing I checked, as of anhour ago, I think, trump's
threatening it like anadditional 50 percent tariff on
China due to the fact that theyput out reciprocal tariffs of 34
, 36 percent or whatever it is.
Of course we saw a massivemarket contraction and then
within that like tech, of course, being one of the most volatile
sectors, I think the wholemarket was down like five
(02:00):
percent ish.
Don't quote me, but it's likebasically.
And then I think tech was atleast temporarily down closer to
12 last week or something crazylike that, if I remember
correctly in the journal.
So I'm sure hopefully, maybesome of that's just like
temporary, just shock right tothe market and tariffs.
But it's definitely a reallyuncertain time right now.
And I'm curious if you'rehearing anything from customers.
(02:22):
I know like we have earlyearnings call coming out,
probably in a few weeks.
Ceos are going to be talking,but just, is there any kind of
word on the street, jim,customers, or your advisors or
VCs, or what are you hearing outthere?
Speaker 2 (02:35):
Yeah, totally so.
First of all, I think it'sreally hard to know how this
stuff shakes out.
I do think that the marketcorrection has probably been an
overcorrection.
When you think about theoverall GDP of the US,
interestingly, we're a veryheavy services country as it
relates to GDP.
I think 70% of our GDP is fromservices industry and I think
(02:59):
only 10%, 20% or something likethat is from trade, and a lot of
that is actually between Canadaand Mexico and the US, and so
when you take that factor out,it's even less.
And so when you think about themarket correction, that's
happened.
What did you say?
10, 12% or something like thatIn?
Speaker 1 (03:19):
tech.
I think I saw that Like it wasone of the hard graph things.
Speaker 2 (03:21):
I think the overall market lost like 5% and wiped
out like 6 trillion ish orsomething in market value and so
I think that's like anovercorrection, because when you
just do the simple math on thisstuff, tariffs aren't gonna
reduce that gdp down to zero oreven half of what it is.
They're gonna add some friction.
(03:42):
But so, first of all, I thinkit's, I think it's like an
overcorrection.
The second thing is it's reallyhard to know how this stuff is
going to shake out, because alot of people believe that the
administration is doing this toset them up for like
negotiations.
Yeah, there's a lot of likeimbalance in terms of how
tariffs work when you lookacross different countries, and
(04:04):
actually a lot of the tariffsout there are pretty unfair to
the US, in the sense that the UShas a much lower tariff on
these countries than they haveon us when they're importing our
goods, and so a lot of peoplethink these across-the-board
tariffs are just to get peopleto the negotiating table to
negotiate tariffs that are morereciprocal across the board.
(04:25):
It's really hard to say howthis stuff's going to shake out
until another few weeks or amonth or a few months pass and
we can actually see what's thestrategy behind this and does it
work or does?
Speaker 1 (04:38):
it not?
Yeah, it's interesting becauseyou're right, like it could be
temporary.
But I'm wondering, like it isto some extent the we did this
once before the united states.
It was like in it was a reallylong time ago.
The president called I think itwas like mckinsey, I would have
to or I'd have to go doublecheck.
But there was one time maybenot mckinsey I'll have to go
back and double check and I'llput it in the notes of the
(04:59):
episode.
Cool, I forget his name, Ithink it was that.
But he did a tariff strategywhere essentially the United
States was in a lot of debt andimplemented a tariff strategy
and back in the day beforeincome tax, that's actually how
the government collected.
A lot of income was throughtariffs and then, as essentially
we implemented the income tax,tariffs went down, income tax
(05:20):
went up and that is essentiallymodern day United States.
That's how we collect, thegovernment collects.
The revenue is income tax.
So this has been done before inthe past and it actually did
take the country from being in asignificant amount of debt to a
surplus and to a point whereit's like almost like you don't
necessarily want a country to bein too big of a surplus,
(05:42):
because what are they doing withthat money?
Right, like the money should be, you should be taxing just
enough to essentially providewhat you need to.
So you don't necessarily want asurplus, but you definitely
don't want the debt that we havenow, and so back in the day,
when they did this, it did work,but then, essentially in the
second term, this president didaway with it.
It was no longer working, butthese things are so complicated.
(06:05):
From what I was researchinginto it, it really wasn't clear
if it wasn't working becausethey were at a surplus and it
just changed the market dynamicsand it just wasn't valuable
anymore.
It was just hurting them orsomething else.
The thing is, though, againthis happened.
This was over 100 years ago.
The economy is obviouslycompletely different these days.
(06:25):
There's a lot more tradeoccurring, even if it's a
minority of our GDP, and thenthere's a connectivity of
globalization and otherindustries or, excuse me,
countries I don't know thepercentage of GDP for them and
then there's the whole.
There's so much of the marketon confidence, right, and if
people pause spending even more,how that could impact things.
(06:48):
And then, even short term, ifMexico, canada, prices are
increased on, goods become moreexpensive for Americans if that
heats up inflation.
I'm not an economist, but I'mjust wondering does that just
stop when you lower the tariffs?
You know what I mean.
No, it's a really interestingquestion.
Speaker 2 (07:06):
I think these things are super complex and that's why
there's not a clear-cut answerto foreign policy or tariffs and
stuff like that, and somethingthat happened 100 years ago
might not play out the same waytoday, like you mentioned.
And so I think all of this isto say people are feeling a lot
of uncertainty right now to youroriginal question, because it's
really hard to know how thisstuff shakes out and it's still
(07:28):
early days.
We're trying to keep a pulse onthis with our customers and
then also our prospects folksthat are considering looking at
JEM.
Whenever we see uncertainty wethink all right, how can we best
serve our customers?
How can we best serveprospective buyers who might be
(07:49):
thinking about Gem?
And the good news is we've beenthrough a few of these cycles
as an industry and so we'velearned a lot.
We've learned that when there'smore uncertainty in the market
or when companies are reallyslowing down down hiring, that
there's a much stronger need forlower cost all-in-one
consolidation.
They can save companies money,also help unify their stack.
(08:14):
There's a lot of benefits tohaving everything under one roof
, and we've even come up withsome pretty creative ways for
companies that wanna embark onthis longer term journey of
moving towards all in one to getstarted today with a nominal
amount of spend and then onlystart paying us as, like, their
different renewals come up forthe pieces that are on their
(08:38):
current stack and in this way,people can benefit from having
the all in one platformoneplatform out of the gate, but
like never be double paying forthe different line items that
they already have.
So that's not how we thinkabout it.
Internally is like how can webest serve our customers and the
market when there's a lot ofuncertainty, because no one
wants to be the last thingsomebody wants to be doing is
(08:58):
double paying for tools whenthey're headed into a lot of
uncertainty.
Speaker 1 (09:03):
Yeah, it's definitely for sure.
By the way, I just fact-checkedmyself.
I don't.
I think I saw McKinsey.
I was thinking the consultingfirm was saying McKinley, ah
yeah, 1890s, and he was a hugeadvocate of tariffs.
So I recommend people look itup.
It's really, it is fascinating.
I've wrapped my head around it,I think, as much as I have time
for interesting stuff and yeah,yeah, for sure.
(09:24):
It's getting to terms like oh,that's like a simple thing,
right, like it's prettystraightforward, and then it
turns out no, not really, butbut yeah, in terms of how I'm.
I think people are thinkingabout the market right now is
people are a lot of.
I think a lot of folks are in aholding pattern, right,
particularly in in theindustries that are directly
affected, in fact, likemanufacturing, for instance but
not just going out like, hey,let's open up plants.
(09:45):
That's like a massive, multi,multi, multi million dollar
endeavor that takes one to threeyears to even get them
productive.
So, yeah, but it's kind of okay, we just have to, we just have
to wait.
Nobody really knows, and Ithink it's just it.
Just for me, it's like I runtwo, two companies I have a
recruiting services company andI have the software company June
(10:06):
for Secure Vision it's.
I don't really know how it'sgoing to impact us.
I can say right now, ourcustomers with different
industries really nobody.
The only customers of companiesthat are pausing and not making
decisions are reallymanufacturing supply chain, like
they're at a standstill, likeany kind of deals and pipeline
related to that they're notconsidering, they're just not
(10:28):
moving forward.
But you know, in otherindustries it's essentially it's
weird, it's like business asusual, almost, despite all of
this stuff happening in thebackground.
So I guess that's good, right.
And I think, though, like, interms of customers thinking
about, like spending all in one,that's still been the trend for
the past few years, right, Ithink that in the markets going
(10:51):
into that direction andconsolidation, which is, I think
, it's a good thing, so, from afor customers.
I think that they still wantcompanies still want that.
When it comes to hiring and techstacks consolidation, I think
also this idea of being able toaccess gym, like different
products, like just to getonboarded yeah, started to start
(11:13):
adding value, pull up, givethem help, help them where they
need it and then transition theminto a full stack or a full
product suite customer yeah,definitely the way to go,
because I think folks are likelooking for all-in-one, they're
looking for flexibility, butthis is a macro trend,
regardless of what happens right, even if autonomy gets hit mid
(11:35):
to long term because of this, itreally doesn't change.
I don't think too much howcompanies are going to think
about hiring or particularly thetechnology that they're going
to be using.
If anything, it's just furtherreinforcement that we need to
optimize tech and be very leanas an organization.
Now we think about talentacquisition.
Speaker 2 (11:53):
That's right.
If anything, I think it justaccelerates that trend.
Speaker 1 (11:55):
Yeah, it's just like the same thing, but it's not
like pivoting.
I don't think really.
Speaker 2 (11:58):
Yeah, that's right.
Speaker 1 (11:59):
Yeah, so that'll be really interesting to see what
happens here.
But I and I think just to it'sinteresting that all this market
uncertainty and consolidationand cost scrutiny and all these
types of things is taking placealongside a lot of innovation in
the AI space, which actuallyenables companies to be a lot
more effective with their spend.
But I guess, before we get intothe company side of AI, we
(12:22):
wanted to talk about howcandidates are leveraging it and
the interview process.
Speaker 2 (12:26):
Yeah.
Speaker 1 (12:27):
So this isn't actually a side that I've done
as much research into.
I'm curious if you wouldn'tmind just sharing with me and
the audience, like what are thebiggest use cases that
candidates are leveraging for AIand they're for applying to
jobs and things like that?
Speaker 2 (12:42):
Yeah.
So the two biggest things thatI'm hearing from like the market
, from customers when I'm atconferences and things like that
talking to folks in theindustry are one some candidates
are starting to adopt toolsthat make it really easy to
apply to hundreds of roles allat the same time while still
personalizing their cover letterand their resume to the
(13:03):
opportunity, and so it'sbasically reducing the friction
dramatically to apply to roles,and we can talk about that in a
sec.
The second is I was speaking ona panel at Transform and I
think the moderator asked sowhat does everybody think about
candidates using generative AIin the hiring process, like for
actual interviews, and so Ithought that was a fascinating
(13:25):
question.
But yeah, I'm really curious toget your take on that one too,
james, in terms of yeah.
Speaker 1 (13:30):
So when they were talking about candidates using
generative AI in the interviewprocess, what were they?
Did they give any more like?
What specifically were you guystalking about there?
Speaker 2 (13:41):
Well, yeah, I think a lot of companies, so a lot of
candidates.
First of all, if they're onZoom, they're realizing they can
, like, use Gen AI to supportthemselves in the interview
process and a lot of companies.
Speaker 1 (13:52):
Yeah, I guess they just sign ChatGPT at the same
time.
Speaker 2 (13:55):
Yeah, how do you think about that?
How do you feel aboutcandidates using Cloud or
ChatGPT or something like that?
And my somewhat spicy take iswe want candidates to be AI
fluent.
Speaker 1 (14:11):
Yeah, you don't want somebody who doesn't know how to
use it, right.
Speaker 2 (14:13):
Yeah, we want them to be using AI in their jobs, and
so let's find a way for them touse AI in their interview
process.
In fact, maybe let's actuallyencourage it in certain ways.
I actually heard of this reallycool interview.
I forget which company this was.
It was one of the leading AIcompanies.
A friend of mine was on BizOps.
She's never coded in her lifeand this company said hey, use
(14:38):
GenAI to code something up.
It's like really simple, butlike just do some pair
programming with GenAI and we'lldo it with you, and I thought
that was the coolest interviewever.
She actually realized that shecould code when she had never
actually tried coding before.
Speaker 1 (14:53):
Yeah, yeah, it's pretty wild, I think, frankly,
if there is a, what comes tomind for me as an employer is
okay.
Are we going to be able totruly evaluate somebody's
skillset or are they going toget past us?
I just don't think that's thecase.
If you're interviewingcorrectly, like even if
somebody's using, I think of somany of the questions that folks
should be asking is reallyparticularly if it's a role that
(15:16):
requires experience dialinginto past experience, like
walking you through projects,specific problems, how they
overcame them.
For sales, it's talking innumbers, right, you have to be.
You can't tell you your averagedeal size and sales length and
quote attainment and can you geta reference from the previous
direct manager to back that up?
And that chat gpt is not goingto help with those types of
(15:39):
things too.
Totally.
I think, too, with behavioralquestions, you could tie
behavior into and personalityattributes into, talking about
examples in the past, right,just really dialing into their
personal experiences, I think islike personal professional
experiences, like you can stillevaluate people.
I don't think that.
I think it would be a littlebit like if somebody was using
(16:02):
Chachi PT on an interview withme, like I would.
It's not that I would beworried that I was going to hire
somebody that's not actuallyqualified, but I it would still.
Honestly, maybe for me, I don'tknow, but I feel like it's
cheating, I don't know, I justwould be like weird.
It's how, like, I'm here tohave a conversation with you.
Yeah, I think that woulddefinitely be something that I
(16:22):
would consider a yellow flag,not because, like, I don't want
people to leverage chat, gpt,but it's okay.
Look, we both know that we'retrying to have a human to human
interaction here.
I don't know, yeah, I thinkit's okay.
Look, we both know that we'retrying to have a human to human
interaction here.
I don't know yeah, I think it'sweird I think it's weird if
somebody really used chat gpt onan interview I get it.
Speaker 2 (16:38):
I get it.
But on the flip side, if wewant our employees, our people,
to be using chat, gpt or claudewhen they get hired I don't know
, it's almost tough should weallow candidates to use
generative ai as an extension oftheir brain?
Here's an interesting analogy Iwas thinking about the other
day.
How old are you, james?
Speaker 1 (16:53):
33.
Speaker 2 (16:54):
33.
All right, so this might dateme a little bit.
I'm not sure if you had thisexperience growing up In grade
school when you did researchpapers.
Do you remember having to go tothe library and get citations
for your?
Speaker 1 (17:06):
book?
Yeah, you remember that.
And did your teachers ever sayno, don't use Google, don't use
Wikipedia?
Yeah, yeah, a little bit.
Speaker 2 (17:15):
I remember that.
Do you remember that?
That memory stuck with mebecause I was like I can get
this information so much moreeasily by going to Wikipedia or
doing a Google search, yet I'mlike being forced to go to the
library, look in these cards,these physical cards, to find
the book, then open the book andtry to find the information I
need, just so that I can have anactual citation from, like, a
(17:35):
physical book, instead of usingall the information at my
fingertips on the internet.
Oh, yeah, for sure.
I think of it in a very similarway of hey, jenny, I was just
going to be an extension of, solet's face that.
Speaker 1 (17:50):
Yeah, but, like also you, if you have somebody a
question on an interview 10years ago, you wouldn't want
them to google an answer and tryto find like an article.
You just want to know, okay,what do you?
And part of it's like hey, howdo you leverage ai?
How would you leverage ai?
Speaker 2 (18:04):
but I do think there should be some level of that's a
good limit, says actually, iffor the interview, depending on.
So for the interview, if it'ssomething where you'd want them
not to Google, maybe youwouldn't want them to use Gen AI
.
But on the flip side, what isthe rationale for that?
Because on our jobs we canGoogle things.
Speaker 1 (18:24):
Yeah that's true, I think.
For me, it's like the wholereason I'm talking to somebody
is to get a better understandingof their experience and skill
set.
It's like everybody has accessto the same GTP, chat, gpt.
So it's like I want to learnabout you, not.
Speaker 2 (18:38):
The thing I liked about this interview question
that this company had designedfor that candidate is they had
actually got folks usinggenerative AI and got them to
show how they think and how theyiterate.
Oh, I like that.
I like that a lot.
I like the idea of bringingpeople in.
Speaker 1 (18:56):
Hey, can you leverage this tool to help think through
this idea or to do this codingassessment?
I think that would show howtech savvy somebody is, how well
they can understand, likeprompt engineering or creative,
adaptable, general, maybe newintelligence tests.
I think that kind of stuff isreally helpful.
That's a cool motion.
I do like that.
Speaker 2 (19:14):
Here's maybe where I think I draw the line is yeah, I
wouldn't want candidates usinggenerative AI as a way to
substitute for learning how theythink, and then maybe we just
need to reimagine the questionswe're asking that understand
really understand how candidatesthink about a problem.
Maybe the difference betweenGoogling something and
(19:36):
generative AI is can actuallyspit out some pretty reasonable
answers.
You know, thinking throughthings in a way where a
candidate could just parrot itback.
Speaker 1 (19:45):
Yeah, yeah, for sure Fascinating.
Yeah, I don't really I don'tmind.
Yeah, I definitely want peoplewho are leveraging gen ai, I
guess, on the interview.
I like the idea of it beingsome kind of like assignment or
working session.
I think that's really cool.
Um, I think I definitely wouldwant to know how they would
think about leveraging it intheir job, but again, more of
like their thought process andhow they think about leveraging
(20:08):
it and using it as an extension,as you said, to like their
brain and their thought processand behind the scenes they're
just plugging that question intogen ai and it's parroting back
here.
Speaker 2 (20:13):
Think about leveraging it and using it as an
extension, as you said, to liketheir brain and their thought
process.
And behind the scenes, they'rejust plugging that question into
Gen AI and it's parroting backhere five ways you could use it
on your job.
Speaker 1 (20:20):
Yeah, I know Exactly, it's just yeah.
But yeah, I mean, I think, likethe other thing with the
applications is, I think that'sjust going to, that's just going
to happen.
I do think that's why there's alot of value in a product like
june, like with what I'mbuilding right, because there
are the markets going to beflooded with applications that
help people apply really fastand the market's going to be
(20:42):
flooded with a lot ofapplications that are reviewing
resumes and applications anddoing that motion as well.
So it's like both.
It's like an arms race of AI.
Which system can outsmart theother?
I think to the extent therecruiting industry can get away
from keyword-based matching orsearching for unqualified talent
(21:04):
pools is really important.
I think once you have some kindof evaluation step in place
whether through a recruiter orthrough or like a tool like June
I think then that kind ofmatching motion does become a
lot more valuable because, likeone of the issues it's like with
inbounds is you can doeverything right as a sourcer or
(21:27):
a product could do everythingright.
But then my concern would justbe like, like people have a lot
of access to tools and resourcesto put together resumes, put
together like the keywords tellthe story, but it's again, it's,
and I guess people could stilleven with an evaluation.
I'll tell you what you want tohear, I just think.
I think that the idea of havingsome kind of qualification step
(21:47):
in place is really important tomake those types of things
valuable step in place is reallyimportant to make those types
of things valuable.
Speaker 2 (21:57):
Yeah, totally yeah, and I could even see yeah, yeah.
First of all, I agree the armsrace was something I was just
reflecting on and a lot ofpeople are like, oh man, I wish
folks wouldn't be using these AItools, but the fact of the
matter is they make it so easyto apply.
Like, of course, over the nextfew years, like every single
candidate is going to be usingthese tools if it helps them get
more interviews and increasestheir chances even at all.
Speaker 1 (22:18):
I think I don't have an issue with that at all.
The noise to signal ratio, like, though, is just what is the is
clearly if it benefitscompanies, because maybe there's
people that wouldn't have foundyou or didn't have time to
apply.
Speaker 2 (22:34):
That's the really interesting thing is, I do
actually think that if companiesembrace AI as well so that they
can get to the most qualifiedfolks, then it benefits both
sides, because it essentiallyenables a much more efficient
marketplace of candidate jobopportunities.
Whereas previously, a candidatemight be able to apply to I
don't know five, 10 roles a dayIf they can apply to hundreds,
(22:58):
but then the AI can bubble upthe ones that are actually a fit
.
You remove all the human manualwork from the process.
Now you've got like anefficient marketplace.
Speaker 1 (23:08):
Yeah, I have no issue with it and I think it's just.
I think it's just going to makethe market, the economy, every
company in it, just moreefficient and effective and help
companies move faster.
It's I think, it's good.
I'm looking for.
These are the types of jobs I'minterested in.
(23:33):
And then how they go out and dothe applications like why
should somebody have to do thatmanual motion of applying and
applying when you know there's agood chance?
You're not even going to hearback from the company.
Yeah, you know what I mean, soI have zero issue with that.
Speaker 2 (23:48):
And maybe for candidates, they still the short
list of companies that theyknow they're really excited
about before interviewing.
They still do themselves to puttheir best foot forward.
Then they get like a longer tailof opportunities and interviews
.
Yeah, I think maybe the placewhere I do take issue is if any
of these AI tools I'm not sureif this is the case but if
they're actually misrepresentinga candidate's experience and
(24:10):
background and just jammingkeywords in there that aren't
actually relevant to theirexperience, because then I think
it's helping no one as soon asthey go through June or like a
actual recruiter interview,hiring manager interview, like
it's going to be so easy to telland it's just going to be a
waste of time for both sidesyeah, I think it's.
Speaker 1 (24:30):
that's why it's almost like if there's going to
be automation and AI leverage onone side in order for the other
side to actually absorb thatand process, that requires AI
and automation.
Yeah, it wouldn't like, becauseif a company is getting a
thousand more applicants everyweek, or more tens of thousands,
or whatever, and they're notleveraging AI or automation,
(24:52):
like how are they supposed toget through that?
Yeah, totally it's like it hasto be.
You have to leverage it like acompany.
But the other thing like youneed is you need, like the AI
that's generating theapplications, to be factual,
yeah, I think so, and that'speople will stack in keywords
and I think one of the mostcommon ways is oh, I did this
(25:13):
once in a project or I watched ayoutube video on it and there's
that kind of stuff, and so thatstuff's going to start to
happen at scale.
So you are going to have a lotmore resumes of people that
aren't qualified, but I don'tknow what it will actually do to
the ratio.
Maybe it's still okay if, forsome kind of skilled knowledge
(25:34):
worker role, if 3% of applicants, 5% of applicants are worth
screening, if you, if folks, areusing ai automation, will that
ratio stay the same?
It's just it's going to have alot more volume.
I don't know, but I don't knowif it'll get better, if it'll
get worse in terms of the ratioof like relevancy of the
applications.
Yeah, just don't know.
But I think it's a good thinghonestly.
(25:56):
I think it's.
I think it's good I think sotoo.
Speaker 2 (25:59):
I think once both sides of the market move towards
using ai, we're actually goingto end up in a more efficient
place, surprisingly.
Speaker 1 (26:08):
Yeah, I just don't have any issue with it, and I
think companies are obviouslygoing to be doing everything to
be efficient and effective withtheir process, and I would hope
you want to hire people thatthink the same way.
You know what I mean.
As we said, you want peoplethat know how to leverage
technology typically, or in alot of roles you do Not
necessarily for every role, butat least in a lot of circles we
run in right.
(26:29):
You want people that areadaptable.
Yeah, totally.
I want to talk about Gem alittle bit.
So really just on where theproduct is today.
What's coming up?
Some new, possibly futurereleases?
What do you have coming down?
What are you currently doingand what do you have coming down
the pipe right now with June,excuse me with Jim?
Speaker 2 (26:50):
Yeah, totally Happy to talk about a whole bunch of
different products, but I thinkspecifically on the AI front,
given that we were just talkingabout that so we've built out
like a really strong matchingand ranking engine which takes
in resumes on one side and thenfive to 10 criteria that the
recruiter specifies on the otherside for a job, and then uses
(27:11):
generative AI to rank and matchand score resumes based on those
five to 10 criteria, and sowe've applied that to AI
sourcing on top of 650 millionpublic profiles.
We've also applied that to yourinbound applicants.
So to our point earlier aroundcompanies getting inundated with
applicants, folks can find theones that are most likely to be
(27:36):
the best fit much, much faster,and then potentially they could
advance those folks immediatelyto recruiter screen or even
hiring manager screen if theyscore really high, and then they
could use June for either thelong tail or the mid tail to
screen the rest.
It's a cool tie back to whatyou guys are doing.
Next up, though, we're applyingthat same matching and ranking
(27:59):
foundation to candidaterediscovery.
Speaker 1 (28:02):
It's so funny, like how I was bringing that up
earlier.
It's like that's exactly whatI'm hearing from customers and
prospects is a use case they'rereally interested in.
Speaker 2 (28:11):
Yeah so it's cool.
Speaker 1 (28:13):
Sounds like you're hearing the same or thinking the
same way about it.
Speaker 2 (28:16):
Just based on what I know about June, companies can
only interview so manycandidates, right, so they have
to pick and choose.
We help them identify the onesthat are most likely to be worth
a recruiter's time or a hiringmanager's time.
Past that you got to imaginethat if June could do interviews
for a much broader set, thatmore great people would be in
(28:38):
the mix that maybe didn't knowhow to put their best foot
forward with their resume, orwho interview better than and
actually have other skills thataren't easy to demonstrate just
from a written resume.
No, I think it was a reallycool synergy between those two.
Speaker 1 (28:54):
Let's say, I was talking with the CEO of a
company called Recruit CRM,which is oh yeah, you know them,
okay.
Speaker 2 (29:00):
Yeah, oh, no, sorry, I was thinking about a different
company, but yeah.
Speaker 1 (29:08):
Okay, yeah, recruitcrm Sean, their founder
and CEO a pretty cool story.
They actually bootstrapped andthey have hundreds of customers,
I think around a couple hundredemployees.
At this time they might evenhave a thousand customers, I'm
not sure, but they do.
It's an ATS, but it's like arecruiting automation solution
for staffing companies, and thatwas essentially like the exact
use case we talked about,potentially with a partnership
with June and RecruitCRM wasthey already have?
(29:31):
They have a kind of like anautomation AI layer to identify
profiles, right, thatspecifically for staffing of
folks that are likely to be afit, and then for June to be
like the layer underneath thatto shorten that.
But that should make it alittle bit smaller from what
they so it's.
I think that there's and then Ithink, just too, it just
(29:52):
depends on, like the industry inthe use case.
Speaker 2 (29:55):
We're just gonna have to see where it seems to fit
the best but yeah, yeah, and Ican see the same thing applying
to candidate rediscovery stuffwe're working on.
In fact, there you have evenmore candidates or folks in your
CRM that you've identified thatcould be a good fit for a role,
because you're not just limitedto the applications for a one
or two week or three week periodfor this specific job that's
(30:16):
been opened up, because you canactually look across all
previous applicants, allprevious folks in your CRM that
the recruiting team hasidentified as a good fit, and so
there the volume's even higher.
So I think the idea that folkscould use, like GEMS AI to
identify, I don't know, maybethe 10, 20 GEMS, so to speak,
(30:39):
that they want a recruiter totalk to immediately, and then
they could use June to screenhundreds to see if they're a
good fit for this new role thatjust opened up, to broaden the
pool, maybe double the amount ofqualified folks they can bring
into the pipeline by seeing amuch broader view of candidates,
sounds really interesting.
Speaker 1 (30:58):
Yeah, tna Rediscovery is really cool.
I think it's just traditionallyan area that has been somewhat
underserved in the fromrecruiting technology.
I think that there's been.
There's a lot of area for justproviding a better experience
there for recruiting tech andmore value to customers.
And it's interesting it's likefor June.
We actually have a customerthat's starting with us and I
(31:19):
guess a week from today, whothey only want to use June for
candidate rediscovery Cool.
Actually, they're not to start.
They're actually not going tobe using us for inbound
screening, screening inboundapplicants.
It's going to be what's that?
Speaker 2 (31:35):
Yeah, why not also use it for screening?
Speaker 1 (31:38):
Because they're.
So this one is a it's a staffingcompany in the GovCon federal
state and it's like clearedtalent, and so it's a limited
talent pool.
It's still big, but it's likesomewhat it's not infinite, and
they're specifically theyrecruit for engineers, right,
like a specific type of engineer, like data engineers in this
(32:00):
case, and so what they'relooking for is of course, things
change over time, so they wantJune to be able to reach out
after six months and say hey, inFebruary you spoke with Debbie
and expressed interest in X, yand Z, or had mentioned that
you're currently doing this.
How are things going?
Are you actively looking atthis point?
(32:21):
Are you still looking for thistype of role or whatever the
kind of requalification is,because, of course, data in the
system may not be currentanymore.
It's a way to re-engage withthat talent, stay close to them,
stay in front of them.
So it's like an engagement andrediscovery kind of
requalification motion which islike exactly that's the use case
(32:43):
that they're going to be usingat first.
So they want to get that outfirst.
Speaker 2 (32:46):
And when the talent pool is more narrow, then you
know, maybe they're actuallyable to interview most of the
folks that come inbound thatmatch that very narrow
qualification.
But then they've got this poolof people already in their
system that they're just notengaging with because I think so
and I think there's also likethe relationship piece.
Speaker 1 (33:03):
I think specifically like they really want to speak
with everyone, build thatrelationship off the bat and
they're like they're willing tospeak with people that aren't
qualified, like they're justlike it's worth it because they
have to get to the select fewthat are.
So I think that just theirworkflow, it makes sense for
that.
But, yeah, it was a little bitsurprising because I got on the
(33:25):
discovery and to do a demo and Iwas ready to.
Of course, we bring uprediscovery, but I was also
expecting to talk about inboundand the CEO's.
Just no, I want to.
This is what we need.
We need rediscovery, we need tore-engage, we need to stay in
front of them consistently.
There's sometimes you speak tosomebody we may not place them
until two years later and I needa consistent way to engage with
(33:46):
them, to stay up to date withwhat they're doing, what they're
looking for and to remind themabout us.
Right, that's essentially whatthey're looking for.
Speaker 2 (33:54):
Cool good stuff.
Speaker 1 (33:55):
Yeah, yeah, I think Rediscovery is a really cool one
.
I think that's again.
Speaker 2 (34:10):
I think there's a lot of opportunity there for
companies.
Yeah, me too.
That's just a goldmine If I canput some stats behind that.
We definitely serve a decentnumber of staffing agencies.
A lot of our customers arein-house.
For in-house customers acrossthe board, 30 to 50% of folks
that are hired already existedin your CRM or ATS before you
hire them.
And then for enterprisecustomers, it's something like
60, 70% of the larger ones and,yeah, that's a goldmine.
But when you think about, like,how folks are actually entering
(34:32):
process, it's in reallyinefficient ways.
It's people going out and coldsourcing them again, or
companies running like Just soexpensive.
Right, yeah, you're buildingpipeline and 60, 70% of them, if
you're an enterprise customer,are already people that you have
relationships with, but you'repaying all over again to build
(34:52):
those pipes.
Speaker 1 (34:54):
Yeah, that's the whole thing.
One of the reasons of many thatI really like the idea of
optimizing inbound and kind ofrediscovery is because outbound
motions can be very expensivefrom a headcount perspective and
they're important and they'restill like probably the most I
would say for specifically forknowledge workers and specific
profiles.
I would say you need anoutbound motion right like at
(35:16):
secure vision.
Most of the hires we help ourcustomers with are still
outbound outbound sourcing butnonetheless that's because we
there hasn't been tech.
I think that has reallyoptimized inbound and
rediscovery very well.
There's just been gaps in thetechnology and I think that
those things are now like moreproducts are coming out to
(35:37):
essentially increasecontribution to hiring from
inbound, increase contributionto hiring from rediscovery and
make that a more significant ROImotion and that should help at
least balance out the cost wherethe sourcing efforts it's going
to cost more but you can bereally dialed in and get those
new profiles.
And that's really, if you'repaying a senior recruiter and a
(35:59):
recruiting tech stack foroutbound, which is expensive,
more expensive, like you shouldhave them laser focused on
building those net newrelationships, right.
Speaker 2 (36:09):
Yeah, exactly, you don't want them like exactly
reinventing the wheel with folksthat you already know about.
Same for inbound like companiesspend millions of dollars on
like job advertising and 60 70%of the people they hire are
people that are already in theirdatabase yeah, that's true no,
I think it applies to both.
It just across the board, likethe top of the funnel, is quite
(36:33):
expensive.
So if you can augment that withpeople you already know about,
no brainer yeah, yeah.
Speaker 1 (36:42):
Just one quick question on the rediscovery
motion that you're building out.
Essentially, it's going in andyou're able to search for folks
that match based on theirscreening interviews or their
resumes, or is it like acombination?
How is GEMS surfacing thecandidates that are the best for
a role?
Speaker 2 (37:00):
Yeah, so it's two things.
One is, on top of the resume,we'll use that same ranking and
matching engine and help youfind folks that best match those
five to 10 criteria that, likethe recruiter or hiring manager,
is defined for that job, andI'll look across your entire ATS
and CRM database for folks thatare the highest match.
(37:20):
But then on top of that, youcan also add some smart filters
so you can filter out folksbased on, like, how far they got
in the interview process, whatthe blend of scorecards was.
Speaker 1 (37:30):
Oh, okay, yeah, that's really cool.
Speaker 2 (37:32):
Yeah, folks out based on have you had a touchpoint
with them in the last three tosix months or were they rejected
within the last year?
A lot of the really commonrules of engagement that
companies might have about, likewhen they want to re-interview
folks.
And because GEM is anall-in-one recruiting platform
that covers sourcing, CRM,scheduling, even like talent
(37:56):
marketing capabilities, ATS likewe've got the most complete
source of truth for all thosedifferent touch points that you
can put on top of.
Speaker 1 (38:03):
Yeah, for sure it all , yeah, it's integrated, all
tied together.
Yeah, that's awesome, man.
Yeah, I got to get my hands onmore of the products that you
have right now Still using.
We're on the sourcing productof building cadences and
outreach campaigns, which is, Ithink, you're running butter at
least it was back in the day soit's the primary product and, of
course, grown so much sincethen.
Speaker 2 (38:24):
Yeah, let's get you set up on it, James.
I'd love to get you guys thefull, the full power of Jam all
in one.
Speaker 1 (38:30):
Yeah, we got to do it , man.
I actually have been meaning totalk to you about that, because
I'd rather, I just I do want todo everything through through
Jam at this point, just based onwhat you're building.
It's just.
It would make things a loteasier for us too.
Speaker 2 (38:41):
You got it.
I feel like we've had a reallyproductive pod.
We've we've figured outpotential partnership
opportunities between you andJem.
Yeah, yeah, we're going to getyou on to Jem all in one.
Let's do it, yeah.
Speaker 1 (38:52):
Hell yeah, man.
Yeah, as always, it's a.
It's been a lot of fun.
Thank you for joining us todayand sharing your insights, and I
always enjoy these episodes alot.
I'm happy we get to do them ona regular basis.
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