October 10, 2024 • 46 mins
James Mackey and Elijah Elkins sit down with Apriora’s Co-founder and CEO, Aaron Wang, to discuss how their product delivers and evaluates on-demand phone screens to applicants.
They discuss the similarities between autonomous cars and AI interview evaluations and explore whether AI products should focus on co-pilot functionality on screening calls or if new AI products should remove the need for recruiters to be present on the screening call, allowing the recruiter to only engage with talent that AI approves.
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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 am your host, james Mackey,joined again by my co-host,
elijah Elkins.
Elijah, what's up?
I'm doing well Good.
We also got Aaron Wang with ustoday.
Aaron is the co-founder and CEOof Apriora and he's gonna tell
us a little bit about hisproduct today.
Thanks for joining us.
Speaker 2 (00:20):
Excited to be here, james and Elijah.
This is gonna be fun.
Yeah, excited to be here, jamesand Elias, this is going to be
fun.
Yeah, it's going to be a goodone.
So I guess, to kick us off,we'd love to know, just like the
high level about your productand a little bit about you, like
(00:40):
how you came to start thecompany and where you are today.
Sure, aprior automates phonescreens and live video
interviews with an autonomousrecruiting agent, and so we help
enterprises and staffing firmsconduct thousands of interviews
every day and help thoserecruiting teams better
understand.
You know, out of the hundredpeople that applied, out of the
thousand people that applied,who are the top 5% that I should
really be speaking to andinvesting our recruiters' time
with?
And so that's a little bitabout the product and what we're
trying to build, nice, nice.
(01:01):
And so you started the littlebit about the product and what
we're trying to build.
Speaker 1 (01:04):
Nice, nice, and so you started the company about
two years ago.
Speaker 2 (01:09):
Yeah, it's been about a year actually since we
initially built it and sincethen we've been growing and
scaling like crazy, and so it'sbeen a fun ride.
Speaker 1 (01:18):
Okay, cool, nice.
And so what gave you the ideato start this company?
Speaker 2 (01:25):
Like what inspired you?
Yeah, start this company.
What inspired you?
Yeah, we had built anotherstartup in a similar space, in
the interviewing space, tailoredtowards candidates, and through
that experience we had found agraveyard, if you will interview
automation tools and learned alot about the different parties
within the hiring space.
Lot about the different partieswithin the hiring space, the
(01:46):
hiring manager and thecandidates, the interviewer, the
staffing firm and what all ofthese parties incentives are and
what they care about.
And with the advent ofmainstream generative AI, now is
a time when you actually cancreate extraordinary value for
all of these parties a lot bynew technology.
Speaker 1 (02:04):
Nice, and I saw also that you have a technical
background right as an engineer,and then you're also a VC.
You do some investment right.
Speaker 2 (02:13):
I do some investing.
I wouldn't say I'm a VC myself,but I'm a venture partner at
Pioneer and do some investing onthe side.
Speaker 1 (02:22):
Okay, awesome, awesome.
We're really excited to diveinto your product.
I'm actually really interestedin this use case, so I'm excited
to learn more here.
I suppose, just to kick us off,when you are discussing
essentially taking on, would yousay okay, taking on the
screening interview primarily?
(02:42):
Is it primarily text or is itaudio?
How does it currently work?
Speaker 2 (02:49):
Yeah, we have a few products.
Our first and most popularproduct is a video interview
solution.
Like how we're, a lot of yourinterviews might be a Zoom call
or a Teams call.
It's face-to-face Instead ofyou being on that call.
An autonomous recruiting agentwill actually host and interview
the candidate on that call andit's over our own video
(03:12):
conferencing platform.
So the candidate doesn't haveto install Zoom or Teams, but it
allows the employers or thestaffing firm to actually get a
sense of the candidate'sbehavior and soft skills and
during the interview thecandidate and the recruiting
agent have a live, personalized,genuine conversation.
Speaker 3 (03:31):
Got it.
I just want to jump in here toclarify something, aaron.
So basically, when they'redoing that video interview,
they're not interacting withlike a live generated avatar,
like people might have seen,like a video of I don't know a
newscaster or something created.
It's more, there's an avatarimage down in the corner right
(03:54):
and but they are getting thatlike live voice interaction, but
it's not some ai generatedperson on the screen right.
Speaker 2 (04:02):
Yeah, you've got that exactly right.
We found that and happy to chatabout this more.
But what we really care aboutis the candidate experience, and
what we found is thatgenerating a live avatar
throughout an interview degradesthe candidate experience.
Although that technology issuper cool, it's not what the
candidate's like, and so you'recorrect.
(04:24):
During the video interview, weessentially have a profile
picture of the candidates like,and so you're correct.
During the video interview, weessentially have a profile
picture of the recruiting agent,so that when they're having
that conversation, thecandidates can feel comfortable
and give their all during thatinterview.
Speaker 3 (04:36):
Nice, yeah, thank you for clarifying that.
Speaker 1 (04:39):
So it's voice AI, so asking questions and there's a
conversation, but it's aconversational AI.
Okay, so how's that going?
Because sometimes when I'musing voice ai, it still can be
pretty clunky.
You know, particularly whenthere's like stuff like pauses
and whatnot people talk adifferent cadence, stuff like
that.
How do you smooth over thatexperience?
How do you make that work?
Speaker 2 (04:58):
yeah, I think the the tug is really between two
aspects of the technology.
There's one, so there are twothings that make a great
conversation.
Two things are latency righthow long does it take for me to
respond to you after you'vefinished your response?
And the second is intelligenceright.
Are you going to remember whatI said three minutes ago and
(05:21):
bake that into your nextresponse?
And so with both of those, weor I should say we built a lot
of these technologies from theground up, and that's allowed us
to control these aspects.
We also have really greatpartnerships with the folks at
OpenAI and Azure, allowing us toreally utilize the best that
the AI technologies have tooffer.
(05:42):
You mentioned that.
I have my engineering and AIresearch background and that
really helps, because we trulyunderstand the technology and
we're able to make thesetrade-offs so that we can
maximize the candidateexperience.
It just feels like a natural,fluid conversation.
Speaker 1 (05:59):
For sure.
Do the candidates have theability to respond by text, or
is it only voice?
Speaker 2 (06:04):
And do the candidates have the ability to respond by
text or is it only voice?
During the interview, theyrespond over voice, both in the
video interviews, and we alsohave a phone call product as
well the second that you apply,you'll get a phone call, and so
that's growing in popularity.
We do have a portion where theycan actually respond to a text.
For example, let's say youapply for a job and our
recruiting agent calls you butyou're not available.
(06:26):
The recruiting agent willactually send you a text and say
, hey, it looks like I missedyou.
Speaker 1 (06:32):
I'll probably give you another call in the next
couple of hours if that worksfor you.
Oh, that's awesome.
I really love that.
Speaker 2 (06:38):
Yeah, increase the essentially the engagement of
the candidate and trying to makethat high quality.
Speaker 1 (06:48):
So is it primarily in terms of how your customers
engage?
Do you see, as soon as somebodyapplies, do most customers want
them to just have the abilityto start the screening process,
or do you see customers want toessentially do an initial review
of the profile and then havethem decide from there if they
want to screen the candidate?
How do you see it worktypically?
Speaker 2 (07:09):
what's really unique about what we offer is that
companies now have the abilityto engage with every candidate
at scale, and what that means isthey're now able to widen their
talent aperture and not onlyconsider the folks that had a
4.0 and went to a great schooland had the best career
(07:33):
backgrounds, but also those that, hey, maybe they didn't have
the most opportunity throughouttheir career, but they have the
skills and they have theknowledge to prove it and be a
great employee.
They have the skills and theyhave the knowledge to prove it
and be a great employee, and weshouldn't be overlooking those
folks.
And the way that is articulatedin the use cases of our
(07:58):
customers is all the timethey'll just interview every
candidate because it's just socost effective and it's a way to
access talent that maybe yourcompetitors aren't accessing
today, aren't accessing today.
Speaker 1 (08:07):
So, that being said, it's like this tool is not
evaluating the talent per se.
It's collecting the screeningdata and then allowing the
hiring team to make, essentiallygiving them a lot more
information to evaluate anddecide if they want to move
forward in the process.
Is that accurate?
Speaker 2 (08:20):
Yeah, so after every interview, the AI recruiting
agent will write up detailedfeedback notes and, for example,
upload that or sync that toyour applicant tracking system
so that, for example, yourrecruiters can make a
well-informed decision.
The AI recruiting agent todaycan score, so you can give it a
rubric for the things that youcare about for that particular
(08:42):
role or requisition and we'llscore it at the candidate based
on that interview interaction.
And what's great about that isit allows the recruiters to
focus their time on thecandidates that do meet the
requirements of the role, asopposed to those that maybe
don't.
Speaker 1 (08:57):
So basically, the hiring team can filter based on
certain criteria to identify thecandidates that match best on
the filters or whatever is that?
Speaker 2 (09:09):
exactly right.
So, for example, maybe there'sa, let's say, a light industrial
role right where you need to beauthorized to work in the
united states, and you need to.
You know it's located in boston, massachusetts, so you'll be
able to drive up to Boston everyday.
The AI recruiting agent can askthose questions and then tag
that applicant as okay, great,they're authorized to work in
(09:30):
the US and they're able to workin Boston in person, and that
just makes it easier for therecruiter to go back into their
ATS and say, okay, great, I wantto talk to those folks because
they meet the criteria.
Speaker 1 (09:43):
Yeah, folks, because they meet the criteria, yeah,
yeah, because, like so.
With this tool, it's reallywhere it saves time is ensuring
that when recruiters or hiringteams do speak with somebody,
they're much more likely to makeit to the next round.
It's not necessarily savingtime at the very top of the
funnel because the recruitersstill have to go through all of
the candidates.
Essentially, it's like morelike that one layer deeper
(10:04):
within the funnel where it'ssaving time.
Is that accurate?
Speaker 2 (10:08):
Yeah, and I think there's more to it.
That is because we score everyinterview.
You can, let's say we scorethem out of 100,.
For example, you know, as arecruiter, I can set up an
automation.
You know, we have an automation, for example, with many ATSs,
and so the second someoneapplies, they can get access to
an interview.
They take that interview.
That data gets automaticallypopulated into their ATS the
(10:32):
employer's ATS and that includesa score.
Speaker 1 (10:39):
And so they can filter and sort based on that.
Okay, cool, all right.
So I'm just trying to think Imight be a little bit redundant,
I just want to make sure I'mdialing in.
It is providing a very clearscore for each interviewer, but
that so that, and I guess that'sbased on if they match the
criteria.
But then you start to get intoAI making like the doing the
(11:08):
evaluation versus just packagingdata for to make it easier for
the hiring team to evaluate.
So I guess my question is onthe.
You know, we I just had a reallyinteresting conversation with
steve bartell, ceo of gem, andwe were talking about ai's role
in recruiting and the differencebetween like essentially
enablement and packaging dataversus doing the evaluation
directly, and so he was talkingabout like just like the legal
(11:30):
kind of gray area, so to speak.
And so I'm just curious how youthink about that.
And with that scoring, do yousee that?
Well, no, it's just likescoring based like are you
remote or in person?
Those are like very basiccriteria.
It's not evaluating based offanything deeper.
Speaker 2 (11:48):
I'm kind of curious how you think about that in
terms of your product.
Yeah, so we're firm believersin human in the loop.
What we don't do is we don'tallow at this time the
recruiting agents toautomatically create a
disposition of the candidate andhave that actually be synced to
the ATS.
We think of the evaluation as adata point.
We tell you, hey, this personhas, let's say, an 80 in
(12:09):
communication skill.
And then let me tell youexactly why I gave them an 80,
right, because three minutes ofthe interview they had a really
great explanation of this, butthree minutes of the interview
they kind of had some troublediscussing this particular
experience at their last rolehere.
And so I think evaluationcertainly plays an important
role in bringing value to therecruiting teams.
(12:31):
I think it's important to makeit both have human in the loop,
but also make it explainable anddata-driven.
So don't just give me a score,but tell me, hey, how did you
come to this?
And let me make my own decisionon the actual candidate.
Speaker 1 (12:45):
Yeah for sure.
Yes, it's an interesting topicright when people are trying to
figure out exactly what AI'srole should be and then also, as
legal cases start to happen.
Right Right now, for instance,what's going on with Workday?
I don't know if you guys arefamiliar with that there's a
huge class action lawsuit ontheir AI discriminating upon
(13:08):
race, age and whatnot.
Now, who knows if there's anyvalidity to it?
Right, we don't know yet, butthat's something that's current
and a lot of folks are saying.
Steve was saying that'sprobably going to set a
precedent for future years tocome.
But yeah, it's reallyinteresting.
We're speaking with some CEOswho are very aggressive and
others that are very reserved.
I would say Greenhouse, the CEO, from what I can tell, seems to
(13:30):
be incredibly reserved.
Oh yeah, but you got Workable'sCEO who we had on Elijah, what
like two weeks ago.
Speaker 3 (13:37):
Yeah, nikos.
Speaker 1 (13:37):
I think, yeah, workable's incredibly aggressive
, yeah, I mean they'reimplementing AI in every part of
the funnel for talentacquisition and employee
experience.
They're an HRIS right.
Speaker 3 (13:52):
They built one within the last couple of years, but
they started as an ATS only.
Speaker 1 (13:57):
Yeah, they just started that.
So everything's sourcing to HR.
They're just going all in, itseems.
But yeah, I'm in the same.
I think philosophically, Ithink about it the way that you
are.
It's like thinking aboutbuilding a product of ultimately
what's going to create the mostvalue for the user and just
pushing aggressively in thatdirection, and I think getting
(14:18):
into evaluation territories isultimately more valuable, and
then just like putting insafeguards in place to make sure
that we know exactly what theai is actually evaluating off of
is really important.
But yeah, I think this is thefuture.
Speaker 2 (14:30):
really I think there are different philosophies for
how you want to approach newtechnologies.
I think you see that in everyplatform ship, whether that's
the cloud or mobile, of course,the internet and the question
you have to ask yourself as aleader is at what point do you
put your chips in and how much?
And what are just theopportunity costs of doing so
(14:54):
and, more importantly, not doingso?
And we're much more of theopinion that we think generative
AI is here to stay, and it'svery hard to imagine a world
where there's going to be lessAI in recruiting in the next
five to 10 years, and so it'smuch more important to find
those value cases, those usecases where customers will find
(15:15):
value, and doing so in a safemanner, to ensure you're in a
good spot.
Speaker 3 (15:21):
I think it's really interesting, too right.
If you've worked with startupsbefore, oftentimes you're
dealing with first-time hiringmanagers, first-time
interviewers, and for somereason, companies seem to feel
there's less risk from havinguntrained interviewers that
could be asking highlyinappropriate or even illegal
(15:42):
questions and they feel likethere's more risk from that
interviewer or that there's lessrisk from an interviewer doing
that and giving an evaluation, agenuine evaluation that impacts
hiring outcomes, versus an AIthat can be like fully audited,
like where you can refine itover time, like you're saying,
(16:03):
aaron.
You can know why it's givingdifferent scores.
You can also make sure itdoesn't ask illegal questions.
That, to me, is much lower riskthan the bias you're going to
get from an AI.
It seems like it would bepotentially lower risk than all
the untrained interviewers whocould essentially say whatever
(16:24):
they want and put your companyat risk.
Speaker 2 (16:27):
And I think you mentioned a good point there is
that it's for an AI.
It's measurable, right.
You can do statistical analysesand figure out what is the kind
of bias we're looking at today,Because you can measure it and
you can plot it over time.
You can take different actionsto lower that over time, right.
That's much harder to do withsomething you can't measure,
(16:48):
like a human interviewer thatmight be the first time
interviewing, or they woke up onthe wrong side of the bed, or
they didn't have a cup of coffee.
If you can measure it, it'smuch easier to be able to
control it, and so I think a lotof the big players that you
mentioned are going to be caughtup in these larger scale
litigations.
I think a good comparison isthe autonomous driving market.
Speaker 1 (17:12):
I was thinking about this yesterday.
I think that's a fantastic.
It's a very relevant comparison.
Speaker 2 (17:18):
Yeah, and you see that I don't know if you guys
have been in San Franciscorecently, but I'm sure a lot of
the listeners have.
There are Waymos everywhere,people are taking Waymos left
and right.
They're completely autonomous.
People love it.
People pay more for Waymosbecause they can take meetings
during the car right, it's agreat experience and yeah, you
definitely have some casualties,like Cruise, for example, got
(17:40):
dragged in the mud in the newsfor a bit, but in the long run,
that's probably going to be thefuture of driving it is.
Speaker 1 (17:48):
You know it's like.
The other thing, too is likewhen you're building a product,
particularly at an early stage,it's like at the rate it is
moving.
Do you really want to build aproduct for, like where you are
today or where we've been forthe past six months, are you
building the product of thefuture?
like yeah and it just seemsobvious to me.
It's like we should be buildingproducts that are like actually
going to represent what thefuture holds.
Yes, there are going to beroadblocks potentially, or just
(18:12):
lessons learned is going to berisk, but that's where the
opportunity is as well.
That's where we get like thebiggest lift and are creating
the most value.
So I think you know startupsneed to be aggressive here.
I think, aaron, I think whatyou're doing is smart.
I think that you have to pushin this direction.
I think there's a ton of valuehere.
(18:33):
I'm curious, though when areyou seeing the best traction now
?
I know you raised money.
I think back in May you raiseda couple million bucks, right?
Speaker 2 (18:43):
Yeah, our last round was 3 million around that time,
and I think that's a question wethink a lot about, because I
think this is a broadgeneralization.
But I think the point is clear.
It's like, every company hiresand thus it's very important to
(19:05):
focus, because you need to pickone ICP, focus on them, solve
their problems, because not allthe markets will be ready, like
I think a very obvious exampleis executive search.
Right, that's not really aninterviewing or a screening
problem and it's more of asourcing problem and finding
those right people, so thatmarket's not quite ready.
So the question is okay, whatmarkets are ready?
(19:26):
And a great way to look at thatis just sort by value, right,
or I guess the inverse of that,which is pain, right, who is
spending the most oninterviewing and in screening?
Today we found a lot of successin the external recruiting side
of things.
That's been very good for usand that's in their entire
business, right, and it's a verygood for us and that's in their
entire business, right, andit's a very market sensitive
(19:47):
business for them.
And so if you can introduceautomation that actually brings
value to them and saves themtime, increases placements for
them, of course, software isgoing to be much cheaper than
any type of human-based labor.
That is a lot of value that youcan provide and we've had a lot
of success there.
Speaker 1 (20:06):
Okay, and with these staffing firms are you seeing,
is it more like on the SMB,mid-market or enterprise?
Speaker 2 (20:12):
players, yeah, so we've been really excited to be
working with folks across theboard.
I think the bigger there's avery clear value add for
companies like in the mid-marketbecause they it's very hard to
scale like a staffing businessto the level that they want to.
There's just so thin margins.
(20:34):
Even if you look at the 10Ks ofpublic staffing firms today,
you'll see folks that are doing6 billion in revenue versus 18
billion in revenue annually.
They're taking home the sameamount of profit or being very
close to break, even thoughone's doing a 3X the amount of
annual revenue.
And we're seeing a lot ofuptake in the mid-market section
.
Speaker 1 (20:52):
That's awesome and this might actually be the same
for in-house teams too.
We can just look at my agents'design for now.
The specific types of rolesthey fill, I'm sure in the
industry they serve, I'm sureimpacts it.
We were speaking.
It was David Tell at Qual whowas saying you're seeing a lot
of in light industrial.
He was just seeing a ton ofdemand.
What types of staffing agenciesare you seeing?
(21:15):
Is it like temp hiring, permplacement?
What types of industries androles are they working on?
Speaker 2 (21:21):
Yeah, it really has been across the board, which is
really exciting.
It turns out, when you havesomething that is, you know, an
intelligent and intelligentagents, what you find is that if
they can do, if that agent canscreen for a senior software
engineer or a senior NETdeveloper, then it can probably
(21:41):
ask the questions required toscreen for a warehouse associate
or a forklift operator, and sothat's been really exciting for
us.
A lot of our customers todayare in, for example, it staffing
, light industrials, hospitality, healthcare, a lot of temp, and
I think that these cases areextremely obvious because a lot
(22:04):
of those tend to be much morehigher volume.
Speaker 1 (22:07):
Got it, so you to be much more higher volume.
Got it, so you see more of thehigher volume side.
Do you see this as?
Where do you think a productlike this fits in with maybe
lower volume?
I mean, I think lower volume.
The products that we're seeing,like we brought on CEO of
BrightHire and Pillar andthey're doing like internet
(22:32):
interview intelligence platforms, where it's like AI co-pilots
that are doing a reallyfantastic job of packaging data
to help companies evaluatefaster these are, I think,
primarily on lower volumesearches.
There could be like a b2bgrowth stage mid-market tech
company, something like that.
They're hiring a softwareengineer.
Maybe they have 10 candidatesin the funnel.
You know they're leveragingBrightHire to.
It does, of course, like the jobdescription generation, custom
question generation, which isall very basic stuff, and then
(22:54):
packaging the data effectivelyand then also give like some
gong-like feedback on wherethey're like interview quality,
how good are the interviewersdoing?
Are they starting on time?
That kind of stuff.
So it's pretty cool.
I do a lot of.
They have a lot of featuresLike.
(23:14):
Like do you see your productfitting in on some of those
lower volume uh use cases aswell?
Or like how do you I'm justcurious if there's an
application for what you'redoing and some of those other
use cases yeah, I think there'scertainly.
Speaker 2 (23:22):
I think there certainly is we.
The value prop is going to be abit different because hiring
for value prop is going to be abit different, because hiring
for those folks is going to be abit different.
Again the incentives aredifferent.
So for those folks, if they'rehiring a senior software
engineer in San Francisco andthey don't hire too many of
those then it turns out whatthey really want is someone
that's super high quality, andso having an AI recruiting agent
(23:47):
that can do that supertechnical, in-depth interview
ends up being really useful forthem, because you can
essentially bubble up a veryin-depth technical screen to
that first interview, to thatfirst interaction.
You'd love to know if someoneis technically competent right
away, but it's really difficultbecause you know your engineers
are, you know, very well paidand quite expensive, and so
(24:09):
they're expensive, but they alsodon't have a lot of time and
you pay them to do.
You know to code and buildproduct.
Imagine where ai has read allthe documentation, understands
your tech stack and understandsthe tech stack that's on the
candidate's resume, and they canhave a really in-depth
technical conversation.
That ends up being a very, veryinteresting value prop for
those folks.
Speaker 1 (24:30):
Yeah, and that's like what I'm getting at too.
I see a very strong use casefor lower volume searches as
well, because I think that itwould make a lot of sense for,
when people are applying inbound, to just be able to open up a
screening call so that whenpeople are looking at resumes
(24:52):
there's just so many screeningcalls where you're just wasting
time.
Yeah, we have the salary rangeposted on the job description
but somebody doesn't look.
It's like okay, we got to dothat.
Or are they available forhybrid or are they if it's a
salesperson?
Do they work with likemid-market enterprise customers?
Are they available for hybridor are they if it's a
salesperson?
Do they work with mid-marketenterprise customers?
Are they primarily SMB?
There's just stuff that we haveto know that even an experienced
recruiter if you ask those upfront and you can get off the
(25:14):
phone in five minutes, it'sstill just a big waste of time
where it's like you can improvethe conversion rate from that
initial conversation with arecruiter to the hiring manager
if you have more informationgoing into that call.
It's just interesting becausemost of the application of
product your product and then acouple of similar they're not
exactly the same products we'veseen.
(25:34):
It's like we're on this likehigh volume side as the primary
use case we're seeing.
So it's just it's interestingto me.
I see this incredible use casefor low volume searches as well
that I don't know.
Speaker 2 (25:45):
Yeah, I think what you bring up there is important
is we're not only increasingbasically the quantity or the
bandwidth that your recruitingteam can handle, but also just
increase the quality.
Your recruiters it's unlikelythat they have a super
experienced background inengineering, right?
I mean, this is a technicalhire.
Or they were maybe never ledgo-to-market if it were a sales
(26:09):
hire.
And so what does that goodsales hire look like?
Well, it turns out that the AIactually knows, because it's
read everything there is to knowabout what is a good sales hire
and what experiences are goodto have.
And if you can give the AIrecruiter, for example, the job
description and the company'sculture, then the AI recruiter
(26:31):
can also help sell the role andthe position and again just
increase the quality of everyinteraction that you're having
with the candidate.
I think is something superspecial.
We're not hiring hundreds ofpeople every month.
We actually use our own product, our own recruiting agent, to
do a lot of the hiring, In fact,the last two people again, so
(26:52):
we're pretty low volume.
Our last two folks we hiredwere both using our AI
recruiting agent and both ofthem have turned out exceptional
, right?
One of them's an engineer andone of them heads up our
go-to-market and so sales hiring, so I think that's really
exciting and heads up ourgo-to-market and so sales hiring
, so I think that's reallyexciting and we are hiring.
So feel free to everybody outthere, feel free to uh, yeah,
(27:14):
yeah, I mean that's uh, that'sgreat.
Speaker 1 (27:15):
It's like when you're growing as a startup too, it's
like you need to hire.
This is a product that you needfor, arguably like the most
important part of your business,like your team is gonna for a
product.
It doesn't matter what kind ofcompany.
Your team is fundamental toanything you're going to build
and any success you're going tohave.
It's the input for any level ofsuccess.
But building anything great ofvalue in the world.
Speaker 2 (27:39):
No, that's right.
Yeah, I think an important noteis what's best and what you're
looking for in that next hire,and so our hope is to get you to
a yes as soon as possible.
Get you in front of thecandidate, that is great, and if
you're, let's say, youracceptance rate is at 1%, then
let me just put that onecandidate in front of you and
the other 99, you know, notdirect them to you, not have you
(28:01):
have to filter through everysingle one of them, have a
conversation with every singleone of them.
Speaker 1 (28:05):
Yeah, for sure.
So I've been monopolizing a lotof the questions.
Elijah, Do you have any burningquestions right now?
I could keep going all day onthis.
Speaker 3 (28:15):
Yeah, I have a couple of questions, but we did the
sourcing technology one theother day that I got to geek out
on and dominate things, so Iappreciate that.
I'm curious, aaron, how do yousee things shifting in the
market?
So we've got the early stagevideo interviewing tools that
were mostly kind of one way.
You've got companies likeSparkHire and there's a couple
(28:37):
other big ones that I'm notremembering their names.
Then you've got this justwithin the last few years
probably, companies like Jamesmentioned on the interview
intelligence side, so likeBrightHire, pillar, metaview, et
cetera.
How do you see Apriora comingin and fitting into that?
Are those companies, theinterview intelligence going to
(28:58):
build their own AI agents, doyou think?
Or are they going to want tomaybe I don't know create an
agent, but actually it's Appriori in the background that's
actually delivering.
I'm just curious how you seethese shifts happening and your
role in that.
Speaker 2 (29:16):
There are a lot of companies that do talent
intelligence or interviewintelligence, and that takes a
lot of times the form of havinga note taker on the call right
and being able to essentially belike a gong for interviews.
I think there are a lot ofthose types of companies.
It's a fantastic product.
(29:38):
Today, we really, we reallywant to skate to where the puck
is going to be and not where itis today.
I think today, you know thatrecruiter might not be on that
call, or at least they're goingto be a lot less recruited being
on those calls, because they'regoing to be instead speaking
with people that are actuallyqualified and not spending time
with people that might not be.
(29:59):
And so we're really, reallybullish on complete autonomous
agents, and that's what we're,you know.
Of course, that's what we'rereally, really bullish on
complete autonomous agents andthat's what we're.
Of course, that's what we'rebuilding out and what our
customers love about us today.
And again, it all goes back tovalue, right?
If we look at that Waymoanalogy, these interview
intelligence platforms would beUbers.
They're great and they're veryconvenient, they're very helpful
(30:22):
, but there still needs to be adriver there, right?
Speaker 1 (30:28):
do you want to build a red box or netflix like?
Speaker 2 (30:31):
exactly, exactly and and I think it's particularly
this way is actuallyparticularly interesting,
because what you do is becauseyou have a driver there right,
and you again the you mentioned.
it's very hard to measure howgood that driver is, you just
get in the car Right, and butyou'd be, you'd feel a lot safer
(30:51):
if you knew that, hey, this waymore car has done literally
millions and millions of milesand has never crashed.
So statistically it's just,you're just a lot better off.
I know I don't want to, I don'tmean to go on a tangent here,
but a couple of decades, manydecades ago, elevators used to
be manual.
Right, you have an elevatoroperator actually standing in
the elevator with you and movingyou to the floor.
(31:12):
But it's pretty hard to imaginethat world today.
It would feel almost unsafe.
And so for us it's aboutskating to where the puck is
going to be, and we think thatwhere that puck is going to be
is going to be an autonomousagent for hiring.
Speaker 3 (31:25):
And how are you going to work with the recruiters?
I'm sure taxi drivers goingwith your analogy aren't excited
about Waymo, and some of themin this case, some of them may
be buyers for the technology.
So I'm curious how you seerecruiters adopting the
technology.
Lots of their time is spentdoing screening calls.
Recruiters adopting thetechnology lots of their time is
(31:47):
spent doing screening calls andthey're even struggling, I
think, sometimes to want toadopt either a note taker or
BrightHire, one of theseinterview intelligence tools.
Yeah, how do you see that going, at least for the recruiters
who are currently using yourproduct and, in the future,
How's it going to help them andwhat's their relationship with
it?
Speaker 2 (32:02):
Yeah, so in the short term, I still believe that a
recruiter is more likely to bereplaced by another recruiter.
You shouldn't be scared of AItaking your job tomorrow.
You still are going to need arecruiter to facilitate a lot of
those interactions.
For example, hey, I talked tothe hiring manager and I had an
(32:24):
intake meeting with him or herand these are the interview
questions and these are thethings that they care about.
Here's the rubric.
Then the interview agent can gooff and go do that interview,
and so I think that recruiterswill still be replaced by
recruiters.
Maybe a recruiter that's usingAI will be replaced by those
other recruiters, and I thinkthat's the place of technology
(32:49):
and I think recruits today stillhave a very valuable skill set
and we want them to focus on themore human aspects of
recruiting going to careerevents and focusing on employer
branding things that are reallyhard to automate and candidly.
They probably want to focusmore on that anyways, because
it's just more branding rightThings that are really hard to
automate and candidly.
They probably want to focusmore on that anyways, because
it's just more human right.
(33:10):
There's nothing human aboutgoing on eight to 10 screening
calls a day, right, or trying tochat with someone that you
don't know much about thatdomain, right?
A lot of that just can and webelieve should be automated so
that you can focus on doing thetasks that you'd love doing as a
recruiter.
Speaker 1 (33:30):
I agree Honestly.
I own an RPO company, embeddedRecruiting Agency and we've
worked with over 200 customersin the past decade A lot of
companies, a lot of startups,growth stage companies, a
handful of enterprises,primarily in the tech industry,
but not only and I honestly feellike if you're a good recruiter
, you should be screening out80% of the people in your phone
(33:53):
screen and that's if you'redoing a great job sourcing.
It should be more if you have ajunior to mid-level sourcer, if
you have a great senior levelsourcer, a lot of our customers.
We're passing on 80% of thepeople on first round.
The reason why I think that alot of recruiters they do see
their role as sales, but whenyou really put on that business
(34:15):
owner executive hat, you got toremember it's not just about
filling roles, it's aboutbuilding value and building a
team that's going to scale asuccessful company and add value
to the customer.
That's a lot harder than justgetting somebody in the seat and
the role of recruiter should beone hand you're beckoning,
you're pulling people in, theother one you're pushing away,
right, you're putting up thebarriers, right, and so it just
(34:38):
like again for our seniorrecruiters.
They had to get really good atevaluating quickly and they
spent a lot of their timejumping on the phone with a
candidate saying all right, look, I'm happy to answer your
questions.
I ask my questions in order,starting with a high level fit,
and we only get into the detailsif it actually makes sense,
because I don't want to ask youall these details.
(34:58):
It doesn't make sense to gointo that and we'll just do it
in order to make sure it makessense for both of us to continue
the conversation and I don'tknow 20 to 30 percent of the
time off the phone in the firstfive minutes and then you got
another 20, 30 percent of thetime that you're off the phone
at 15.
And then you got probably less,around 20 percent of the time.
(35:19):
You're hopefully trying toscramble to get everything in
before the call and you'rebuilding that relationship by
the end of the call, talkingabout the process and next steps
and everything like that.
But I'm just thinking, yeah, asa senior recruiter, somebody who
knows what you're doing, if youcan in a meaningful way
increase your conversion ratefrom phone screen or from your
(35:39):
first interview.
If the product is doing thescreen, it eliminates and
collapses the process.
But from that initial humaninterview to the next round.
If you can increase thatconversion rate, that's huge.
If you're doing it in theappropriate way, like I think.
A lot of times conversion ratesare like people think about
them the wrong way in arecruiting funnel, I think like
(36:00):
more is better.
Speaker 3 (36:00):
No honestly, a lot of times like west is better
there's a balancing act.
Speaker 1 (36:04):
If it's too low, it's like are you setting up the
right people?
If it's too high, like are youjust people through?
Oh, it's nuanced, but but yeah,anyways, like it just would
save a lot of the time and youwant particularly you're saving
the time as your senior levelresources, which is like your
senior level recruiter or yourhiring team, and there's like
metrics that daniel tape puttogether and like growth
companies hiring and a lot oftimes hiring managers are
(36:27):
spending 50% or more of theirtime interviewing On average.
I was talking with MattCaldwell.
I don't know if you guys knowMatt, but he scaled a company
called Rocket Power, an RPO firm, from a few people to over 400
people and he sold a historicamount of money to Kelly
Services and yeah, anyway, samething.
He's looking at it essentiallythe same way.
(36:47):
They basically calculated and,believe it or not, there was
around 75 hours on averagecompanies were taking per hire,
and those are the later stagecompanies, right, ones that you
would have heard of, which is aninsane amount of time.
So think about that much timeon payroll of executives.
(37:07):
And that's not even coveringthe cost of working with an RPO
agency job postings, whateveryou're doing to fuel that growth
?
That's insanity.
So if you can leverage atechnology to improve the
quality of your pipeline forevery human touchpoint, that is.
(37:29):
This is a seven to eight figureproblem for businesses and they
don't even realize it.
Speaker 2 (37:35):
Yeah, I can just speak from my own experience,
because we are hiring and when Ipost a job, I'm going to get
hundreds and hundreds ofapplications and resource them
and try to get them to apply andI make an effort to meet the
candidates that I like.
But there's just no way thatI'm going to be spending or any
of our employees are going to bespending hours and hours
(37:56):
looking through every singleresume and making the right call
on every single one.
That takes a lot of time.
So if I could just have, in theclick of a button, have my
recruiting agent hop on a Zoomcall to every one of the
hundreds of people and then justhey, out of 100, these are the
great ones.
These guys scored over 90.
They've got.
(38:16):
They're really smart.
I think you should talk withthem.
That's great.
I'm just going to speak withthose guys.
I'm going to give them afantastic experience because I
think we're going to have areally great relationship, and
so I think you're spot on there,james.
It's a really exciting time.
Speaker 1 (38:30):
Yeah, for sure.
And I have one other question.
It's a burning question that Ihave before we jump off the next
few minutes.
I'm totally blanking on itright now.
Dang it, it was a good one too.
It was a really good one, I'mtelling you, aaron.
Speaker 3 (38:42):
Well, elijah, what other questions do you have?
No, no other questions rightnow.
I have a fairly differentopinion on the way I do like
phone screens and stuff, butthat's probably for a different
episode, because I could, ok, Iremember my question, so let's
just do that All right.
Speaker 1 (38:59):
So for what about?
So what do you think aboutautomation and AI product driven
interviews for late stageinterviews, so like we're seeing
this initial application andscreening calls, but like
technical tests, seems like aclear one to me, to the extent
that companies are using thirdparty testings or just doing
homegrown evaluation.
Like why wouldn't we like atechnical interview, basically
(39:23):
incorporate an agent and thenbasically just package that
evaluation for a hiring team?
So getting like beyondscreening but really getting
into like code assessment andthese types of things.
I'm curious.
I'm sure you guys have thoughtabout that.
Speaker 2 (39:38):
Yeah, and again, I know we've talked a bit about
this already, but it all comesback down to value.
There's a lot more value todrive when you go from 100
candidates to 10, that's thescreening process than in 10 to
one, and so it's very intuitivethat the companies being built
today are starting with a largerproblem.
I think over time you're goingto see automation start to
(40:00):
trickle in and take over thatportion of the funnel as well,
but it may even be the case thatthe funnel in a way collapses,
because at that point why notjust do?
that technical assessment at thestart, right, it's not like the
thing that's bandwidthing you.
The reason you can't do thattoday is because you mentioned
those senior level resources,those engineers and those hiring
(40:20):
managers.
They just don't have time.
And the recruiters don't have alot more of that bandwidth, but
they don't have time.
The recruiters don't have a lotmore of that bandwidth, but
they don't have the knowledge,the experience there.
Ai has all of that, and so youmight even just see a collapsing
of the funnel where technicalsagain bubble up, and it's just
part of the screening process.
Speaker 1 (40:37):
Yeah, exactly, I think maybe this concept of
segmented stages might start tocollapse.
As you said, there's going toneed to be a way that we
organize the data to be in apresentable fashion where it's
segmented but like thistraditional interview process
with these, the way that it'sdone, it's definitely going to
shift where maybe there isn'tthe need to schedule like five
(40:58):
separate interviews at segmentedtimes for the candidate to do
that over a period of weeks andmaybe you still segment out the
data but a lot of it can be donein one workflow right, Like
show pipeline stages and stufflike that.
It'll just be different.
Speaker 2 (41:14):
The difference in cost between, let's say, like a
recruiter and, as I know, we'restaying on this technical
interview topic.
So the difference in costbetween a recruiter and an
engineer is going to be prettyhigh.
But the difference between amodel that is like super bare
bones and one that canunderstand engineering, the cost
there's a couple cents, if notnone, and so there, and you've
(41:36):
already got them on the phonecall in that screening interview
.
So you might as well throw acouple technical screen screens
in there as well.
Speaker 1 (41:43):
So are you like, in terms of your evaluation,
where's that data being pulledfrom?
Is it being pulled from the jobdescription?
Like, are you doing thecustomer questions?
Like, where are you generatingcustomer questions and where are
you pulling that evaluationdata from your customer?
Speaker 2 (42:01):
Yeah, so the evaluation, so there's the
interview questions andessentially the rubric or the
scoring criteria out of each oneis like out of 100, for example
, so you can have things likecommunication or experience or
other, even things like Englishproficiency or discipline, so
(42:22):
that'd be things like behavioralquestions, and those can be
automatically generated by yourrecruiting agent.
All you have to do is give itthe job description and it
already understands things aboutyour company during the
onboarding process and it'llgenerate those interview
questions in the group for you.
Or you can just upload thescoring rubric yourself, for
example, based on intake notes.
(42:42):
What the hiring manager caresabout.
Speaker 1 (42:45):
Got it and you guys, are you integrate with applicant
tracking systems and whatnot?
Speaker 2 (42:50):
Yeah, we agree with a bunch of them Always.
We're always trying tointegrate with more of them.
We yeah?
So the answer is yes.
Speaker 1 (42:58):
Cool, awesome.
We're coming up on time here.
Last chance, elijah.
Speaker 3 (43:05):
Awesome, we're coming up on time here.
Last chance, elijahno-transcript.
Speaker 2 (43:30):
Um looking forward to catching up again.
Speaker 1 (43:33):
This was super fun yeah, of course we're looking
forward to having you back onthe show and for everybody
tuning in.
Thank you so much for joiningus and we'll talk to you next
time.
Take care.
Hello, welcome to the Breakthrough Hiring Show.
I am your host, james Mackey,joined again by my co-host,
elijah Elkins.
Elijah, what's up?
I'm doing well Good.
We also got Aaron Wang with ustoday.
Aaron is the co-founder and CEOof Apriora and he's gonna tell
us a little bit about hisproduct today.
Thanks for joining us.
Speaker 2 (00:20):
Excited to be here, james and Elijah.
This is gonna be fun.
Yeah, excited to be here, jamesand Elias, this is going to be
fun.
Yeah, it's going to be a goodone.
So I guess, to kick us off,we'd love to know, just like the
high level about your productand a little bit about you, like
(00:40):
how you came to start thecompany and where you are today.
Sure, aprior automates phonescreens and live video
interviews with an autonomousrecruiting agent, and so we help
enterprises and staffing firmsconduct thousands of interviews
every day and help thoserecruiting teams better
understand.
You know, out of the hundredpeople that applied, out of the
thousand people that applied,who are the top 5% that I should
really be speaking to andinvesting our recruiters' time
with?
And so that's a little bitabout the product and what we're
trying to build, nice, nice.
(01:01):
And so you started the littlebit about the product and what
we're trying to build.
Speaker 1 (01:04):
Nice, nice, and so you started the company about
two years ago.
Speaker 2 (01:09):
Yeah, it's been about a year actually since we
initially built it and sincethen we've been growing and
scaling like crazy, and so it'sbeen a fun ride.
Speaker 1 (01:18):
Okay, cool, nice.
And so what gave you the ideato start this company?
Speaker 2 (01:25):
Like what inspired you?
Yeah, start this company.
What inspired you?
Yeah, we had built anotherstartup in a similar space, in
the interviewing space, tailoredtowards candidates, and through
that experience we had found agraveyard, if you will interview
automation tools and learned alot about the different parties
within the hiring space.
Lot about the different partieswithin the hiring space, the
(01:46):
hiring manager and thecandidates, the interviewer, the
staffing firm and what all ofthese parties incentives are and
what they care about.
And with the advent ofmainstream generative AI, now is
a time when you actually cancreate extraordinary value for
all of these parties a lot bynew technology.
Speaker 1 (02:04):
Nice, and I saw also that you have a technical
background right as an engineer,and then you're also a VC.
You do some investment right.
Speaker 2 (02:13):
I do some investing.
I wouldn't say I'm a VC myself,but I'm a venture partner at
Pioneer and do some investing onthe side.
Speaker 1 (02:22):
Okay, awesome, awesome.
We're really excited to diveinto your product.
I'm actually really interestedin this use case, so I'm excited
to learn more here.
I suppose, just to kick us off,when you are discussing
essentially taking on, would yousay okay, taking on the
screening interview primarily?
(02:42):
Is it primarily text or is itaudio?
How does it currently work?
Speaker 2 (02:49):
Yeah, we have a few products.
Our first and most popularproduct is a video interview
solution.
Like how we're, a lot of yourinterviews might be a Zoom call
or a Teams call.
It's face-to-face Instead ofyou being on that call.
An autonomous recruiting agentwill actually host and interview
the candidate on that call andit's over our own video
(03:12):
conferencing platform.
So the candidate doesn't haveto install Zoom or Teams, but it
allows the employers or thestaffing firm to actually get a
sense of the candidate'sbehavior and soft skills and
during the interview thecandidate and the recruiting
agent have a live, personalized,genuine conversation.
Speaker 3 (03:31):
Got it.
I just want to jump in here toclarify something, aaron.
So basically, when they'redoing that video interview,
they're not interacting withlike a live generated avatar,
like people might have seen,like a video of I don't know a
newscaster or something created.
It's more, there's an avatarimage down in the corner right
(03:54):
and but they are getting thatlike live voice interaction, but
it's not some ai generatedperson on the screen right.
Speaker 2 (04:02):
Yeah, you've got that exactly right.
We found that and happy to chatabout this more.
But what we really care aboutis the candidate experience, and
what we found is thatgenerating a live avatar
throughout an interview degradesthe candidate experience.
Although that technology issuper cool, it's not what the
candidate's like, and so you'recorrect.
(04:24):
During the video interview, weessentially have a profile
picture of the candidates like,and so you're correct.
During the video interview, weessentially have a profile
picture of the recruiting agent,so that when they're having
that conversation, thecandidates can feel comfortable
and give their all during thatinterview.
Speaker 3 (04:36):
Nice, yeah, thank you for clarifying that.
Speaker 1 (04:39):
So it's voice AI, so asking questions and there's a
conversation, but it's aconversational AI.
Okay, so how's that going?
Because sometimes when I'musing voice ai, it still can be
pretty clunky.
You know, particularly whenthere's like stuff like pauses
and whatnot people talk adifferent cadence, stuff like
that.
How do you smooth over thatexperience?
How do you make that work?
Speaker 2 (04:58):
yeah, I think the the tug is really between two
aspects of the technology.
There's one, so there are twothings that make a great
conversation.
Two things are latency righthow long does it take for me to
respond to you after you'vefinished your response?
And the second is intelligenceright.
Are you going to remember whatI said three minutes ago and
(05:21):
bake that into your nextresponse?
And so with both of those, weor I should say we built a lot
of these technologies from theground up, and that's allowed us
to control these aspects.
We also have really greatpartnerships with the folks at
OpenAI and Azure, allowing us toreally utilize the best that
the AI technologies have tooffer.
(05:42):
You mentioned that.
I have my engineering and AIresearch background and that
really helps, because we trulyunderstand the technology and
we're able to make thesetrade-offs so that we can
maximize the candidateexperience.
It just feels like a natural,fluid conversation.
Speaker 1 (05:59):
For sure.
Do the candidates have theability to respond by text, or
is it only voice?
Speaker 2 (06:04):
And do the candidates have the ability to respond by
text or is it only voice?
During the interview, theyrespond over voice, both in the
video interviews, and we alsohave a phone call product as
well the second that you apply,you'll get a phone call, and so
that's growing in popularity.
We do have a portion where theycan actually respond to a text.
For example, let's say youapply for a job and our
recruiting agent calls you butyou're not available.
(06:26):
The recruiting agent willactually send you a text and say
, hey, it looks like I missedyou.
Speaker 1 (06:32):
I'll probably give you another call in the next
couple of hours if that worksfor you.
Oh, that's awesome.
I really love that.
Speaker 2 (06:38):
Yeah, increase the essentially the engagement of
the candidate and trying to makethat high quality.
Speaker 1 (06:48):
So is it primarily in terms of how your customers
engage?
Do you see, as soon as somebodyapplies, do most customers want
them to just have the abilityto start the screening process,
or do you see customers want toessentially do an initial review
of the profile and then havethem decide from there if they
want to screen the candidate?
How do you see it worktypically?
Speaker 2 (07:09):
what's really unique about what we offer is that
companies now have the abilityto engage with every candidate
at scale, and what that means isthey're now able to widen their
talent aperture and not onlyconsider the folks that had a
4.0 and went to a great schooland had the best career
(07:33):
backgrounds, but also those that, hey, maybe they didn't have
the most opportunity throughouttheir career, but they have the
skills and they have theknowledge to prove it and be a
great employee.
They have the skills and theyhave the knowledge to prove it
and be a great employee, and weshouldn't be overlooking those
folks.
And the way that is articulatedin the use cases of our
(07:58):
customers is all the timethey'll just interview every
candidate because it's just socost effective and it's a way to
access talent that maybe yourcompetitors aren't accessing
today, aren't accessing today.
Speaker 1 (08:07):
So, that being said, it's like this tool is not
evaluating the talent per se.
It's collecting the screeningdata and then allowing the
hiring team to make, essentiallygiving them a lot more
information to evaluate anddecide if they want to move
forward in the process.
Is that accurate?
Speaker 2 (08:20):
Yeah, so after every interview, the AI recruiting
agent will write up detailedfeedback notes and, for example,
upload that or sync that toyour applicant tracking system
so that, for example, yourrecruiters can make a
well-informed decision.
The AI recruiting agent todaycan score, so you can give it a
rubric for the things that youcare about for that particular
(08:42):
role or requisition and we'llscore it at the candidate based
on that interview interaction.
And what's great about that isit allows the recruiters to
focus their time on thecandidates that do meet the
requirements of the role, asopposed to those that maybe
don't.
Speaker 1 (08:57):
So basically, the hiring team can filter based on
certain criteria to identify thecandidates that match best on
the filters or whatever is that?
Speaker 2 (09:09):
exactly right.
So, for example, maybe there'sa, let's say, a light industrial
role right where you need to beauthorized to work in the
united states, and you need to.
You know it's located in boston, massachusetts, so you'll be
able to drive up to Boston everyday.
The AI recruiting agent can askthose questions and then tag
that applicant as okay, great,they're authorized to work in
(09:30):
the US and they're able to workin Boston in person, and that
just makes it easier for therecruiter to go back into their
ATS and say, okay, great, I wantto talk to those folks because
they meet the criteria.
Speaker 1 (09:43):
Yeah, folks, because they meet the criteria, yeah,
yeah, because, like so.
With this tool, it's reallywhere it saves time is ensuring
that when recruiters or hiringteams do speak with somebody,
they're much more likely to makeit to the next round.
It's not necessarily savingtime at the very top of the
funnel because the recruitersstill have to go through all of
the candidates.
Essentially, it's like morelike that one layer deeper
(10:04):
within the funnel where it'ssaving time.
Is that accurate?
Speaker 2 (10:08):
Yeah, and I think there's more to it.
That is because we score everyinterview.
You can, let's say we scorethem out of 100,.
For example, you know, as arecruiter, I can set up an
automation.
You know, we have an automation, for example, with many ATSs,
and so the second someoneapplies, they can get access to
an interview.
They take that interview.
That data gets automaticallypopulated into their ATS the
(10:32):
employer's ATS and that includesa score.
Speaker 1 (10:39):
And so they can filter and sort based on that.
Okay, cool, all right.
So I'm just trying to think Imight be a little bit redundant,
I just want to make sure I'mdialing in.
It is providing a very clearscore for each interviewer, but
that so that, and I guess that'sbased on if they match the
criteria.
But then you start to get intoAI making like the doing the
(11:08):
evaluation versus just packagingdata for to make it easier for
the hiring team to evaluate.
So I guess my question is onthe.
You know, we I just had a reallyinteresting conversation with
steve bartell, ceo of gem, andwe were talking about ai's role
in recruiting and the differencebetween like essentially
enablement and packaging dataversus doing the evaluation
directly, and so he was talkingabout like just like the legal
(11:30):
kind of gray area, so to speak.
And so I'm just curious how youthink about that.
And with that scoring, do yousee that?
Well, no, it's just likescoring based like are you
remote or in person?
Those are like very basiccriteria.
It's not evaluating based offanything deeper.
Speaker 2 (11:48):
I'm kind of curious how you think about that in
terms of your product.
Yeah, so we're firm believersin human in the loop.
What we don't do is we don'tallow at this time the
recruiting agents toautomatically create a
disposition of the candidate andhave that actually be synced to
the ATS.
We think of the evaluation as adata point.
We tell you, hey, this personhas, let's say, an 80 in
(12:09):
communication skill.
And then let me tell youexactly why I gave them an 80,
right, because three minutes ofthe interview they had a really
great explanation of this, butthree minutes of the interview
they kind of had some troublediscussing this particular
experience at their last rolehere.
And so I think evaluationcertainly plays an important
role in bringing value to therecruiting teams.
(12:31):
I think it's important to makeit both have human in the loop,
but also make it explainable anddata-driven.
So don't just give me a score,but tell me, hey, how did you
come to this?
And let me make my own decisionon the actual candidate.
Speaker 1 (12:45):
Yeah for sure.
Yes, it's an interesting topicright when people are trying to
figure out exactly what AI'srole should be and then also, as
legal cases start to happen.
Right Right now, for instance,what's going on with Workday?
I don't know if you guys arefamiliar with that there's a
huge class action lawsuit ontheir AI discriminating upon
(13:08):
race, age and whatnot.
Now, who knows if there's anyvalidity to it?
Right, we don't know yet, butthat's something that's current
and a lot of folks are saying.
Steve was saying that'sprobably going to set a
precedent for future years tocome.
But yeah, it's reallyinteresting.
We're speaking with some CEOswho are very aggressive and
others that are very reserved.
I would say Greenhouse, the CEO, from what I can tell, seems to
(13:30):
be incredibly reserved.
Oh yeah, but you got Workable'sCEO who we had on Elijah, what
like two weeks ago.
Speaker 3 (13:37):
Yeah, nikos.
Speaker 1 (13:37):
I think, yeah, workable's incredibly aggressive
, yeah, I mean they'reimplementing AI in every part of
the funnel for talentacquisition and employee
experience.
They're an HRIS right.
Speaker 3 (13:52):
They built one within the last couple of years, but
they started as an ATS only.
Speaker 1 (13:57):
Yeah, they just started that.
So everything's sourcing to HR.
They're just going all in, itseems.
But yeah, I'm in the same.
I think philosophically, Ithink about it the way that you
are.
It's like thinking aboutbuilding a product of ultimately
what's going to create the mostvalue for the user and just
pushing aggressively in thatdirection, and I think getting
(14:18):
into evaluation territories isultimately more valuable, and
then just like putting insafeguards in place to make sure
that we know exactly what theai is actually evaluating off of
is really important.
But yeah, I think this is thefuture.
Speaker 2 (14:30):
really I think there are different philosophies for
how you want to approach newtechnologies.
I think you see that in everyplatform ship, whether that's
the cloud or mobile, of course,the internet and the question
you have to ask yourself as aleader is at what point do you
put your chips in and how much?
And what are just theopportunity costs of doing so
(14:54):
and, more importantly, not doingso?
And we're much more of theopinion that we think generative
AI is here to stay, and it'svery hard to imagine a world
where there's going to be lessAI in recruiting in the next
five to 10 years, and so it'smuch more important to find
those value cases, those usecases where customers will find
(15:15):
value, and doing so in a safemanner, to ensure you're in a
good spot.
Speaker 3 (15:21):
I think it's really interesting, too right.
If you've worked with startupsbefore, oftentimes you're
dealing with first-time hiringmanagers, first-time
interviewers, and for somereason, companies seem to feel
there's less risk from havinguntrained interviewers that
could be asking highlyinappropriate or even illegal
(15:42):
questions and they feel likethere's more risk from that
interviewer or that there's lessrisk from an interviewer doing
that and giving an evaluation, agenuine evaluation that impacts
hiring outcomes, versus an AIthat can be like fully audited,
like where you can refine itover time, like you're saying,
(16:03):
aaron.
You can know why it's givingdifferent scores.
You can also make sure itdoesn't ask illegal questions.
That, to me, is much lower riskthan the bias you're going to
get from an AI.
It seems like it would bepotentially lower risk than all
the untrained interviewers whocould essentially say whatever
(16:24):
they want and put your companyat risk.
Speaker 2 (16:27):
And I think you mentioned a good point there is
that it's for an AI.
It's measurable, right.
You can do statistical analysesand figure out what is the kind
of bias we're looking at today,Because you can measure it and
you can plot it over time.
You can take different actionsto lower that over time, right.
That's much harder to do withsomething you can't measure,
(16:48):
like a human interviewer thatmight be the first time
interviewing, or they woke up onthe wrong side of the bed, or
they didn't have a cup of coffee.
If you can measure it, it'smuch easier to be able to
control it, and so I think a lotof the big players that you
mentioned are going to be caughtup in these larger scale
litigations.
I think a good comparison isthe autonomous driving market.
Speaker 1 (17:12):
I was thinking about this yesterday.
I think that's a fantastic.
It's a very relevant comparison.
Speaker 2 (17:18):
Yeah, and you see that I don't know if you guys
have been in San Franciscorecently, but I'm sure a lot of
the listeners have.
There are Waymos everywhere,people are taking Waymos left
and right.
They're completely autonomous.
People love it.
People pay more for Waymosbecause they can take meetings
during the car right, it's agreat experience and yeah, you
definitely have some casualties,like Cruise, for example, got
(17:40):
dragged in the mud in the newsfor a bit, but in the long run,
that's probably going to be thefuture of driving it is.
Speaker 1 (17:48):
You know it's like.
The other thing, too is likewhen you're building a product,
particularly at an early stage,it's like at the rate it is
moving.
Do you really want to build aproduct for, like where you are
today or where we've been forthe past six months, are you
building the product of thefuture?
like yeah and it just seemsobvious to me.
It's like we should be buildingproducts that are like actually
going to represent what thefuture holds.
Yes, there are going to beroadblocks potentially, or just
(18:12):
lessons learned is going to berisk, but that's where the
opportunity is as well.
That's where we get like thebiggest lift and are creating
the most value.
So I think you know startupsneed to be aggressive here.
I think, aaron, I think whatyou're doing is smart.
I think that you have to pushin this direction.
I think there's a ton of valuehere.
(18:33):
I'm curious, though when areyou seeing the best traction now
?
I know you raised money.
I think back in May you raiseda couple million bucks, right?
Speaker 2 (18:43):
Yeah, our last round was 3 million around that time,
and I think that's a question wethink a lot about, because I
think this is a broadgeneralization.
But I think the point is clear.
It's like, every company hiresand thus it's very important to
(19:05):
focus, because you need to pickone ICP, focus on them, solve
their problems, because not allthe markets will be ready, like
I think a very obvious exampleis executive search.
Right, that's not really aninterviewing or a screening
problem and it's more of asourcing problem and finding
those right people, so thatmarket's not quite ready.
So the question is okay, whatmarkets are ready?
(19:26):
And a great way to look at thatis just sort by value, right,
or I guess the inverse of that,which is pain, right, who is
spending the most oninterviewing and in screening?
Today we found a lot of successin the external recruiting side
of things.
That's been very good for usand that's in their entire
business, right, and it's a verygood for us and that's in their
entire business, right, andit's a very market sensitive
(19:47):
business for them.
And so if you can introduceautomation that actually brings
value to them and saves themtime, increases placements for
them, of course, software isgoing to be much cheaper than
any type of human-based labor.
That is a lot of value that youcan provide and we've had a lot
of success there.
Speaker 1 (20:06):
Okay, and with these staffing firms are you seeing,
is it more like on the SMB,mid-market or enterprise?
Speaker 2 (20:12):
players, yeah, so we've been really excited to be
working with folks across theboard.
I think the bigger there's avery clear value add for
companies like in the mid-marketbecause they it's very hard to
scale like a staffing businessto the level that they want to.
There's just so thin margins.
(20:34):
Even if you look at the 10Ks ofpublic staffing firms today,
you'll see folks that are doing6 billion in revenue versus 18
billion in revenue annually.
They're taking home the sameamount of profit or being very
close to break, even thoughone's doing a 3X the amount of
annual revenue.
And we're seeing a lot ofuptake in the mid-market section
.
Speaker 1 (20:52):
That's awesome and this might actually be the same
for in-house teams too.
We can just look at my agents'design for now.
The specific types of rolesthey fill, I'm sure in the
industry they serve, I'm sureimpacts it.
We were speaking.
It was David Tell at Qual whowas saying you're seeing a lot
of in light industrial.
He was just seeing a ton ofdemand.
What types of staffing agenciesare you seeing?
(21:15):
Is it like temp hiring, permplacement?
What types of industries androles are they working on?
Speaker 2 (21:21):
Yeah, it really has been across the board, which is
really exciting.
It turns out, when you havesomething that is, you know, an
intelligent and intelligentagents, what you find is that if
they can do, if that agent canscreen for a senior software
engineer or a senior NETdeveloper, then it can probably
(21:41):
ask the questions required toscreen for a warehouse associate
or a forklift operator, and sothat's been really exciting for
us.
A lot of our customers todayare in, for example, it staffing
, light industrials, hospitality, healthcare, a lot of temp, and
I think that these cases areextremely obvious because a lot
(22:04):
of those tend to be much morehigher volume.
Speaker 1 (22:07):
Got it, so you to be much more higher volume.
Got it, so you see more of thehigher volume side.
Do you see this as?
Where do you think a productlike this fits in with maybe
lower volume?
I mean, I think lower volume.
The products that we're seeing,like we brought on CEO of
BrightHire and Pillar andthey're doing like internet
(22:32):
interview intelligence platforms, where it's like AI co-pilots
that are doing a reallyfantastic job of packaging data
to help companies evaluatefaster these are, I think,
primarily on lower volumesearches.
There could be like a b2bgrowth stage mid-market tech
company, something like that.
They're hiring a softwareengineer.
Maybe they have 10 candidatesin the funnel.
You know they're leveragingBrightHire to.
It does, of course, like the jobdescription generation, custom
question generation, which isall very basic stuff, and then
(22:54):
packaging the data effectivelyand then also give like some
gong-like feedback on wherethey're like interview quality,
how good are the interviewersdoing?
Are they starting on time?
That kind of stuff.
So it's pretty cool.
I do a lot of.
They have a lot of featuresLike.
(23:14):
Like do you see your productfitting in on some of those
lower volume uh use cases aswell?
Or like how do you I'm justcurious if there's an
application for what you'redoing and some of those other
use cases yeah, I think there'scertainly.
Speaker 2 (23:22):
I think there certainly is we.
The value prop is going to be abit different because hiring
for value prop is going to be abit different, because hiring
for those folks is going to be abit different.
Again the incentives aredifferent.
So for those folks, if they'rehiring a senior software
engineer in San Francisco andthey don't hire too many of
those then it turns out whatthey really want is someone
that's super high quality, andso having an AI recruiting agent
(23:47):
that can do that supertechnical, in-depth interview
ends up being really useful forthem, because you can
essentially bubble up a veryin-depth technical screen to
that first interview, to thatfirst interaction.
You'd love to know if someoneis technically competent right
away, but it's really difficultbecause you know your engineers
are, you know, very well paidand quite expensive, and so
(24:09):
they're expensive, but they alsodon't have a lot of time and
you pay them to do.
You know to code and buildproduct.
Imagine where ai has read allthe documentation, understands
your tech stack and understandsthe tech stack that's on the
candidate's resume, and they canhave a really in-depth
technical conversation.
That ends up being a very, veryinteresting value prop for
those folks.
Speaker 1 (24:30):
Yeah, and that's like what I'm getting at too.
I see a very strong use casefor lower volume searches as
well, because I think that itwould make a lot of sense for,
when people are applying inbound, to just be able to open up a
screening call so that whenpeople are looking at resumes
(24:52):
there's just so many screeningcalls where you're just wasting
time.
Yeah, we have the salary rangeposted on the job description
but somebody doesn't look.
It's like okay, we got to dothat.
Or are they available forhybrid or are they if it's a
salesperson?
Do they work with likemid-market enterprise customers?
Are they available for hybridor are they if it's a
salesperson?
Do they work with mid-marketenterprise customers?
Are they primarily SMB?
There's just stuff that we haveto know that even an experienced
recruiter if you ask those upfront and you can get off the
(25:14):
phone in five minutes, it'sstill just a big waste of time
where it's like you can improvethe conversion rate from that
initial conversation with arecruiter to the hiring manager
if you have more informationgoing into that call.
It's just interesting becausemost of the application of
product your product and then acouple of similar they're not
exactly the same products we'veseen.
(25:34):
It's like we're on this likehigh volume side as the primary
use case we're seeing.
So it's just it's interestingto me.
I see this incredible use casefor low volume searches as well
that I don't know.
Speaker 2 (25:45):
Yeah, I think what you bring up there is important
is we're not only increasingbasically the quantity or the
bandwidth that your recruitingteam can handle, but also just
increase the quality.
Your recruiters it's unlikelythat they have a super
experienced background inengineering, right?
I mean, this is a technicalhire.
Or they were maybe never ledgo-to-market if it were a sales
(26:09):
hire.
And so what does that goodsales hire look like?
Well, it turns out that the AIactually knows, because it's
read everything there is to knowabout what is a good sales hire
and what experiences are goodto have.
And if you can give the AIrecruiter, for example, the job
description and the company'sculture, then the AI recruiter
(26:31):
can also help sell the role andthe position and again just
increase the quality of everyinteraction that you're having
with the candidate.
I think is something superspecial.
We're not hiring hundreds ofpeople every month.
We actually use our own product, our own recruiting agent, to
do a lot of the hiring, In fact,the last two people again, so
(26:52):
we're pretty low volume.
Our last two folks we hiredwere both using our AI
recruiting agent and both ofthem have turned out exceptional
, right?
One of them's an engineer andone of them heads up our
go-to-market and so sales hiring, so I think that's really
exciting and heads up ourgo-to-market and so sales hiring
, so I think that's reallyexciting and we are hiring.
So feel free to everybody outthere, feel free to uh, yeah,
(27:14):
yeah, I mean that's uh, that'sgreat.
Speaker 1 (27:15):
It's like when you're growing as a startup too, it's
like you need to hire.
This is a product that you needfor, arguably like the most
important part of your business,like your team is gonna for a
product.
It doesn't matter what kind ofcompany.
Your team is fundamental toanything you're going to build
and any success you're going tohave.
It's the input for any level ofsuccess.
But building anything great ofvalue in the world.
Speaker 2 (27:39):
No, that's right.
Yeah, I think an important noteis what's best and what you're
looking for in that next hire,and so our hope is to get you to
a yes as soon as possible.
Get you in front of thecandidate, that is great, and if
you're, let's say, youracceptance rate is at 1%, then
let me just put that onecandidate in front of you and
the other 99, you know, notdirect them to you, not have you
(28:01):
have to filter through everysingle one of them, have a
conversation with every singleone of them.
Speaker 1 (28:05):
Yeah, for sure.
So I've been monopolizing a lotof the questions.
Elijah, Do you have any burningquestions right now?
I could keep going all day onthis.
Speaker 3 (28:15):
Yeah, I have a couple of questions, but we did the
sourcing technology one theother day that I got to geek out
on and dominate things, so Iappreciate that.
I'm curious, aaron, how do yousee things shifting in the
market?
So we've got the early stagevideo interviewing tools that
were mostly kind of one way.
You've got companies likeSparkHire and there's a couple
(28:37):
other big ones that I'm notremembering their names.
Then you've got this justwithin the last few years
probably, companies like Jamesmentioned on the interview
intelligence side, so likeBrightHire, pillar, metaview, et
cetera.
How do you see Apriora comingin and fitting into that?
Are those companies, theinterview intelligence going to
(28:58):
build their own AI agents, doyou think?
Or are they going to want tomaybe I don't know create an
agent, but actually it's Appriori in the background that's
actually delivering.
I'm just curious how you seethese shifts happening and your
role in that.
Speaker 2 (29:16):
There are a lot of companies that do talent
intelligence or interviewintelligence, and that takes a
lot of times the form of havinga note taker on the call right
and being able to essentially belike a gong for interviews.
I think there are a lot ofthose types of companies.
It's a fantastic product.
(29:38):
Today, we really, we reallywant to skate to where the puck
is going to be and not where itis today.
I think today, you know thatrecruiter might not be on that
call, or at least they're goingto be a lot less recruited being
on those calls, because they'regoing to be instead speaking
with people that are actuallyqualified and not spending time
with people that might not be.
(29:59):
And so we're really, reallybullish on complete autonomous
agents, and that's what we're,you know.
Of course, that's what we'rereally, really bullish on
complete autonomous agents andthat's what we're.
Of course, that's what we'rebuilding out and what our
customers love about us today.
And again, it all goes back tovalue, right?
If we look at that Waymoanalogy, these interview
intelligence platforms would beUbers.
They're great and they're veryconvenient, they're very helpful
(30:22):
, but there still needs to be adriver there, right?
Speaker 1 (30:28):
do you want to build a red box or netflix like?
Speaker 2 (30:31):
exactly, exactly and and I think it's particularly
this way is actuallyparticularly interesting,
because what you do is becauseyou have a driver there right,
and you again the you mentioned.
it's very hard to measure howgood that driver is, you just
get in the car Right, and butyou'd be, you'd feel a lot safer
(30:51):
if you knew that, hey, this waymore car has done literally
millions and millions of milesand has never crashed.
So statistically it's just,you're just a lot better off.
I know I don't want to, I don'tmean to go on a tangent here,
but a couple of decades, manydecades ago, elevators used to
be manual.
Right, you have an elevatoroperator actually standing in
the elevator with you and movingyou to the floor.
(31:12):
But it's pretty hard to imaginethat world today.
It would feel almost unsafe.
And so for us it's aboutskating to where the puck is
going to be, and we think thatwhere that puck is going to be
is going to be an autonomousagent for hiring.
Speaker 3 (31:25):
And how are you going to work with the recruiters?
I'm sure taxi drivers goingwith your analogy aren't excited
about Waymo, and some of themin this case, some of them may
be buyers for the technology.
So I'm curious how you seerecruiters adopting the
technology.
Lots of their time is spentdoing screening calls.
Recruiters adopting thetechnology lots of their time is
(31:47):
spent doing screening calls andthey're even struggling, I
think, sometimes to want toadopt either a note taker or
BrightHire, one of theseinterview intelligence tools.
Yeah, how do you see that going, at least for the recruiters
who are currently using yourproduct and, in the future,
How's it going to help them andwhat's their relationship with
it?
Speaker 2 (32:02):
Yeah, so in the short term, I still believe that a
recruiter is more likely to bereplaced by another recruiter.
You shouldn't be scared of AItaking your job tomorrow.
You still are going to need arecruiter to facilitate a lot of
those interactions.
For example, hey, I talked tothe hiring manager and I had an
(32:24):
intake meeting with him or herand these are the interview
questions and these are thethings that they care about.
Here's the rubric.
Then the interview agent can gooff and go do that interview,
and so I think that recruiterswill still be replaced by
recruiters.
Maybe a recruiter that's usingAI will be replaced by those
other recruiters, and I thinkthat's the place of technology
(32:49):
and I think recruits today stillhave a very valuable skill set
and we want them to focus on themore human aspects of
recruiting going to careerevents and focusing on employer
branding things that are reallyhard to automate and candidly.
They probably want to focusmore on that anyways, because
it's just more branding rightThings that are really hard to
automate and candidly.
They probably want to focusmore on that anyways, because
it's just more human right.
(33:10):
There's nothing human aboutgoing on eight to 10 screening
calls a day, right, or trying tochat with someone that you
don't know much about thatdomain, right?
A lot of that just can and webelieve should be automated so
that you can focus on doing thetasks that you'd love doing as a
recruiter.
Speaker 1 (33:30):
I agree Honestly.
I own an RPO company, embeddedRecruiting Agency and we've
worked with over 200 customersin the past decade A lot of
companies, a lot of startups,growth stage companies, a
handful of enterprises,primarily in the tech industry,
but not only and I honestly feellike if you're a good recruiter
, you should be screening out80% of the people in your phone
(33:53):
screen and that's if you'redoing a great job sourcing.
It should be more if you have ajunior to mid-level sourcer, if
you have a great senior levelsourcer, a lot of our customers.
We're passing on 80% of thepeople on first round.
The reason why I think that alot of recruiters they do see
their role as sales, but whenyou really put on that business
(34:15):
owner executive hat, you got toremember it's not just about
filling roles, it's aboutbuilding value and building a
team that's going to scale asuccessful company and add value
to the customer.
That's a lot harder than justgetting somebody in the seat and
the role of recruiter should beone hand you're beckoning,
you're pulling people in, theother one you're pushing away,
right, you're putting up thebarriers, right, and so it just
(34:38):
like again for our seniorrecruiters.
They had to get really good atevaluating quickly and they
spent a lot of their timejumping on the phone with a
candidate saying all right, look, I'm happy to answer your
questions.
I ask my questions in order,starting with a high level fit,
and we only get into the detailsif it actually makes sense,
because I don't want to ask youall these details.
(34:58):
It doesn't make sense to gointo that and we'll just do it
in order to make sure it makessense for both of us to continue
the conversation and I don'tknow 20 to 30 percent of the
time off the phone in the firstfive minutes and then you got
another 20, 30 percent of thetime that you're off the phone
at 15.
And then you got probably less,around 20 percent of the time.
(35:19):
You're hopefully trying toscramble to get everything in
before the call and you'rebuilding that relationship by
the end of the call, talkingabout the process and next steps
and everything like that.
But I'm just thinking, yeah, asa senior recruiter, somebody who
knows what you're doing, if youcan in a meaningful way
increase your conversion ratefrom phone screen or from your
(35:39):
first interview.
If the product is doing thescreen, it eliminates and
collapses the process.
But from that initial humaninterview to the next round.
If you can increase thatconversion rate, that's huge.
If you're doing it in theappropriate way, like I think.
A lot of times conversion ratesare like people think about
them the wrong way in arecruiting funnel, I think like
(36:00):
more is better.
Speaker 3 (36:00):
No honestly, a lot of times like west is better
there's a balancing act.
Speaker 1 (36:04):
If it's too low, it's like are you setting up the
right people?
If it's too high, like are youjust people through?
Oh, it's nuanced, but but yeah,anyways, like it just would
save a lot of the time and youwant particularly you're saving
the time as your senior levelresources, which is like your
senior level recruiter or yourhiring team, and there's like
metrics that daniel tape puttogether and like growth
companies hiring and a lot oftimes hiring managers are
(36:27):
spending 50% or more of theirtime interviewing On average.
I was talking with MattCaldwell.
I don't know if you guys knowMatt, but he scaled a company
called Rocket Power, an RPO firm, from a few people to over 400
people and he sold a historicamount of money to Kelly
Services and yeah, anyway, samething.
He's looking at it essentiallythe same way.
(36:47):
They basically calculated and,believe it or not, there was
around 75 hours on averagecompanies were taking per hire,
and those are the later stagecompanies, right, ones that you
would have heard of, which is aninsane amount of time.
So think about that much timeon payroll of executives.
(37:07):
And that's not even coveringthe cost of working with an RPO
agency job postings, whateveryou're doing to fuel that growth
?
That's insanity.
So if you can leverage atechnology to improve the
quality of your pipeline forevery human touchpoint, that is.
(37:29):
This is a seven to eight figureproblem for businesses and they
don't even realize it.
Speaker 2 (37:35):
Yeah, I can just speak from my own experience,
because we are hiring and when Ipost a job, I'm going to get
hundreds and hundreds ofapplications and resource them
and try to get them to apply andI make an effort to meet the
candidates that I like.
But there's just no way thatI'm going to be spending or any
of our employees are going to bespending hours and hours
(37:56):
looking through every singleresume and making the right call
on every single one.
That takes a lot of time.
So if I could just have, in theclick of a button, have my
recruiting agent hop on a Zoomcall to every one of the
hundreds of people and then justhey, out of 100, these are the
great ones.
These guys scored over 90.
They've got.
(38:16):
They're really smart.
I think you should talk withthem.
That's great.
I'm just going to speak withthose guys.
I'm going to give them afantastic experience because I
think we're going to have areally great relationship, and
so I think you're spot on there,james.
It's a really exciting time.
Speaker 1 (38:30):
Yeah, for sure.
And I have one other question.
It's a burning question that Ihave before we jump off the next
few minutes.
I'm totally blanking on itright now.
Dang it, it was a good one too.
It was a really good one, I'mtelling you, aaron.
Speaker 3 (38:42):
Well, elijah, what other questions do you have?
No, no other questions rightnow.
I have a fairly differentopinion on the way I do like
phone screens and stuff, butthat's probably for a different
episode, because I could, ok, Iremember my question, so let's
just do that All right.
Speaker 1 (38:59):
So for what about?
So what do you think aboutautomation and AI product driven
interviews for late stageinterviews, so like we're seeing
this initial application andscreening calls, but like
technical tests, seems like aclear one to me, to the extent
that companies are using thirdparty testings or just doing
homegrown evaluation.
Like why wouldn't we like atechnical interview, basically
(39:23):
incorporate an agent and thenbasically just package that
evaluation for a hiring team?
So getting like beyondscreening but really getting
into like code assessment andthese types of things.
I'm curious.
I'm sure you guys have thoughtabout that.
Speaker 2 (39:38):
Yeah, and again, I know we've talked a bit about
this already, but it all comesback down to value.
There's a lot more value todrive when you go from 100
candidates to 10, that's thescreening process than in 10 to
one, and so it's very intuitivethat the companies being built
today are starting with a largerproblem.
I think over time you're goingto see automation start to
(40:00):
trickle in and take over thatportion of the funnel as well,
but it may even be the case thatthe funnel in a way collapses,
because at that point why notjust do?
that technical assessment at thestart, right, it's not like the
thing that's bandwidthing you.
The reason you can't do thattoday is because you mentioned
those senior level resources,those engineers and those hiring
(40:20):
managers.
They just don't have time.
And the recruiters don't have alot more of that bandwidth, but
they don't have time.
The recruiters don't have a lotmore of that bandwidth, but
they don't have the knowledge,the experience there.
Ai has all of that, and so youmight even just see a collapsing
of the funnel where technicalsagain bubble up, and it's just
part of the screening process.
Speaker 1 (40:37):
Yeah, exactly, I think maybe this concept of
segmented stages might start tocollapse.
As you said, there's going toneed to be a way that we
organize the data to be in apresentable fashion where it's
segmented but like thistraditional interview process
with these, the way that it'sdone, it's definitely going to
shift where maybe there isn'tthe need to schedule like five
(40:58):
separate interviews at segmentedtimes for the candidate to do
that over a period of weeks andmaybe you still segment out the
data but a lot of it can be donein one workflow right, Like
show pipeline stages and stufflike that.
It'll just be different.
Speaker 2 (41:14):
The difference in cost between, let's say, like a
recruiter and, as I know, we'restaying on this technical
interview topic.
So the difference in costbetween a recruiter and an
engineer is going to be prettyhigh.
But the difference between amodel that is like super bare
bones and one that canunderstand engineering, the cost
there's a couple cents, if notnone, and so there, and you've
(41:36):
already got them on the phonecall in that screening interview
.
So you might as well throw acouple technical screen screens
in there as well.
Speaker 1 (41:43):
So are you like, in terms of your evaluation,
where's that data being pulledfrom?
Is it being pulled from the jobdescription?
Like, are you doing thecustomer questions?
Like, where are you generatingcustomer questions and where are
you pulling that evaluationdata from your customer?
Speaker 2 (42:01):
Yeah, so the evaluation, so there's the
interview questions andessentially the rubric or the
scoring criteria out of each oneis like out of 100, for example
, so you can have things likecommunication or experience or
other, even things like Englishproficiency or discipline, so
(42:22):
that'd be things like behavioralquestions, and those can be
automatically generated by yourrecruiting agent.
All you have to do is give itthe job description and it
already understands things aboutyour company during the
onboarding process and it'llgenerate those interview
questions in the group for you.
Or you can just upload thescoring rubric yourself, for
example, based on intake notes.
(42:42):
What the hiring manager caresabout.
Speaker 1 (42:45):
Got it and you guys, are you integrate with applicant
tracking systems and whatnot?
Speaker 2 (42:50):
Yeah, we agree with a bunch of them Always.
We're always trying tointegrate with more of them.
We yeah?
So the answer is yes.
Speaker 1 (42:58):
Cool, awesome.
We're coming up on time here.
Last chance, elijah.
Speaker 3 (43:05):
Awesome, we're coming up on time here.
Last chance, elijahno-transcript.
Speaker 2 (43:30):
Um looking forward to catching up again.
Speaker 1 (43:33):
This was super fun yeah, of course we're looking
forward to having you back onthe show and for everybody
tuning in.
Thank you so much for joiningus and we'll talk to you next
time.
Take care.
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