February 21, 2025 • 39 mins
Are outdated hiring practices slowing you down? Join us for an insightful chat with Varun Khurana, co-founder of Wayfaster, as he shares his journey from employee to entrepreneur. Frustrated by recruitment inefficiencies, Varun and his co-founder built a cutting-edge voice AI solution to revolutionize high-volume hiring.
We dive into how AI is reshaping recruitment—streamlining resume screening, optimizing interviews, and enhancing efficiency while keeping the human touch at the forefront. But as AI evolves, does it threaten recruiter jobs or simply refine them?
Get the inside scoop on AI’s role in hiring, its impact on job markets, and the future of tech-driven recruitment. Don’t miss this episode! 🎙️
Additional Resources:
1. Wayfaster
2. Mass Recruitment: The Complete Guide
3. How Is Artificial Intelligence Changing the Recruiting Process?
4. Can You Trust AI to Handle Recruitment?
🧠 WANT TO LEARN MORE? Be sure to subscribe and check out 4 Corner Resources at https://www.4cornerresources.com/
👋 FOLLOW PETE NEWSOME ONLINE:
Linkedin: https://www.linkedin.com/in/petenewsome/
Blog Articles: https://www.4cornerresources.com/blog/
👋 FOLLOW VARUN KHURANA ONLINE:
Linkedin: https://www.linkedin.com/in/vkhurana2/
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Pete Newsome (00:00):
You're listening to the Hire Calling Podcast,
your source for all thingshiring, staffing and recruiting.
I'm Pete Newsome and my guesttoday is Varun Khurana, founder
of Wayfaster.
Varun, how are you today?
I'm doing great, pete.
Thanks for having me.
Thanks for joining.
You are doing something prettyexciting in the marketplace
right now, so I'm super pumpedto hear more about it.
You and I have not spokenbefore today, so that's always a
(00:27):
fun thing.
Where all these questions I'masking they're genuine because I
don't know the answer, it makesfor a more exciting interview,
I think.
Varun Khurana (00:31):
I'd love to hear it.
Hopefully we can tell you alittle bit more about Wayfaster
and what we're working on.
Pete Newsome (00:36):
Let's start from before we get to that.
Tell me a little bit about yourbackground and, ultimately, how
you came to start Wayfaster.
Varun Khurana (00:43):
Yeah, absolutely.
So there's two of us there's meand my co-founder, shreyas, and
a little bit of context on thecompany.
So Shrey was an early engineerat Checkr, which I think is very
familiar to people in thestaffing and HR space, for doing
background checks.
I was at Instacart, which is amarketplace that does grocery
delivery, grocery delivery andother things now as well, and we
(01:07):
noticed a couple of differentthings at those companies,
because those are both companiesthat A in corporate hire a lot
of different people, but alsothe customers they serve hire a
lot of people as well.
So Instacart will hire a lot ofdelivery drivers.
Checkr works with a lot of highvolume light industrial staffing
firms drivers.
Checkr works with a lot of highvolume light industrial
staffing firms and the issue younotice is that, as you need to
(01:32):
hire more people, it actuallyscales exponentially cost and
time wise to hire these people.
So at Instacart, when you vetdelivery drivers, it costs.
It goes like that Same thingwith all the staffing firms
Checkr works with as well.
And we also, when we wereworking at corporate, we
ourselves, as mid-twentiespeople, were doing a bunch of
interviews and when you're 25,you have no idea what you're
talking about in an interview.
(01:53):
You're just guessing and it'sthe best thing that you can hope
for is just you don't mess itup.
And so we always knew it was aproblem to both interview people
in the thousands of people,like corporate does, and also in
the hundreds of thousands, tensof thousands, as you see some
of the bigger staffing firms,bigger marketplaces in the world
do, and there wasn't really amodality to how you'd actually
(02:16):
interview more peopleefficiently.
The way you'd do it in the pastis you'd do a one-way video
interview.
You'd give them a text messagechat, which I think everyone
hates.
Every candidate hates.
Every recruiter hates it too.
Pete Newsome (02:29):
What are you getting out of that?
Varun Khurana (02:31):
And then Shrey had also been, like the first
engineer at a company calledDeepgram, which builds
text-to-speech models, and westarted to see this voice AI
thing was like a real thing thatwas happening and it was very
much for us having a problemthat we'd seen before many times
combined with now having thetechnology to actually solve it
at scale in a way that didn'texist before.
(02:51):
I think that's the magic ofmagic background of any good
startup.
Right, it couldn't have beendone six months ago, two years
ago.
You have to hit it on the rightpoint of time.
Pete Newsome (03:00):
Necessities, mother of invention.
Right, you saw a need in themarket, you lived it.
How did you make the leap?
I mean going from being anemployee to a founder.
That's a big step.
Needless to say, anyone who'sdone it knows that very well.
What was the catalyst for youmaking that decision and saying,
hey, this is something I needto solve?
Varun Khurana (03:17):
Yeah, I'll give you the honest answer, which is
that we were both working atcorporate jobs in 2022, where
the company wasn't growing thatfast anymore.
It was a crypto down cycle atCoinbase, where Shrey was, and I
was.
At Instacart, which has reallyslowed down growth by that point
, and it was something we knewwe wanted to do.
That being said, we wentthrough many failed ideas before
(03:41):
we landed on this one.
It wasn't a linear leap wherewe quit our jobs and then the
next day, wayfaster was born.
We worked on some really greatideas I think that we might have
missed the boat on likesoftware for private equity
firms and we also worked on somereally terrible ones.
We had like index funds forcrypto influencers, and these
are all learning experiences,and I think it was like six
months to a year of really justfliling around a little bit and
(04:05):
figuring out a problem that wasreally worth solving, with a
solution that we had adifferentiated viewpoint on, and
it was a very nonlineartransition that I don't think
enough people talk about.
When you're first starting acompany, which is it's never the
first idea right.
Pete Newsome (04:19):
Yeah, it rarely is right.
If anyone could come up with agreat idea, it would be easy,
right, and it's not.
I certainly can appreciate that.
But I hope, through all of thatyou did, if you had Bitcoin,
you did hold on to it.
Through all that, I hope thatwasn't one of your bad decisions
you made along the way.
Varun Khurana (04:34):
It's hard starting a company.
You're very poor and I'm verygrateful to Bitcoin for staying
with me through that entire timetime Nice, absolutely.
Pete Newsome (04:45):
So we're not in 2022 anymore, thank goodness,
and hopefully we don't go backthere.
So then, when you guys decidedto start Wayfaster, you lived
the problem you decided toexperience.
Describe the product for anyonewho's unfamiliar with it.
What problem does Wayfastersolve?
Varun Khurana (04:58):
Yeah, absolutely so.
If you're a staffing firm I'llput this in the context of
staffing our HR team, which is,like the statistics show, that
you get to about half theapplications that you receive,
and the ones that you do receive, you're not answering that
person right away, even if youend up answering them eventually
.
And the two key metrics thateveryone has decided really
(05:20):
matter in hiring are time tohire, which is how fast can you
contact someone and get themthrough your funnel, and then
the number of applicants,especially if you're staffing
where your pay is paid for eachincremental person that you're
interviewing and able to place.
And those two go hand in hand.
And really what we do is webuild voice agents that think
and sound like humans, so theyhave the same conversation that
(05:42):
we're having today that canactually interview people as
soon as they apply.
So the minute someone applies,they get on the phone with one
RAI interviewer.
He runs their screen.
That seems very familiar, verycomfortable.
We're able to process a lot ofmetadata out of that.
So an audio recordingtranscript and then what we call
structured outputs, which arethings we automatically extract
(06:03):
from an interview and push backinto your ATS.
And really what it is yourrecruiters are then only
speaking to qualified candidates, but you've also interviewed
all of your candidates on asmart timeframe, so you're
cutting down your time to hire.
You're getting only qualifiedcandidates for your recruiters,
and you're doing it at arelatively low cost too, which
is the tertiary benefit.
(06:23):
At the end of the day, it'sabout having great people and
getting to them fast.
If you can cut some costs inthe process, too, it's not a bad
thing as well.
Pete Newsome (06:31):
I'm more than a little excited about this
evolutionary step becausetechnology has made recruiting
more difficult than it waspreviously.
I'll share what I mean by that.
I'm old, so when I startedrecruiting, we would run ads in
the newspaper.
We would have resumes faxed tous or mailed.
I was excited to check the mailevery day as a young recruiter,
(06:52):
if you can believe that.
But each resume you had youreceived as a recruiter meant
something you had to get themost out of that conversation.
You had to really hone yourskills on building meaningful
relationships and buildingrapport quickly with someone and
gathering as much informationas you can from a can.
So you really invested time inthat individual right and you
(07:13):
had to in order to survivebecause you didn't know where
the next resume was coming from.
And I was away from recruitingfor 10 years before starting
Four Corner Resources, which isnow 19 years old.
So it's been a long time sinceI've been back.
But in between, monstercom wasborn and CareerBuilder and
through those products andothers like them and now
OneClick Recruiting, it's becomethe opposite.
(07:36):
You get a flood of resumes forany job you post now and it's
taken that art that wasnecessary to become a good
recruiter completely out of theequation and it's become this
mess of a volume game where, ifyou get 500 resumes within an
hour or two which happens for alot of jobs as a recruiter, it's
(07:56):
just not realistic to gothrough this and the best
candidates can be buried.
It's first in, first out, andATS systems don't do a good job
of ranking.
You know all of this right, andanyone in recruiting does, and
the problem that I've beentrying unsuccessfully to solve
for years was how can I put ajob posting up and have some
(08:16):
sort of a screening emailresponse, right, hey, rune,
thanks for applying.
Confirm these five thingsbefore we put you in touch with
the live recruiter or schedule.
You live right To take away allthat kind of garbage on both
sides, right?
Candidates, there's no price topay for just clicking and
applying to a million jobs, andrecruiters don't have the
(08:39):
ability to go through them.
So it was really askingcandidates to take an extra step
in order to engage with therecruiter life, but that was
impossible to solve, which iscrazy.
You're going to don't tell methere was a solution I didn't
know about and you knew what itwas and existed all along,
probably, but I couldn't find it, and so now what you're
describing solves that in a muchbetter way than an email ever
(09:02):
could.
Right now, you're having a liveinteraction, or as live as it
can be, through AI, which Ithink counts, and everyone wins
right, the candidate getsimmediate feedback or gets to
hear from someone, therecruiters get to spend their
time in the most quality fashion, which was the goal all along.
So I say all of that to say I'mreally excited.
(09:22):
There's no question there.
I just want to let you know Ipersonally and professionally
think this is a solution that'sso needed in the market, and you
can't say that about everytechnology that comes out.
But let me ask you about thepotential downside to it.
So I'm Gen X, right, so I'mearly 50s.
(09:44):
You still have a lot of boomers.
I am not early 50s.
You still have a lot of boomers, and I'm not a boomer.
You still have a lot of those.
In the workplace, you havemillennials this is somewhat new
interacting with AI.
Tell me about the, the rate ofpeople willing to interact with
AI.
What are you seeing?
What is it?
What is the data show?
Varun Khurana (09:59):
Yeah, first of all, you mentioned something
called mail.
Pete Newsome (10:02):
I'm not really sure what that is, I'm just you
let me know Is that it wouldcome on a horse with a carriage
behind it and they would.
Yeah, so it was.
I'll tell you about that later.
Varun Khurana (10:12):
Yeah, I definitely think that.
One thing I will add to whatyou're saying is not just the
influx of resumes.
So you're seeing this with likeIndeed and LinkedIn are almost
50% of recruiter spend in the USnow and they're known for easy
applies, so the volume is higherthan it is ever before.
But the flip side of the AIboom has actually been for
candidates.
It's super easy to replicatewhat a company's ATS is looking
(10:37):
for from a job description.
Pete Newsome (10:39):
Two years ago at least your resumes.
Varun Khurana (10:41):
You could filter out the candidates with a little
bit of higher intent and usesome keywords.
That gave you like it wasn't aperfect filter, but it gave you
something.
Now, all those resumes lookalike too, so you don't even
know where to start if you're arecruiter, which is what is
making this a really good optionfor recruiters, where they just
get something, a first passfilter, now that an ATS filter
isn't working at all.
(11:01):
But just to directly addressyour question, around downsides,
we always tell companies thatplease don't use this for an
executive search.
We've seen companies try tointerview CFO candidates and I
was like that is a horrible idea.
Please don't do that, becauseit's really good for it's really
bad for roles where therecruiter has to sell the
candidate just as much as thecandidate has to take the job,
(11:23):
and I think that there's a lotof jobs that exist, especially
on the mid-tire levels of anyindustry.
It's a two-sided conversationand recruiters are going to be
able to sell in a way that AIcan never do, no matter what any
of these products are promisingyou.
I do think that the candidatereception was one thing that I
was really scared of, and it'sbeen overwhelmingly positive,
(11:47):
and one of the reasons has beenlike it feels like candidates
feel like they're heard and likethey're getting a response that
they normally wouldn't have had.
I think there are certainverticals where people are less
responsive than others To yourpoint.
I don't think it's an age thing.
It's actually more about thevertical you're serving.
So we actually see less of adelineation around like age or
(12:09):
gender or anything like that,but more so hey, if you work in
a warehouse versus you workactually in a construction
industry.
Construction actually loves this.
They love to talk on the phone,even with its, even if it's ai,
but we see something likeindustrial.
The response rates, dependingon the brand and like company
that they're interacting with,actually vary quite a bit, and
(12:31):
so I would say to sum that allup is like for higher precision
roles, higher cognition roles,like this is not a tool that
should be used, because it isactually very much on the
recruiter to sell the candidateon the first call.
I would say for the rest of theroles non-exact roles of the
(12:51):
world I think it depends on howmuch leverage your employer
brand has and how much goodwillyou have with the candidates is
also one of the big keycomponents there as well, if
that makes sense.
Pete Newsome (13:03):
It does.
I'm surprised about yourcomment about the age thing,
though I wish I could quote it.
I should have had it preparedfor today.
I read an article sometime inthe past few weeks saying that
Gen Z prefers to interact withbots versus humans, and who
knows, you see all kinds ofcrazy articles.
You never know what's true,necessarily but it resonated
(13:25):
with me.
I thought that makes sense,right.
I have four kids age 16 through24.
They all have phones that arein their hand 24-7.
I'm not sure that I've everseen them speak on the phone and
they certainly don't pick upwhen I call.
That's my first-hand experienceand I just think it makes sense
, right, that the younger youare, the more open you are to
(13:47):
technology.
But what you said makes senseas well, which is higher volume
positions.
I think this is a more naturalfit, for as a recruiter, I would
generally associate that withjust a pure volume of
applications that we receive,not because it's a different
level just from supply anddemand, which ultimately is tied
(14:08):
to the level.
So it's been the same, perhaps,but for a different reason.
Varun Khurana (14:14):
Yeah, one of the interesting things about the age
thing, which is we've slowlybeen indoctrinated up to this
point without kind of usrealizing it, like, my parents
have been using Alexa for yearsnow right in our house.
It never works, but it's beenthere, and I think we've moved
towards bot-based text.
And then we have these voicedevices we're talking to and
(14:34):
then we're seeing some stuffwith the LLM companies
themselves coming out withproducts like this, and I think
that adoption curves slowlycreeped into older generations
as well, to the point that a lotof them are very used to
interacting with this tech, evenif they don't directly know it.
And it's one of the earliestthings we used to measure,
because our calls would takeeight, nine seconds to connect
(14:57):
when we first built this out andwhere the tech was a little
more nascent.
And we would always try to geta good gauge on how people
reacted to when the bot firstspoke to them.
If we didn't tell them ahead oftime, if we just triggered a
phone call and there'd be someconfusion for a couple seconds.
But we were always reallyimpressed with how smoothly
(15:19):
people would understand this wasa bot, hear it and go with it
if we didn't tell them.
Now, obviously, as a company,we have all these measures in
place where we give peoplepractice calls and it's an
amazing candidate experience.
But even in those earliest days.
People just go with the flow andthey've been using this tech
for years and they just don'trealize it.
And that's what's crazy aboutthis.
Pete Newsome (15:39):
That's a great point.
We do use it and we don't eventhink about Alexa being a great
example of that.
I get a kick out of my wifeinteracting with it because as
Alexa fails to respond, her tonechanges and she thinks, if
she's like harsher with Alexa,we'll do what she wants, which I
think the only thing we use itfor is setting an alarm to get
up in the morning.
That's the extent of what Alexadoes for us.
(16:00):
Let's break it down so we'lluse your example of a warehouse
position.
I think that's a great one, aconstruction role.
So I put my job posting onIndeed.
Applications start to come intake over from there.
Varun Khurana (16:18):
What happens?
Yeah, absolutely so.
We're a company calledWayfaster and so our goal, as
you can imagine, is just speed,primary first, and the way it
works is you'll apply it.
That application info will getsent to an ATS and staffing is
full horn primarily and morecorporate.
It can be anything fromWorkable to Ashby, depending on
the type of company.
Pete Newsome (16:35):
As soon as that happens.
Varun Khurana (16:37):
What we'll do is sometimes companies will have a
default ATS filter, Sometimesthey don't.
One of the benefits is you caninterview every candidate, so
you don't necessarily need onewith Wayfaster.
So they apply, we trigger alink to each of those candidates
.
The company decides whetherit's phone or video, depending
on the role.
With a warehouse, it's morethan likely phone, and a big
reason why it's phone or videodepending on the role with a
(16:57):
warehouse.
it's more than likely phone, anda big reason why it's instant
is like we find 80% ofapplications actually come
between the hours of five andnine, and so it's when someone's
frustrated at their currentrole, especially a warehouse,
and they're like fuck this, I'mgoing to apply, excuse the
language, I'm going to apply toanother job and like we want to
get them as soon as they're inthat frustration point so that
(17:18):
they are able to really gothrough the application process.
Pete Newsome (17:20):
They take the interview out of that.
Varun Khurana (17:23):
We'll pull out.
We'll first onboard them, tellthem hey, this is an AI on
behalf of staffing firm thatwe're representing.
They'll run through a list ofquestions, Some of it which is
pre-populated, some of it whichis actually generated on the fly
from AI based on what thecandidate is saying.
From there we'll take out theresults, transcript recording,
(17:44):
some outputs.
We'll take all that data, We'llpush it back into the ATS.
We can set the filters on whichthere's an accept or reject
decision, and then we schedule afollow-up recruiter interview
with a real recruiter, if needbe and if they're qualified, and
then we schedule a follow-uprecruiter interview with a real
recruiter, if need be and ifthey're qualified.
So we essentially go fromapplication to the point where
they book their next call withthe recruiter in the span of
maybe 10 to 15 minutes.
Pete Newsome (18:05):
Love it.
So the job rec can come in atfive o'clock, the recruiter can
post the ad, go home for thenight and, in theory, come in
the next morning and they havemeetings booked with zoom.
Whatever phone call with actualcandidates who've already been
screened by the ai.
Is that it in a nutshell?
Varun Khurana (18:22):
yeah, that's exactly it, and for some
industrial roles you actuallycan actually just have them show
up to the job site by the nextday.
Because if you've automatedyour stuff around compliance and
background checks and you'relike we just need a light filter
in terms of checking a couplecheck the box items here, we can
actually go through that entireworkflow from within your ATS,
depending on how advanced yourrecruitment system is Now.
Pete Newsome (18:44):
Would that come from a preloaded list already
that exists in the ATS, or couldthat also work with
applications who are coming inlive for the first time?
Varun Khurana (18:53):
Yeah, so that's actually the beauty of it is we
do both.
So we actually a lot of thetimes.
One of the craziest things Ilearned about staffing is the
way it works at a lot ofstaffing firms is you'll put up
a role, they'll have spent allthis money on Indeed and you
need five people at a warehouseand they'll have 15 people apply
(19:14):
.
They fill those five peoplewith those 15 people, then
they'll have 70 other peopleapply and then they never talk
to them.
The next they fill those fivepeople with those 15 people,
then they'll have 70 otherpeople apply and then they never
talk to them.
The next time they fill therole, they just post that same
ad on Indeed, and it happens sooften and it drove us crazy.
So we actually tell companiestwo things.
We're like look, the firstthing we're going to do is we're
going to actually go justinterview everyone in your ATS
(19:34):
that's just on the backlog.
They may have switchedpositions, but this is valuable
data that you never talk tothese people and then from there
, every person who applies wealso interview.
So we actually do it both wayswhere we want to interview
companies existing ATS databaseand their backlog and also for
every new applicant that comesin.
The goal is holistically likeyou're never missing a good
(19:57):
application that couldpotentially be valuable to your
firm.
Pete Newsome (20:00):
So if we did the scenario where we said we want
to clean up our ATS and everystaff and company has a need to
do that, I suspect right, all mypeers and friends do.
And at Four Corner we haveroughly a million candidate
resumes dating back as long as19 years ago candidate resumes
(20:21):
dating back as long as 19 yearsago and I would estimate that
only about half of those areclean today, but the fact is
that is gold that's sittingbeneath the surface, that I
can't really get to for variousreasons and, at the very least,
it's impossible to keep up withpeople right, no matter how good
your intentions are.
It's impossible to keep up withpeople right, no matter how good
your intentions are.
It's just not practical For thescenario you outlined.
(20:41):
Just to run with that, those 70candidates that came in, you
really didn't have a practicalway to address them because
you've already filled theposition of yes, you want to
look forward and we all mean it,would love to do that in a
perfect world, but we're on tothe next job, right, and it's
just the reality of it.
So we lose money by pausing todo that as an industry.
(21:02):
You know that I'd love to cleanup my whole database, so if we
wanted to do that, would we justcome up with a list of
questions and give it to the AIto say, hey, look, this is what
we want.
We want to find out what thecandidates are doing today.
And maybe we set a call with therecruiter if they're on the
market, on and on, there's somuch benefit to that, and is
(21:24):
that?
But is that how it would work?
Varun Khurana (21:31):
Yeah, that's a lot of the time.
Staffing firms come to us andlook like they're a lot it's
still a very new technology andthey're worried about, hey, how
are candidates going to react tothis?
And we tell them, like looklike your response rate on your
past ats candidates can be waylower.
They change numbers.
They're happy in their new job,like maybe they're in between
things like your contactinformation is off, so maybe we
were able to reach half as manyas we would with new applicants.
(21:53):
But we tell them, like let'sjust try it out on your backlog
of candidates.
We can theoretically at leasttry to interview all of them and
even if 10% of them end upresponding and updating that
information, like you mentioned,it's still it's something that
you would have normally.
Not even that 10% isn't comingto you.
And so we try to go tocompanies and tell them here's
(22:14):
where we're going to do firstlift and then we can kind of
transition into new candidatesbecause I think they see the
value of hey, this has workedand we were able to get some
information intake and it wasn'ta hostile experience for the
candidate.
It was actually pretty good forthem, for the ones that did
pick up, and that's how we startthe relationship with most
firms.
A lot of the time, and youimplied this earlier.
Pete Newsome (22:34):
But I just want to clarify you never try to
pretend that it's not a bot,right?
That's communicating to theindividual, right up front.
That this is an AI conversation, right?
Yeah, yeah.
Varun Khurana (22:45):
I think we came to the conclusion.
It's like we don't think peopleare stupid, which is what I
think people who stop try topass off their AI as humans
assume of humans.
And we tried avatars at somepoint and, Pete, let me tell you
, people hated that.
Nobody wants to talk to anavatar Nobody, it turns out.
Pete Newsome (23:02):
Yeah, I listened to your demo.
It varies, steve, right?
Is that the name of your AIvoice?
Yeah, sounds real and we'regetting close.
Right, we're getting there.
Did you see the new Megan Foxmovie on?
Varun Khurana (23:17):
Netflix yet?
No, I haven't.
I'll have to check it out.
Pete Newsome (23:18):
Subservience.
Basically, it's a robot wholives as a caretaker, nanny and
let's just say the husband.
Let's just say the robot isMegan Fox and looks like Megan
Fox.
You can just imagine how thatgoes.
We're seeing this blend happenreally quickly.
But I think people don't wantto be fooled either.
That's just human nature youmentioned a few times.
(23:40):
So back to the database.
I just want to, because that issuch an impactful thing Give me
an idea before we move on topricing.
How does your pricing structurework, because that's a lot of
work.
I don't know where the heavylifting comes in on your side
from a data standpoint andsoftware, but generally speaking
, you don't have to get precisewith it.
But how does it work generally?
(24:01):
Yeah, I would say just the.
Varun Khurana (24:04):
It's not directly answering the question, but one
thing that we've been veryconscious of is that it's not
just the time you're saving fromthe interview.
With every interview there's apost review of the interview,
even if you give them atranscript of recording and all
that stuff.
And part of being way faster isthat we actually want to pull
out the key inputs the recruitercan just take a quick glance of
okay, this person has 22 yearsof experience, this role
(24:28):
requires two.
Let's just this is a no-go orwe just update this information.
So we try to post-process themand pull out the key inputs that
you're looking for there tosave the time on like what we
call like the post-processingthe transcript.
And the reason I bring that upis like that, I think, is like a
big thing for us is we're ableto automate that process.
So it's actually not that hardfor us.
(24:50):
Whether it's 15 candidates or athousand candidates, it's
actually relatively the samelift from us, except for the
infrastructure costs.
In terms of like automation,it's pretty much the same.
We transparently just chargebased on volume.
So if companies want to andthat is completed calls too, and
a completed call being anythinglonger than 30 seconds, and the
(25:11):
volume, as you can imagine,pricing scales down with the
number of calls that you'recommitting to for the year.
So if companies want to do100,000 calls, it's going to be
significantly cheaper than 5,000calls.
But that's how we price.
Pete Newsome (25:24):
You mentioned a few things earlier.
You mentioned targeting largestaffing companies and you also
mentioned corporate versus arecruiting firm.
So differentiate that.
But also tell me if there's acompany size that's really in
your sweet spot.
Varun Khurana (25:37):
No, I don't think we see companies that run high
volumes at really low volumes,like, for example, marketplaces.
Sometimes we'll interview tonsof people and actually have five
, 10 people on the team, andthen we also go up to really big
light industrial staffing firms.
So we don't have any sizeconstraints in terms of size of
(25:58):
company, like generally we'veseen our sweet spot is like a
firm with, whether corporate orstaffing of roughly about a
hundred people and above.
But I think the biggestdenominator is just like volume
of applicants because, and howmany positions you're looking to
fill, because at the end of theday, like you only need an
extra set of hands, whetherthat's through AI or human, if
(26:19):
you have enough applicationvolume coming in, and I think as
long as you have a large numberof applications, I think we're
a pretty good fit for you.
Pete Newsome (26:27):
Can you quantify that?
What would you consider a largenumber?
Yeah?
Varun Khurana (26:31):
I would say roughly, at least 500 to to 2000
a month is like at the veryminimum.
I think is targeting.
What about?
Pete Newsome (26:38):
per job.
Is there like a?
Was there a job that would be?
We talked about levels and Iassociate the levels also with
the supply of candidates.
Right, there's go hand in hand.
There's not gonna get athousand applicants for a CEO.
One click apply.
There will be, but we're goingto try to screen that out as
best we can.
And the job post but is costeffective for a job where you'd
(26:59):
get 20 applicants, or do youneed 200?
Varun Khurana (27:02):
Yeah, I would say it depends on the like real
answers.
It depends on how you're doingit today, which is, if your
recruiter, if you get sevenapplications and they're all
pretty good applications andrecruiters able to get to them
in an hour, then you don'treally need us.
If the recruiter is overwhelmedthat they have 500 applications
or 50 applications or whateverthat number is and they're like
(27:23):
we're having trouble filling therole fast because I can't get
to applications fast enough,then we're probably fit.
There's no hard and fast number.
Obviously, as you can imagine,if you're hiring people by the
bushel and like hiring 50, 100people a day, like you know,
it's going to be a little moreacute, just statistically
speaking.
But we just want to go toplaces where we can help the
(27:43):
most, as opposed to looking atany direct sizes.
But in terms of staffing, it'susually seen that benchmark be
like once you cross that 100person threshold or even like
lower.
We've seen like 25 better, likemore on the RPO side or more
light industrial, where they'redoing more with those 25 people.
That's where we've seen a lotof traction so far.
Pete Newsome (28:03):
Do you see a difference so far in acceptance
or willingness to use theproduct?
Varun Khurana (28:08):
on corporate versus staffing Sorry, say that
one more time.
Pete Newsome (28:12):
Have you seen a difference in just willingness
to step out and adoption, if youwill, of AI and corporate
hiring versus staffing?
Varun Khurana (28:36):
Yeah, I would say staffing using like a DMS or
like one of these heavyenterprise companies, and I
think in corporate obviouslythat's the mandate from HR but
the business kind of goes andlives on even if you're not able
to do that.
Like Domino's would love to getpeople in the door faster and
get people placed and have theirjobs and their stores, but
(28:59):
Domino's will live on even if ittakes them another two or three
days to do it, because theyhave an infinite pool of
applicants.
And I think that employer brandthat you have as a corporate
generally tends to do you somewonders and it's not mission
critical though it is like ahuge problem, whereas in
staffing like that is the wholebusiness model right and I think
(29:20):
that's where we see likerecruitment services is like a
little more acute thancorporates.
Pete Newsome (29:24):
That makes complete sense.
Listen, you mentioned whatdrove you crazy earlier.
What drives me crazy iscompanies who are willing to
just sit on job openings when wemeasure how fast they're filled
in hours, sometimes days atmost, and they measure in weeks,
sometimes even months, which iscrazy to me, but that's reality
.
So I completely I'm notsurprised at your answer at all,
(29:45):
knowing what I do about that.
It seems to me anyone who'ssending a lot of screening
offshore is you've rendered thatcompletely unnecessary or am I
missing something obvious?
Because I think speaking with abot or AI, or Steve in your
case, is a much betterexperience than speaking with
(30:06):
someone overseas where there's alanguage barrier.
Let's just call it for what itis.
You've really take all of thatout of the equation.
Yeah, it's funny.
Varun Khurana (30:15):
So we sell three big things to companies.
We sell them speed, quality andcost.
And when it comes to in the U?
S, when we take things off therecruiters place and put them
qualified candidates you onlyinterview qualified candidates.
We're usually selling them onspeed and cost, right, like
maybe you don't need that extrapair of hands.
(30:36):
When it comes to offshoring,we're actually often selling
quality as well, whereas, likethe AI out of the box, not only
is it faster and more costefficient, though that cost
Delta, as you can imagine, is alot lower offshore.
Actually, just the quality forboth the candidate and the types
of questions that are asked andthe responses generate are
actually significantly alreadybetter than a lot of offshore
(31:00):
interviewers, and I think we'regoing to, as the AI's cognition
gets better, like that gap isgoing to continue to increase
for us offshore.
So I maybe, pete, you can pointme to them, but I actually
haven't come across a lot ofstaffing firms that outsource
this stuff to offshore.
Pete Newsome (31:15):
Really.
Varun Khurana (31:16):
Yeah, very rarely we work with BTOs, but that's
for completely to interviewtheir offshore people, as
opposed to the process.
Pete Newsome (31:24):
You know it's almost necessary to compete
effectively in the VMS space.
If you live there, that'sreally hard to do exclusively
through American recruiters,just because of the cost, as you
mentioned.
So call it offshore, call itnearshore.
I see most of that first levelscreening happening there,
(31:45):
versus with US-based recruiters.
So I'm surprised that you'renot encountering I figured
that's who would flock to yourproduct first.
It was organizations like that,or maybe I think it's still new
.
I don't know how many clientsyou have so far, but I see this
evolution happening fast andI'll tell you I was at the
TechServe Alliance conference.
(32:05):
It just took place two weeksago.
Were you there out in Arizona?
Varun Khurana (32:09):
I missed that one , unfortunately.
Pete Newsome (32:11):
So, techserve, I usually go.
I wasn't able to make it thisyear, but the feedback I got was
that AI integration is a hottopic and everyone's trying to
figure it out.
So, look, I think you're in agreat space.
You're probably a very busy guythese days.
As a result of that, I thinkyou're solving, as I said
(32:32):
earlier, a big problem fornearly every staff and company.
There's any kind of volume,right?
Yeah, any kind other than, likeyou said, executive search.
I see that as an exception, butfor everyone else, man, this is
you're at the right place atthe right time.
So last question AI, future ofAI.
We hear about singularity.
There's a lot of scary thingsout there.
We've got drones flying overNew Jersey, not too far from you
, right?
It's crazy time.
What do you think?
(32:54):
Are you excited?
Are you nervous?
Are you both?
What do you see happening?
Varun Khurana (32:58):
Yeah, I can maybe give you two answers.
One is like in recruitmentspace, and then the second is
more so in the kind of generalAI spokes, I think, within
recruitment.
Like recruiters, I think enterbest at selling candidates and
there's a part of the economywhere that's never going to go
away with that human touch andwhether that's corporates,
(33:20):
staffing firms, no matter whatrole is, every staffing firm
knows it's always best to keep agreat relationship with your
potential candidates.
And I think that's going tocontinue to be true, no matter
how good AI gets, and there'scertainly, I think, other parts
of the stack that are going toget automated, especially as
candidates learn to leverage AIin a way that's more effective
(33:41):
for generating resumes orauto-populating texts or
cheating on assessments and allthese different things, and I
see this being a constant backand forth on AI versus AI.
When it comes to AI broadly, Ithink there's things I'm super
excited about and there's thingsthat I'm terrified about.
Right, like, we work at thecutting edge of models and it
seems like they're starting toasymptote a little bit without
(34:03):
better data, but you can imagine, with a lot of effort and a lot
of money, that's going to getbetter and unblocked.
And I do worry, like mostpeople in tech do, about what
purpose humans are going to playif these models get really
smart.
And I think that is scary,because I believe humans need
work and we like to do it.
(34:23):
Despite how much we complainabout our Zoom meetings and the
mundanity of a lot of it, Ithink doing Excel for six hours
a day it keeps us sane.
And I do worry about if weautomate some of these jobs,
like the AI line's always beenlike, we'll find new careers and
new roles will pop up and I'msure they will, and I think
(34:46):
that's maybe an unfoundedconcern, but it's something that
I worry about.
I also not to throw a newwrinkle at you, pete, but I'm
starting to see the pace of AIas it applies to robotics really
speed up, and so there wasalways this concern about these
real world jobs will always bethere, and now I'm seeing these
robots that can, like using LMsfor spatial awareness, do a lot
(35:09):
of retail jobs, do a lot of likefast food jobs and all this
stuff and that to me is actuallythe craziest stuff I'm seeing.
It's like these humanoid robotsthat leverage AI in a way that
I never saw coming in mylifetime, so that's always
freaks me out.
Pete Newsome (35:23):
It's happening with such rapidity, right?
I think that's the thing that Iworry about in the workforce
people being prepared for is itjust?
It happens almost overnight andfrom the minute chat GPT was
released, entire professionshave almost been rendered moot
and irrelevant.
I just I worry about it a lot.
I worry.
I look at you know young peoplein school right now and getting
(35:45):
degrees and things that aregoing to be completely
unnecessary.
We're spending so much time andmoney.
And then, like you said, therobots.
I mean every week it seems likeElon's putting a new video out
of his robot that he thinks isgoing to be a $20,000 product
within the next couple of yearsthat we're all going to have at
home.
It's bigger, faster, stronger,smarter than everyone else, and
(36:07):
you add dexterity on top of itand you go.
That's a problem.
Varun Khurana (36:09):
Huge problem Terminator.
Very real documentary.
It seems like I would say, whenyou speak of degrees, my one
piece of advice to any listenerwho happens to be listening to a
staffing podcast under the ageof 22, pete, I'm sure you've got
a great audience.
I'm not sure many of them arestill in school, but do not get
a.
CS degree, because that seems tobe like the way that we're able
(36:31):
to generate code seems to beespecially suited to LMs and
what they're able to do and notscale really well, and it's
freaking me out how easy it'sbecoming to build software a lot
of the times you mean my 22year old who's in grad school
for for cybersecurity Probably.
Cybersecurity is going to behuge because we're not going to
be able to tell what's real ornot?
Pete Newsome (36:52):
I think it will.
I think it will be.
I get what you're saying about,about programming and coding.
Is that?
And I've even seen I've evengenerated code, and I don't I'm
not technical at all throughthrough AI that I handed to my
developer.
He's like yeah, it's just amatter of doing what I need to
do to implement it from there,which is crazy, right.
Never would we have thoughtthat, even just a couple of
(37:12):
years ago.
But when it comes to recruiting,we're not going to solve the
world's problems At least I'mnot.
So I'm going to worry aboutrecruiting and you're young
enough, maybe you can.
But I think it makes us evenmore valuable as human
recruiters, because I think ourjob, ultimately, is to not
assess for things like hardskills right, that's relatively
(37:33):
easy and whether it's really agood fit right on things that
just I don't worry about AItaking from us, because you have
to still be able to separatewhat's said from what's implied
and all those things.
Can AI get there one day?
(37:53):
Probably, I think I'll be onthe beach by the time that
happens Hopefully not under it.
But yeah, I think we're goingto see a lot of changes that are
going to be challenging, but Ithink recruiters are safe for a
while.
I really do.
Varun Khurana (38:08):
I think so too.
I'm very bullish on the futurerecruiters.
I think they're just going tobe doing to your point like
different work and like moremanaging the soft skills and
especially I think Four Cornerdoes a decent amount of IT
staffing and I think there's themisalignment between when the
recruiter is doing a skillsassessment with the candidate
shouldn't exist, but someonestill needs to assess can that
(38:31):
candidate communicate well anddo some of these softer things?
And AI is never going to be ableto judge that in the way that
humans can, and that's bothendearing and good for you guys.
I think too, over the nextcouple of years, as, like AI, to
your point, eliminates a lot ofjobs that maybe don't have
those benefits.
Pete Newsome (38:47):
Yeah, it's going to make us better and you're a
big part of that.
I love what you're doing.
I can't wait to see how youprogress from here, and I'd love
to have you back on in a yearlet's see where what's evolved
since then, if you're willing tocome back and talk to me you
may be already from what I know.
Maybe you're the AI and I justdon't know it yet.
(39:09):
But, bruin, thanks so much, man.
This has been a lot of fun andeveryone thanks for listening,
and I'll put all your contactinfo so everyone can find
Wayfaster in our show notes andcheck it out.
It looks like a great product,so thanks so much for your time
today, yeah product, so thanks.
Varun Khurana (39:23):
Thanks so much for your time today.
Yeah, thanks for having me on,pete, appreciate you having me
on.
And yeah, it's justwayfastercom if you guys want to
check this out Awesome.
Pete Newsome (39:30):
All right, everyone.
Thanks for listening.
You're listening to the Hire Calling Podcast,
your source for all thingshiring, staffing and recruiting.
I'm Pete Newsome and my guesttoday is Varun Khurana, founder
of Wayfaster.
Varun, how are you today?
I'm doing great, pete.
Thanks for having me.
Thanks for joining.
You are doing something prettyexciting in the marketplace
right now, so I'm super pumpedto hear more about it.
You and I have not spokenbefore today, so that's always a
(00:27):
fun thing.
Where all these questions I'masking they're genuine because I
don't know the answer, it makesfor a more exciting interview,
I think.
Varun Khurana (00:31):
I'd love to hear it.
Hopefully we can tell you alittle bit more about Wayfaster
and what we're working on.
Pete Newsome (00:36):
Let's start from before we get to that.
Tell me a little bit about yourbackground and, ultimately, how
you came to start Wayfaster.
Varun Khurana (00:43):
Yeah, absolutely.
So there's two of us there's meand my co-founder, shreyas, and
a little bit of context on thecompany.
So Shrey was an early engineerat Checkr, which I think is very
familiar to people in thestaffing and HR space, for doing
background checks.
I was at Instacart, which is amarketplace that does grocery
delivery, grocery delivery andother things now as well, and we
(01:07):
noticed a couple of differentthings at those companies,
because those are both companiesthat A in corporate hire a lot
of different people, but alsothe customers they serve hire a
lot of people as well.
So Instacart will hire a lot ofdelivery drivers.
Checkr works with a lot of highvolume light industrial staffing
firms drivers.
Checkr works with a lot of highvolume light industrial
staffing firms and the issue younotice is that, as you need to
(01:32):
hire more people, it actuallyscales exponentially cost and
time wise to hire these people.
So at Instacart, when you vetdelivery drivers, it costs.
It goes like that Same thingwith all the staffing firms
Checkr works with as well.
And we also, when we wereworking at corporate, we
ourselves, as mid-twentiespeople, were doing a bunch of
interviews and when you're 25,you have no idea what you're
talking about in an interview.
(01:53):
You're just guessing and it'sthe best thing that you can hope
for is just you don't mess itup.
And so we always knew it was aproblem to both interview people
in the thousands of people,like corporate does, and also in
the hundreds of thousands, tensof thousands, as you see some
of the bigger staffing firms,bigger marketplaces in the world
do, and there wasn't really amodality to how you'd actually
(02:16):
interview more peopleefficiently.
The way you'd do it in the pastis you'd do a one-way video
interview.
You'd give them a text messagechat, which I think everyone
hates.
Every candidate hates.
Every recruiter hates it too.
Pete Newsome (02:29):
What are you getting out of that?
Varun Khurana (02:31):
And then Shrey had also been, like the first
engineer at a company calledDeepgram, which builds
text-to-speech models, and westarted to see this voice AI
thing was like a real thing thatwas happening and it was very
much for us having a problemthat we'd seen before many times
combined with now having thetechnology to actually solve it
at scale in a way that didn'texist before.
(02:51):
I think that's the magic ofmagic background of any good
startup.
Right, it couldn't have beendone six months ago, two years
ago.
You have to hit it on the rightpoint of time.
Pete Newsome (03:00):
Necessities, mother of invention.
Right, you saw a need in themarket, you lived it.
How did you make the leap?
I mean going from being anemployee to a founder.
That's a big step.
Needless to say, anyone who'sdone it knows that very well.
What was the catalyst for youmaking that decision and saying,
hey, this is something I needto solve?
Varun Khurana (03:17):
Yeah, I'll give you the honest answer, which is
that we were both working atcorporate jobs in 2022, where
the company wasn't growing thatfast anymore.
It was a crypto down cycle atCoinbase, where Shrey was, and I
was.
At Instacart, which has reallyslowed down growth by that point
, and it was something we knewwe wanted to do.
That being said, we wentthrough many failed ideas before
(03:41):
we landed on this one.
It wasn't a linear leap wherewe quit our jobs and then the
next day, wayfaster was born.
We worked on some really greatideas I think that we might have
missed the boat on likesoftware for private equity
firms and we also worked on somereally terrible ones.
We had like index funds forcrypto influencers, and these
are all learning experiences,and I think it was like six
months to a year of really justfliling around a little bit and
(04:05):
figuring out a problem that wasreally worth solving, with a
solution that we had adifferentiated viewpoint on, and
it was a very nonlineartransition that I don't think
enough people talk about.
When you're first starting acompany, which is it's never the
first idea right.
Pete Newsome (04:19):
Yeah, it rarely is right.
If anyone could come up with agreat idea, it would be easy,
right, and it's not.
I certainly can appreciate that.
But I hope, through all of thatyou did, if you had Bitcoin,
you did hold on to it.
Through all that, I hope thatwasn't one of your bad decisions
you made along the way.
Varun Khurana (04:34):
It's hard starting a company.
You're very poor and I'm verygrateful to Bitcoin for staying
with me through that entire timetime Nice, absolutely.
Pete Newsome (04:45):
So we're not in 2022 anymore, thank goodness,
and hopefully we don't go backthere.
So then, when you guys decidedto start Wayfaster, you lived
the problem you decided toexperience.
Describe the product for anyonewho's unfamiliar with it.
What problem does Wayfastersolve?
Varun Khurana (04:58):
Yeah, absolutely so.
If you're a staffing firm I'llput this in the context of
staffing our HR team, which is,like the statistics show, that
you get to about half theapplications that you receive,
and the ones that you do receive, you're not answering that
person right away, even if youend up answering them eventually
.
And the two key metrics thateveryone has decided really
(05:20):
matter in hiring are time tohire, which is how fast can you
contact someone and get themthrough your funnel, and then
the number of applicants,especially if you're staffing
where your pay is paid for eachincremental person that you're
interviewing and able to place.
And those two go hand in hand.
And really what we do is webuild voice agents that think
and sound like humans, so theyhave the same conversation that
(05:42):
we're having today that canactually interview people as
soon as they apply.
So the minute someone applies,they get on the phone with one
RAI interviewer.
He runs their screen.
That seems very familiar, verycomfortable.
We're able to process a lot ofmetadata out of that.
So an audio recordingtranscript and then what we call
structured outputs, which arethings we automatically extract
(06:03):
from an interview and push backinto your ATS.
And really what it is yourrecruiters are then only
speaking to qualified candidates, but you've also interviewed
all of your candidates on asmart timeframe, so you're
cutting down your time to hire.
You're getting only qualifiedcandidates for your recruiters,
and you're doing it at arelatively low cost too, which
is the tertiary benefit.
(06:23):
At the end of the day, it'sabout having great people and
getting to them fast.
If you can cut some costs inthe process, too, it's not a bad
thing as well.
Pete Newsome (06:31):
I'm more than a little excited about this
evolutionary step becausetechnology has made recruiting
more difficult than it waspreviously.
I'll share what I mean by that.
I'm old, so when I startedrecruiting, we would run ads in
the newspaper.
We would have resumes faxed tous or mailed.
I was excited to check the mailevery day as a young recruiter,
(06:52):
if you can believe that.
But each resume you had youreceived as a recruiter meant
something you had to get themost out of that conversation.
You had to really hone yourskills on building meaningful
relationships and buildingrapport quickly with someone and
gathering as much informationas you can from a can.
So you really invested time inthat individual right and you
(07:13):
had to in order to survivebecause you didn't know where
the next resume was coming from.
And I was away from recruitingfor 10 years before starting
Four Corner Resources, which isnow 19 years old.
So it's been a long time sinceI've been back.
But in between, monstercom wasborn and CareerBuilder and
through those products andothers like them and now
OneClick Recruiting, it's becomethe opposite.
(07:36):
You get a flood of resumes forany job you post now and it's
taken that art that wasnecessary to become a good
recruiter completely out of theequation and it's become this
mess of a volume game where, ifyou get 500 resumes within an
hour or two which happens for alot of jobs as a recruiter, it's
(07:56):
just not realistic to gothrough this and the best
candidates can be buried.
It's first in, first out, andATS systems don't do a good job
of ranking.
You know all of this right, andanyone in recruiting does, and
the problem that I've beentrying unsuccessfully to solve
for years was how can I put ajob posting up and have some
(08:16):
sort of a screening emailresponse, right, hey, rune,
thanks for applying.
Confirm these five thingsbefore we put you in touch with
the live recruiter or schedule.
You live right To take away allthat kind of garbage on both
sides, right?
Candidates, there's no price topay for just clicking and
applying to a million jobs, andrecruiters don't have the
(08:39):
ability to go through them.
So it was really askingcandidates to take an extra step
in order to engage with therecruiter life, but that was
impossible to solve, which iscrazy.
You're going to don't tell methere was a solution I didn't
know about and you knew what itwas and existed all along,
probably, but I couldn't find it, and so now what you're
describing solves that in a muchbetter way than an email ever
(09:02):
could.
Right now, you're having a liveinteraction, or as live as it
can be, through AI, which Ithink counts, and everyone wins
right, the candidate getsimmediate feedback or gets to
hear from someone, therecruiters get to spend their
time in the most quality fashion, which was the goal all along.
So I say all of that to say I'mreally excited.
(09:22):
There's no question there.
I just want to let you know Ipersonally and professionally
think this is a solution that'sso needed in the market, and you
can't say that about everytechnology that comes out.
But let me ask you about thepotential downside to it.
So I'm Gen X, right, so I'mearly 50s.
(09:44):
You still have a lot of boomers.
I am not early 50s.
You still have a lot of boomers, and I'm not a boomer.
You still have a lot of those.
In the workplace, you havemillennials this is somewhat new
interacting with AI.
Tell me about the, the rate ofpeople willing to interact with
AI.
What are you seeing?
What is it?
What is the data show?
Varun Khurana (09:59):
Yeah, first of all, you mentioned something
called mail.
Pete Newsome (10:02):
I'm not really sure what that is, I'm just you
let me know Is that it wouldcome on a horse with a carriage
behind it and they would.
Yeah, so it was.
I'll tell you about that later.
Varun Khurana (10:12):
Yeah, I definitely think that.
One thing I will add to whatyou're saying is not just the
influx of resumes.
So you're seeing this with likeIndeed and LinkedIn are almost
50% of recruiter spend in the USnow and they're known for easy
applies, so the volume is higherthan it is ever before.
But the flip side of the AIboom has actually been for
candidates.
It's super easy to replicatewhat a company's ATS is looking
(10:37):
for from a job description.
Pete Newsome (10:39):
Two years ago at least your resumes.
Varun Khurana (10:41):
You could filter out the candidates with a little
bit of higher intent and usesome keywords.
That gave you like it wasn't aperfect filter, but it gave you
something.
Now, all those resumes lookalike too, so you don't even
know where to start if you're arecruiter, which is what is
making this a really good optionfor recruiters, where they just
get something, a first passfilter, now that an ATS filter
isn't working at all.
(11:01):
But just to directly addressyour question, around downsides,
we always tell companies thatplease don't use this for an
executive search.
We've seen companies try tointerview CFO candidates and I
was like that is a horrible idea.
Please don't do that, becauseit's really good for it's really
bad for roles where therecruiter has to sell the
candidate just as much as thecandidate has to take the job,
(11:23):
and I think that there's a lotof jobs that exist, especially
on the mid-tire levels of anyindustry.
It's a two-sided conversationand recruiters are going to be
able to sell in a way that AIcan never do, no matter what any
of these products are promisingyou.
I do think that the candidatereception was one thing that I
was really scared of, and it'sbeen overwhelmingly positive,
(11:47):
and one of the reasons has beenlike it feels like candidates
feel like they're heard and likethey're getting a response that
they normally wouldn't have had.
I think there are certainverticals where people are less
responsive than others To yourpoint.
I don't think it's an age thing.
It's actually more about thevertical you're serving.
So we actually see less of adelineation around like age or
(12:09):
gender or anything like that,but more so hey, if you work in
a warehouse versus you workactually in a construction
industry.
Construction actually loves this.
They love to talk on the phone,even with its, even if it's ai,
but we see something likeindustrial.
The response rates, dependingon the brand and like company
that they're interacting with,actually vary quite a bit, and
(12:31):
so I would say to sum that allup is like for higher precision
roles, higher cognition roles,like this is not a tool that
should be used, because it isactually very much on the
recruiter to sell the candidateon the first call.
I would say for the rest of theroles non-exact roles of the
(12:51):
world I think it depends on howmuch leverage your employer
brand has and how much goodwillyou have with the candidates is
also one of the big keycomponents there as well, if
that makes sense.
Pete Newsome (13:03):
It does.
I'm surprised about yourcomment about the age thing,
though I wish I could quote it.
I should have had it preparedfor today.
I read an article sometime inthe past few weeks saying that
Gen Z prefers to interact withbots versus humans, and who
knows, you see all kinds ofcrazy articles.
You never know what's true,necessarily but it resonated
(13:25):
with me.
I thought that makes sense,right.
I have four kids age 16 through24.
They all have phones that arein their hand 24-7.
I'm not sure that I've everseen them speak on the phone and
they certainly don't pick upwhen I call.
That's my first-hand experienceand I just think it makes sense
, right, that the younger youare, the more open you are to
(13:47):
technology.
But what you said makes senseas well, which is higher volume
positions.
I think this is a more naturalfit, for as a recruiter, I would
generally associate that withjust a pure volume of
applications that we receive,not because it's a different
level just from supply anddemand, which ultimately is tied
(14:08):
to the level.
So it's been the same, perhaps,but for a different reason.
Varun Khurana (14:14):
Yeah, one of the interesting things about the age
thing, which is we've slowlybeen indoctrinated up to this
point without kind of usrealizing it, like, my parents
have been using Alexa for yearsnow right in our house.
It never works, but it's beenthere, and I think we've moved
towards bot-based text.
And then we have these voicedevices we're talking to and
(14:34):
then we're seeing some stuffwith the LLM companies
themselves coming out withproducts like this, and I think
that adoption curves slowlycreeped into older generations
as well, to the point that a lotof them are very used to
interacting with this tech, evenif they don't directly know it.
And it's one of the earliestthings we used to measure,
because our calls would takeeight, nine seconds to connect
(14:57):
when we first built this out andwhere the tech was a little
more nascent.
And we would always try to geta good gauge on how people
reacted to when the bot firstspoke to them.
If we didn't tell them ahead oftime, if we just triggered a
phone call and there'd be someconfusion for a couple seconds.
But we were always reallyimpressed with how smoothly
(15:19):
people would understand this wasa bot, hear it and go with it
if we didn't tell them.
Now, obviously, as a company,we have all these measures in
place where we give peoplepractice calls and it's an
amazing candidate experience.
But even in those earliest days.
People just go with the flow andthey've been using this tech
for years and they just don'trealize it.
And that's what's crazy aboutthis.
Pete Newsome (15:39):
That's a great point.
We do use it and we don't eventhink about Alexa being a great
example of that.
I get a kick out of my wifeinteracting with it because as
Alexa fails to respond, her tonechanges and she thinks, if
she's like harsher with Alexa,we'll do what she wants, which I
think the only thing we use itfor is setting an alarm to get
up in the morning.
That's the extent of what Alexadoes for us.
(16:00):
Let's break it down so we'lluse your example of a warehouse
position.
I think that's a great one, aconstruction role.
So I put my job posting onIndeed.
Applications start to come intake over from there.
Varun Khurana (16:18):
What happens?
Yeah, absolutely so.
We're a company calledWayfaster and so our goal, as
you can imagine, is just speed,primary first, and the way it
works is you'll apply it.
That application info will getsent to an ATS and staffing is
full horn primarily and morecorporate.
It can be anything fromWorkable to Ashby, depending on
the type of company.
Pete Newsome (16:35):
As soon as that happens.
Varun Khurana (16:37):
What we'll do is sometimes companies will have a
default ATS filter, Sometimesthey don't.
One of the benefits is you caninterview every candidate, so
you don't necessarily need onewith Wayfaster.
So they apply, we trigger alink to each of those candidates
.
The company decides whetherit's phone or video, depending
on the role.
With a warehouse, it's morethan likely phone, and a big
reason why it's phone or videodepending on the role with a
(16:57):
warehouse.
it's more than likely phone, anda big reason why it's instant
is like we find 80% ofapplications actually come
between the hours of five andnine, and so it's when someone's
frustrated at their currentrole, especially a warehouse,
and they're like fuck this, I'mgoing to apply, excuse the
language, I'm going to apply toanother job and like we want to
get them as soon as they're inthat frustration point so that
(17:18):
they are able to really gothrough the application process.
Pete Newsome (17:20):
They take the interview out of that.
Varun Khurana (17:23):
We'll pull out.
We'll first onboard them, tellthem hey, this is an AI on
behalf of staffing firm thatwe're representing.
They'll run through a list ofquestions, Some of it which is
pre-populated, some of it whichis actually generated on the fly
from AI based on what thecandidate is saying.
From there we'll take out theresults, transcript recording,
(17:44):
some outputs.
We'll take all that data, We'llpush it back into the ATS.
We can set the filters on whichthere's an accept or reject
decision, and then we schedule afollow-up recruiter interview
with a real recruiter, if needbe and if they're qualified, and
then we schedule a follow-uprecruiter interview with a real
recruiter, if need be and ifthey're qualified.
So we essentially go fromapplication to the point where
they book their next call withthe recruiter in the span of
maybe 10 to 15 minutes.
Pete Newsome (18:05):
Love it.
So the job rec can come in atfive o'clock, the recruiter can
post the ad, go home for thenight and, in theory, come in
the next morning and they havemeetings booked with zoom.
Whatever phone call with actualcandidates who've already been
screened by the ai.
Is that it in a nutshell?
Varun Khurana (18:22):
yeah, that's exactly it, and for some
industrial roles you actuallycan actually just have them show
up to the job site by the nextday.
Because if you've automatedyour stuff around compliance and
background checks and you'relike we just need a light filter
in terms of checking a couplecheck the box items here, we can
actually go through that entireworkflow from within your ATS,
depending on how advanced yourrecruitment system is Now.
Pete Newsome (18:44):
Would that come from a preloaded list already
that exists in the ATS, or couldthat also work with
applications who are coming inlive for the first time?
Varun Khurana (18:53):
Yeah, so that's actually the beauty of it is we
do both.
So we actually a lot of thetimes.
One of the craziest things Ilearned about staffing is the
way it works at a lot ofstaffing firms is you'll put up
a role, they'll have spent allthis money on Indeed and you
need five people at a warehouseand they'll have 15 people apply
(19:14):
.
They fill those five peoplewith those 15 people, then
they'll have 70 other peopleapply and then they never talk
to them.
The next they fill those fivepeople with those 15 people,
then they'll have 70 otherpeople apply and then they never
talk to them.
The next time they fill therole, they just post that same
ad on Indeed, and it happens sooften and it drove us crazy.
So we actually tell companiestwo things.
We're like look, the firstthing we're going to do is we're
going to actually go justinterview everyone in your ATS
(19:34):
that's just on the backlog.
They may have switchedpositions, but this is valuable
data that you never talk tothese people and then from there
, every person who applies wealso interview.
So we actually do it both wayswhere we want to interview
companies existing ATS databaseand their backlog and also for
every new applicant that comesin.
The goal is holistically likeyou're never missing a good
(19:57):
application that couldpotentially be valuable to your
firm.
Pete Newsome (20:00):
So if we did the scenario where we said we want
to clean up our ATS and everystaff and company has a need to
do that, I suspect right, all mypeers and friends do.
And at Four Corner we haveroughly a million candidate
resumes dating back as long as19 years ago candidate resumes
(20:21):
dating back as long as 19 yearsago and I would estimate that
only about half of those areclean today, but the fact is
that is gold that's sittingbeneath the surface, that I
can't really get to for variousreasons and, at the very least,
it's impossible to keep up withpeople right, no matter how good
your intentions are.
It's impossible to keep up withpeople right, no matter how good
your intentions are.
It's just not practical For thescenario you outlined.
(20:41):
Just to run with that, those 70candidates that came in, you
really didn't have a practicalway to address them because
you've already filled theposition of yes, you want to
look forward and we all mean it,would love to do that in a
perfect world, but we're on tothe next job, right, and it's
just the reality of it.
So we lose money by pausing todo that as an industry.
(21:02):
You know that I'd love to cleanup my whole database, so if we
wanted to do that, would we justcome up with a list of
questions and give it to the AIto say, hey, look, this is what
we want.
We want to find out what thecandidates are doing today.
And maybe we set a call with therecruiter if they're on the
market, on and on, there's somuch benefit to that, and is
(21:24):
that?
But is that how it would work?
Varun Khurana (21:31):
Yeah, that's a lot of the time.
Staffing firms come to us andlook like they're a lot it's
still a very new technology andthey're worried about, hey, how
are candidates going to react tothis?
And we tell them, like looklike your response rate on your
past ats candidates can be waylower.
They change numbers.
They're happy in their new job,like maybe they're in between
things like your contactinformation is off, so maybe we
were able to reach half as manyas we would with new applicants.
(21:53):
But we tell them, like let'sjust try it out on your backlog
of candidates.
We can theoretically at leasttry to interview all of them and
even if 10% of them end upresponding and updating that
information, like you mentioned,it's still it's something that
you would have normally.
Not even that 10% isn't comingto you.
And so we try to go tocompanies and tell them here's
(22:14):
where we're going to do firstlift and then we can kind of
transition into new candidatesbecause I think they see the
value of hey, this has workedand we were able to get some
information intake and it wasn'ta hostile experience for the
candidate.
It was actually pretty good forthem, for the ones that did
pick up, and that's how we startthe relationship with most
firms.
A lot of the time, and youimplied this earlier.
Pete Newsome (22:34):
But I just want to clarify you never try to
pretend that it's not a bot,right?
That's communicating to theindividual, right up front.
That this is an AI conversation, right?
Yeah, yeah.
Varun Khurana (22:45):
I think we came to the conclusion.
It's like we don't think peopleare stupid, which is what I
think people who stop try topass off their AI as humans
assume of humans.
And we tried avatars at somepoint and, Pete, let me tell you
, people hated that.
Nobody wants to talk to anavatar Nobody, it turns out.
Pete Newsome (23:02):
Yeah, I listened to your demo.
It varies, steve, right?
Is that the name of your AIvoice?
Yeah, sounds real and we'regetting close.
Right, we're getting there.
Did you see the new Megan Foxmovie on?
Varun Khurana (23:17):
Netflix yet?
No, I haven't.
I'll have to check it out.
Pete Newsome (23:18):
Subservience.
Basically, it's a robot wholives as a caretaker, nanny and
let's just say the husband.
Let's just say the robot isMegan Fox and looks like Megan
Fox.
You can just imagine how thatgoes.
We're seeing this blend happenreally quickly.
But I think people don't wantto be fooled either.
That's just human nature youmentioned a few times.
(23:40):
So back to the database.
I just want to, because that issuch an impactful thing Give me
an idea before we move on topricing.
How does your pricing structurework, because that's a lot of
work.
I don't know where the heavylifting comes in on your side
from a data standpoint andsoftware, but generally speaking
, you don't have to get precisewith it.
But how does it work generally?
(24:01):
Yeah, I would say just the.
Varun Khurana (24:04):
It's not directly answering the question, but one
thing that we've been veryconscious of is that it's not
just the time you're saving fromthe interview.
With every interview there's apost review of the interview,
even if you give them atranscript of recording and all
that stuff.
And part of being way faster isthat we actually want to pull
out the key inputs the recruitercan just take a quick glance of
okay, this person has 22 yearsof experience, this role
(24:28):
requires two.
Let's just this is a no-go orwe just update this information.
So we try to post-process themand pull out the key inputs that
you're looking for there tosave the time on like what we
call like the post-processingthe transcript.
And the reason I bring that upis like that, I think, is like a
big thing for us is we're ableto automate that process.
So it's actually not that hardfor us.
(24:50):
Whether it's 15 candidates or athousand candidates, it's
actually relatively the samelift from us, except for the
infrastructure costs.
In terms of like automation,it's pretty much the same.
We transparently just chargebased on volume.
So if companies want to andthat is completed calls too, and
a completed call being anythinglonger than 30 seconds, and the
(25:11):
volume, as you can imagine,pricing scales down with the
number of calls that you'recommitting to for the year.
So if companies want to do100,000 calls, it's going to be
significantly cheaper than 5,000calls.
But that's how we price.
Pete Newsome (25:24):
You mentioned a few things earlier.
You mentioned targeting largestaffing companies and you also
mentioned corporate versus arecruiting firm.
So differentiate that.
But also tell me if there's acompany size that's really in
your sweet spot.
Varun Khurana (25:37):
No, I don't think we see companies that run high
volumes at really low volumes,like, for example, marketplaces.
Sometimes we'll interview tonsof people and actually have five
, 10 people on the team, andthen we also go up to really big
light industrial staffing firms.
So we don't have any sizeconstraints in terms of size of
(25:58):
company, like generally we'veseen our sweet spot is like a
firm with, whether corporate orstaffing of roughly about a
hundred people and above.
But I think the biggestdenominator is just like volume
of applicants because, and howmany positions you're looking to
fill, because at the end of theday, like you only need an
extra set of hands, whetherthat's through AI or human, if
(26:19):
you have enough applicationvolume coming in, and I think as
long as you have a large numberof applications, I think we're
a pretty good fit for you.
Pete Newsome (26:27):
Can you quantify that?
What would you consider a largenumber?
Yeah?
Varun Khurana (26:31):
I would say roughly, at least 500 to to 2000
a month is like at the veryminimum.
I think is targeting.
What about?
Pete Newsome (26:38):
per job.
Is there like a?
Was there a job that would be?
We talked about levels and Iassociate the levels also with
the supply of candidates.
Right, there's go hand in hand.
There's not gonna get athousand applicants for a CEO.
One click apply.
There will be, but we're goingto try to screen that out as
best we can.
And the job post but is costeffective for a job where you'd
(26:59):
get 20 applicants, or do youneed 200?
Varun Khurana (27:02):
Yeah, I would say it depends on the like real
answers.
It depends on how you're doingit today, which is, if your
recruiter, if you get sevenapplications and they're all
pretty good applications andrecruiters able to get to them
in an hour, then you don'treally need us.
If the recruiter is overwhelmedthat they have 500 applications
or 50 applications or whateverthat number is and they're like
(27:23):
we're having trouble filling therole fast because I can't get
to applications fast enough,then we're probably fit.
There's no hard and fast number.
Obviously, as you can imagine,if you're hiring people by the
bushel and like hiring 50, 100people a day, like you know,
it's going to be a little moreacute, just statistically
speaking.
But we just want to go toplaces where we can help the
(27:43):
most, as opposed to looking atany direct sizes.
But in terms of staffing, it'susually seen that benchmark be
like once you cross that 100person threshold or even like
lower.
We've seen like 25 better, likemore on the RPO side or more
light industrial, where they'redoing more with those 25 people.
That's where we've seen a lotof traction so far.
Pete Newsome (28:03):
Do you see a difference so far in acceptance
or willingness to use theproduct?
Varun Khurana (28:08):
on corporate versus staffing Sorry, say that
one more time.
Pete Newsome (28:12):
Have you seen a difference in just willingness
to step out and adoption, if youwill, of AI and corporate
hiring versus staffing?
Varun Khurana (28:36):
Yeah, I would say staffing using like a DMS or
like one of these heavyenterprise companies, and I
think in corporate obviouslythat's the mandate from HR but
the business kind of goes andlives on even if you're not able
to do that.
Like Domino's would love to getpeople in the door faster and
get people placed and have theirjobs and their stores, but
(28:59):
Domino's will live on even if ittakes them another two or three
days to do it, because theyhave an infinite pool of
applicants.
And I think that employer brandthat you have as a corporate
generally tends to do you somewonders and it's not mission
critical though it is like ahuge problem, whereas in
staffing like that is the wholebusiness model right and I think
(29:20):
that's where we see likerecruitment services is like a
little more acute thancorporates.
Pete Newsome (29:24):
That makes complete sense.
Listen, you mentioned whatdrove you crazy earlier.
What drives me crazy iscompanies who are willing to
just sit on job openings when wemeasure how fast they're filled
in hours, sometimes days atmost, and they measure in weeks,
sometimes even months, which iscrazy to me, but that's reality
.
So I completely I'm notsurprised at your answer at all,
(29:45):
knowing what I do about that.
It seems to me anyone who'ssending a lot of screening
offshore is you've rendered thatcompletely unnecessary or am I
missing something obvious?
Because I think speaking with abot or AI, or Steve in your
case, is a much betterexperience than speaking with
(30:06):
someone overseas where there's alanguage barrier.
Let's just call it for what itis.
You've really take all of thatout of the equation.
Yeah, it's funny.
Varun Khurana (30:15):
So we sell three big things to companies.
We sell them speed, quality andcost.
And when it comes to in the U?
S, when we take things off therecruiters place and put them
qualified candidates you onlyinterview qualified candidates.
We're usually selling them onspeed and cost, right, like
maybe you don't need that extrapair of hands.
(30:36):
When it comes to offshoring,we're actually often selling
quality as well, whereas, likethe AI out of the box, not only
is it faster and more costefficient, though that cost
Delta, as you can imagine, is alot lower offshore.
Actually, just the quality forboth the candidate and the types
of questions that are asked andthe responses generate are
actually significantly alreadybetter than a lot of offshore
(31:00):
interviewers, and I think we'regoing to, as the AI's cognition
gets better, like that gap isgoing to continue to increase
for us offshore.
So I maybe, pete, you can pointme to them, but I actually
haven't come across a lot ofstaffing firms that outsource
this stuff to offshore.
Pete Newsome (31:15):
Really.
Varun Khurana (31:16):
Yeah, very rarely we work with BTOs, but that's
for completely to interviewtheir offshore people, as
opposed to the process.
Pete Newsome (31:24):
You know it's almost necessary to compete
effectively in the VMS space.
If you live there, that'sreally hard to do exclusively
through American recruiters,just because of the cost, as you
mentioned.
So call it offshore, call itnearshore.
I see most of that first levelscreening happening there,
(31:45):
versus with US-based recruiters.
So I'm surprised that you'renot encountering I figured
that's who would flock to yourproduct first.
It was organizations like that,or maybe I think it's still new
.
I don't know how many clientsyou have so far, but I see this
evolution happening fast andI'll tell you I was at the
TechServe Alliance conference.
(32:05):
It just took place two weeksago.
Were you there out in Arizona?
Varun Khurana (32:09):
I missed that one , unfortunately.
Pete Newsome (32:11):
So, techserve, I usually go.
I wasn't able to make it thisyear, but the feedback I got was
that AI integration is a hottopic and everyone's trying to
figure it out.
So, look, I think you're in agreat space.
You're probably a very busy guythese days.
As a result of that, I thinkyou're solving, as I said
(32:32):
earlier, a big problem fornearly every staff and company.
There's any kind of volume,right?
Yeah, any kind other than, likeyou said, executive search.
I see that as an exception, butfor everyone else, man, this is
you're at the right place atthe right time.
So last question AI, future ofAI.
We hear about singularity.
There's a lot of scary thingsout there.
We've got drones flying overNew Jersey, not too far from you
, right?
It's crazy time.
What do you think?
(32:54):
Are you excited?
Are you nervous?
Are you both?
What do you see happening?
Varun Khurana (32:58):
Yeah, I can maybe give you two answers.
One is like in recruitmentspace, and then the second is
more so in the kind of generalAI spokes, I think, within
recruitment.
Like recruiters, I think enterbest at selling candidates and
there's a part of the economywhere that's never going to go
away with that human touch andwhether that's corporates,
(33:20):
staffing firms, no matter whatrole is, every staffing firm
knows it's always best to keep agreat relationship with your
potential candidates.
And I think that's going tocontinue to be true, no matter
how good AI gets, and there'scertainly, I think, other parts
of the stack that are going toget automated, especially as
candidates learn to leverage AIin a way that's more effective
(33:41):
for generating resumes orauto-populating texts or
cheating on assessments and allthese different things, and I
see this being a constant backand forth on AI versus AI.
When it comes to AI broadly, Ithink there's things I'm super
excited about and there's thingsthat I'm terrified about.
Right, like, we work at thecutting edge of models and it
seems like they're starting toasymptote a little bit without
(34:03):
better data, but you can imagine, with a lot of effort and a lot
of money, that's going to getbetter and unblocked.
And I do worry, like mostpeople in tech do, about what
purpose humans are going to playif these models get really
smart.
And I think that is scary,because I believe humans need
work and we like to do it.
(34:23):
Despite how much we complainabout our Zoom meetings and the
mundanity of a lot of it, Ithink doing Excel for six hours
a day it keeps us sane.
And I do worry about if weautomate some of these jobs,
like the AI line's always beenlike, we'll find new careers and
new roles will pop up and I'msure they will, and I think
(34:46):
that's maybe an unfoundedconcern, but it's something that
I worry about.
I also not to throw a newwrinkle at you, pete, but I'm
starting to see the pace of AIas it applies to robotics really
speed up, and so there wasalways this concern about these
real world jobs will always bethere, and now I'm seeing these
robots that can, like using LMsfor spatial awareness, do a lot
(35:09):
of retail jobs, do a lot of likefast food jobs and all this
stuff and that to me is actuallythe craziest stuff I'm seeing.
It's like these humanoid robotsthat leverage AI in a way that
I never saw coming in mylifetime, so that's always
freaks me out.
Pete Newsome (35:23):
It's happening with such rapidity, right?
I think that's the thing that Iworry about in the workforce
people being prepared for is itjust?
It happens almost overnight andfrom the minute chat GPT was
released, entire professionshave almost been rendered moot
and irrelevant.
I just I worry about it a lot.
I worry.
I look at you know young peoplein school right now and getting
(35:45):
degrees and things that aregoing to be completely
unnecessary.
We're spending so much time andmoney.
And then, like you said, therobots.
I mean every week it seems likeElon's putting a new video out
of his robot that he thinks isgoing to be a $20,000 product
within the next couple of yearsthat we're all going to have at
home.
It's bigger, faster, stronger,smarter than everyone else, and
(36:07):
you add dexterity on top of itand you go.
That's a problem.
Varun Khurana (36:09):
Huge problem Terminator.
Very real documentary.
It seems like I would say, whenyou speak of degrees, my one
piece of advice to any listenerwho happens to be listening to a
staffing podcast under the ageof 22, pete, I'm sure you've got
a great audience.
I'm not sure many of them arestill in school, but do not get
a.
CS degree, because that seems tobe like the way that we're able
(36:31):
to generate code seems to beespecially suited to LMs and
what they're able to do and notscale really well, and it's
freaking me out how easy it'sbecoming to build software a lot
of the times you mean my 22year old who's in grad school
for for cybersecurity Probably.
Cybersecurity is going to behuge because we're not going to
be able to tell what's real ornot?
Pete Newsome (36:52):
I think it will.
I think it will be.
I get what you're saying about,about programming and coding.
Is that?
And I've even seen I've evengenerated code, and I don't I'm
not technical at all throughthrough AI that I handed to my
developer.
He's like yeah, it's just amatter of doing what I need to
do to implement it from there,which is crazy, right.
Never would we have thoughtthat, even just a couple of
(37:12):
years ago.
But when it comes to recruiting,we're not going to solve the
world's problems At least I'mnot.
So I'm going to worry aboutrecruiting and you're young
enough, maybe you can.
But I think it makes us evenmore valuable as human
recruiters, because I think ourjob, ultimately, is to not
assess for things like hardskills right, that's relatively
(37:33):
easy and whether it's really agood fit right on things that
just I don't worry about AItaking from us, because you have
to still be able to separatewhat's said from what's implied
and all those things.
Can AI get there one day?
(37:53):
Probably, I think I'll be onthe beach by the time that
happens Hopefully not under it.
But yeah, I think we're goingto see a lot of changes that are
going to be challenging, but Ithink recruiters are safe for a
while.
I really do.
Varun Khurana (38:08):
I think so too.
I'm very bullish on the futurerecruiters.
I think they're just going tobe doing to your point like
different work and like moremanaging the soft skills and
especially I think Four Cornerdoes a decent amount of IT
staffing and I think there's themisalignment between when the
recruiter is doing a skillsassessment with the candidate
shouldn't exist, but someonestill needs to assess can that
(38:31):
candidate communicate well anddo some of these softer things?
And AI is never going to be ableto judge that in the way that
humans can, and that's bothendearing and good for you guys.
I think too, over the nextcouple of years, as, like AI, to
your point, eliminates a lot ofjobs that maybe don't have
those benefits.
Pete Newsome (38:47):
Yeah, it's going to make us better and you're a
big part of that.
I love what you're doing.
I can't wait to see how youprogress from here, and I'd love
to have you back on in a yearlet's see where what's evolved
since then, if you're willing tocome back and talk to me you
may be already from what I know.
Maybe you're the AI and I justdon't know it yet.
(39:09):
But, bruin, thanks so much, man.
This has been a lot of fun andeveryone thanks for listening,
and I'll put all your contactinfo so everyone can find
Wayfaster in our show notes andcheck it out.
It looks like a great product,so thanks so much for your time
today, yeah product, so thanks.
Varun Khurana (39:23):
Thanks so much for your time today.
Yeah, thanks for having me on,pete, appreciate you having me
on.
And yeah, it's justwayfastercom if you guys want to
check this out Awesome.
Pete Newsome (39:30):
All right, everyone.
Thanks for listening.
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