Become a Creator today!Start creating today - Share your story with the world!
Start for free
00:00:00
00:00:01
Bill Mastin on How AI Is Reshaping Hiring, Retention, and HR
7 Plays8 days ago
Hiring isn’t just evolving. It’s being redefined.
In this episode of MustardHub Voices: Behind the Build, Curtis Forbes sits down with Bill Mastin, CEO of Cadient, to unpack how AI is transforming hiring, retention, and workforce strategy. With 20+ years at the intersection of technology and HR, Bill brings a practical perspective to one of the most complex shifts in modern business.
They explore why hiring feels broken today, from AI-generated resumes and overwhelming applicant pools to the rise of “ghost jobs.” Bill explains how organizations are using AI to screen candidates, predict retention, and rethink the role of recruiters.
The conversation also covers the cultural and operational trade-offs of AI adoption, including bias, transparency, and the balance between efficiency and human connection. From AI-powered interviews to autonomous agents, Bill outlines what leaders need to understand now to stay competitive.
This episode is a must-watch for HR leaders, founders, and operators navigating the future of hiring in an AI-driven world.
About Bill:
Bill spent the last twenty years at the intersection of technology, people, and growth, helping organizations solve their most challenging issues around hiring, onboarding, retention, and performance.
As CEO of Cadient, he’s building solutions that help HR leaders move faster, scale smarter, and prepare their workforce for an AI-driven future. The belief that technology should amplify human potential, not replace it, is his DRIVE. He believes that growth is less about headcount and more about capability. And that the best leaders are the ones who stay curious, stay humble, and never stop learning.
When he’s not thinking about workforce evolution, you'll find him in the mountains. He grew up moving around the US and has worked significantly in EMEA and APAC.
Recommended
Transcript
Introduction to 'Voices Behind the Build'
00:00:06
Speaker
Hello again, everyone. This is another installment of Mustard Hub Voices Behind the Build. In these episodes, I sit down with the people building, backing, and running better workplaces. I'm your host, Curtis Forbes, and my guest today is Bill Mastin.
Bill Mastin's Journey in HR Tech
00:00:20
Speaker
Bill spent ah the last 20 years at the intersection of technology, people, and growth, helping organizations solve their most challenging issues around hiring, onboarding, retention, and performance. As CEO at Cadient,
00:00:34
Speaker
He's building solutions that help HR leaders move faster, scale smarter, and prepare their workforce for an AI-driven future. The belief that technology should amplify human potential, not replace it, is his drive. He believes that growth is less about headcount and more about capability, and that the best leaders are the ones who stay curious, stay humble, and never stop learning.
00:00:58
Speaker
And when he, apparently when he's not thinking about workforce evolution, you can find him in the mountains. He grew up ah moving around the U S and work significantly in um E M E E and APAC.
00:01:12
Speaker
So welcome to behind the build. Thanks for joining me, Bill. Thank you so much, Curtis. I got to tell you, that was maybe one of the the more more graceful and and nice intros um that I've had. So thank you know thank you for that. Scraped it off your LinkedIn. It's great to be here. It's great to talk.
00:01:32
Speaker
um Well, i've been looking forward to it ah for a while. and And you can thank LinkedIn, quite honestly. um But let's let's start with, you know, you, your career path. You know, you didn't start out in HR. So I'm really kind of curious what pulled you there and what attracted you to hiring and and talent.
00:01:50
Speaker
Yeah, I mean, I kind of came into HR tech kind of generally through the door of learning.
Inspiration and Transition in HR Tech
00:01:58
Speaker
So um really, the the very short version is post-university, ended up doing a program in AmeriCorps, worked inner city schools for a couple years as a volunteer, and and then and then learned the technology. We were running a computer lab.
00:02:15
Speaker
Uh, and at the time it was, ah Pearson software, which was like success maker and it would help with school with a test grade test scores and all of that. and um,
00:02:27
Speaker
And I learned that package really well. So as soon as my kind of volunteerism ended, Pearson hired me. And so then I ended up start working in software companies. And really what I'll tell you, what got me inspired in learning technology at as ah as a starting point was that I was observing in class classes a fifth grade student, one that was doing ninth grade algebra and one that couldn't read at first grade level. And the system was able to adjust and expose those students to content that they could actually consume and learn on their own path, like individualized learning paths for one hour a day, where they had you know many hours a day in content that either was too easy
00:03:13
Speaker
are too hard for them. yeah So the power of like technology and the ability to integrate with like the way humans are learning or you know are performing or whatever, that was kind of the start.
00:03:25
Speaker
And then I started working for some of the large learning management system companies, ended up working for a company called Think. We were acquired by Saba. We were doing massive projects, putting learning systems on submarines and the Australian Department of Defense and Cisco partner channel education. So then kind of ended up in corporate learning and then tripped my way into ah organizations that we were acquiring HR technology companies. And I was kind of going in and leading organizations. turnarounds for some of those companies like PeopleFluent, NetDimensions, and then some very niche HR technology companies before I found my
Fragmentation and Disruption in HR
00:04:05
Speaker
way to Cadient. So it's been interesting kind of to navigate that.
00:04:09
Speaker
um HR is so fragmented. So even like under the blankets of HR, you've got all these different groups. talent acquisition to L&D to comp and benefits and, you know, global mobility, which is where I was the CEO of Topia, which was a a global mobility platform. We helped organizations move people on assignment around the world. So,
00:04:33
Speaker
and and do things like automate state to state withholding and some really tricky things if you would do on spreadsheets we did in a system and automate. All of that stuff is up for massive disruption with what's coming in and what's happening right now. Like we're, we're in this kind of in the middle section of this, this, this amazing movie of tech. And it's, ah it's kind of still a little bit hard to predict what the ending is going to be at this point. So.
00:05:01
Speaker
Oh my God, you said it. Well, let's start with, before we get there, because I have a feeling we have a lot, we're going to go deep. Tell us about Cadient Talent. what what What does it focus on? What kind of organizations typically come to you for help?
00:05:15
Speaker
So i would put Katie and Talent at kind of the intersection point and the um and and the the the point of um trying to leverage some of the AI technology that is on the streets now.
AI's Impact on Recruitment
00:05:29
Speaker
But not only that, look at really points of problems that organizations have in in people, people management, and people um hiring, ah retention. um Historically, Cadient has focused on high volume hiring customers. So customers that have retail, ah manufacturing, healthcare, care where they're hiring a lot of people we've built in our core applicant tracking system, some very specific features and functions that support things like pooling, evergreen wrecks, those kinds of things that not all applicant tracking systems have.
00:06:05
Speaker
That being said, that is a um that's that's part of our core business that's been there for a long time. i would say the last 18 months, ah really the focus has been to start to build much more um flexible, modulized technology that can plug into anyone's ah HR ecosystem, whether it's, you know, sourcing problems for recruiters that are struggling with finding the right candidates, screening technology. So in the world of of recruiting right now, one of the biggest problems you have is a recruiter opens up their inbox.
00:06:44
Speaker
They've put a job posting out there and they see 200 resumes that all look like unicorns, right? Because AI has taken the job restriction and they've taken the, the, ah resume and they've said, you know AI, make my resume perfect for this job. So there's a lot of, I almost see it like this kind of existential battle of like companies battling AI that's coming in from the on the recruiting side ah with their own versions of AI to try to you know figure out. mean, I've already had some customers that
00:07:18
Speaker
have found video ah interviews where the candidates are using deepfakes to um perform an interview. So there's all kinds of stuff. Like there's so many things going on right now.
00:07:33
Speaker
um We're helping organizations navigate all of that.
Future of SaaS and Technology in HR
00:07:37
Speaker
And we've had this core SaaS platform. We've got a smart suite set of products that help across all kinds of different areas.
00:07:46
Speaker
um that span from retention or from recruiting to retention. ah So now that's, that that's kind of where we're focusing in right now. I think the future of SAS full stop is more,
00:07:59
Speaker
flexible than what we have done historically. So all SaaS companies, I think, need to evolve with the times and really just get back to solving core problems with the customers have and helping them be successful. That's going to be the future of, I think, all SaaS, but definitely the way that I want to take Katie in.
00:08:19
Speaker
You talked about, you know, some of these these these categories, you know, or or verticals that have, you know, Or that that that that, you know, that hire lots lots and lots of people frequently, right? Probably ah industries that suffer from, you know, turnover in excess of 100% annually, right? you're're You're sort of focusing on these groups. Right.
00:08:45
Speaker
What do you think is a huge misconception? I think the business leaders might have about hiring, but second, you know, when they say you, you talked about, you know sometimes there might be 200 resumes that all look incredible when they say that we can't find good people. What's, what's really going on underneath that statement?
00:09:04
Speaker
Right. Well, so there's a few interesting things. Let me, let me start with, um, you know, the, some of the misconceptions are met like when, uh,
00:09:15
Speaker
there's a 100%, 130% turnover of an or of an organization annually. And this happens a lot in retail brands um and you know um stores selling shoes, whatever. and um And so one of the challenges is that the talent acquisition team that's responsible for the hiring and filling a pipeline of candidates to to fill that in,
00:09:39
Speaker
Once the hiring finishes, they're stakeholders in retention, but they're not really the owner of retention. Often that hands off to the store manager or whatever. So we actually have built some technology. One of the products we have is Smart Tenure that will actually utilize AI to compress data, not only on the candidate you're hiring or the potential candidate you're hiring, but also the trends in that industry And the data from that specific company is called smart tenure. And it'll actually predict the likelihood of an employee staying and how long.
00:10:13
Speaker
Why does this matter? In some retail environments, the average tenure is like 45 days. And it costs anywhere from $3,500 to $5,000 of lost product productivity, replacement fees, and and and training to get that person up to speed.
00:10:30
Speaker
So... We have, and that's in retail with kind of lower um ah cost ah positions. You go into things like healthcare care and nursing and, you know, knowledge workers, and all of a sudden it's not a 3,000. It sometimes goes to 1X, 2X salary of lost productivity, replacement fees, and and lost productivity on the other side while they get up to speed. So it the the The problem, I think, that a lot of the C-suite doesn't necessarily always – they don't look at it holistically from we're going to hire and we're going to retain.
00:11:07
Speaker
Can we even predict who's going to stay and what the cost impact to my business is? They've baked in and assumed – 130% turnover, let's say what if we could take that through predictive analysis down to 75%? You're talking about a significant bottom line impact to a company if you were to implement the right technology to help you better predict candidates and and their their longevity, but also um you know give them a way to communicate
00:11:40
Speaker
ah up the chain in in a, in a, in a, in that's our smart feedback tool. So we've built a lot of technology about this. On the other side, your other question about what's happening with 200 applicants, um, it's just so much waves of AI that, that are happening.
Challenges and Misconceptions in Hiring
00:11:57
Speaker
And every day, a new tool, a new technique, a new hack comes up.
00:12:02
Speaker
You know, there's a fascinating study and report that that got dropped about three weeks ago now. Forbes um published that 45% of job listings are fake. of the job listings are fake And listings are fake.
00:12:18
Speaker
Bob, job postings are fake. So then you you say, okay, well, let's put on pause for second, the 200 applicants that are trying to find a job and they all look the same and they're all perfect.
00:12:30
Speaker
What's going on with the hiring of the companies? Like, what are they doing? And there's a variety of reasons that is happening. One is there's data, um,
00:12:42
Speaker
farming, right? So they're posting positions, there's they're leaving positions up, re ah posting positions to get not only data, but to like, you know, if teams, if they've had a reduction in force and they've planned to rehire, but they're delayed because they're waiting to see policy or economy or macro events play out, um they may say, well, look, we're to their teams where we posted the position, we're looking for the right person.
00:13:10
Speaker
But then they never actually execute on that. So there's a lot of variety of reasons why organizations are keeping positions up. But I thought that number was was much higher than I had expected.
00:13:22
Speaker
That's a that's an insane an insane statistic, certainly higher than I had expected to.
00:13:29
Speaker
did Would you say then that some of the hiring challenges are more about talent availability um or about processes, decision right?
00:13:42
Speaker
Well, i think I think then the other thing that you see is while um the ah the the macro events are causing some organizations to be slower to hire. And and I mean, the jobs reports out and you know the data is the data of like what the hiring is is going on. But it's kind of interesting. it's you know A job isn't a job. It's not apples and oranges, right? Like so somebody gets laid off from a knowledge worker job in Amazon on or Microsoft. um And then maybe they find work in another role, but it wasn't that same, you know, pay or whatever. But we're at this perfect inflection point while there's this macro events that are occurring that are causing some organizations to pause um growth initiatives and hiring. Others are, by the way, like if you're a...
00:14:32
Speaker
AI company, you're building data centers. So it's very specific to the kind of, you know, business you're in. But i think the the challenge that you're also seeing is, um you know, wrapping employees, actually even replacing employees in some case. So I was at the Silicon Slopes event last week and in Utah, in Salt Lake City. It's a tech conference and and you just get to see this kind of great cut of how organizations and software companies and all companies really um in Utah are leveraging tech. There was a company there that has a staffing agency for um digital employees, basically AI agents that now they're going to help staff companies with.
00:15:20
Speaker
So if you think about organizations that are at that point of like, okay, should we hire? Should we, you know, hold for a little bit and see how this plays out, whether we can leverage some of the technology now to do things at a more, you know, ah an advantageous cost basis? Um,
00:15:41
Speaker
Put aside the existential crisis of of that to the workforce and humanity, but just say, okay, from ah from a company perspective, they're driven by profit motive. They respond to the shareholders. They have to reduce costs and increase profit. i mean, that's that's going to be the game until that that whole ah you know game changes, which I don't see that happening anytime soon.
00:16:03
Speaker
talk Talk to me about what you saw there. Talk to me about this company. you know If somebody is playing with this idea of you know bringing on agents instead of you know human beings, does that fundamentally change that hiring process? How do you go about the hiring process in the event that you're looking to bring on an AI agent? What does that even look like?
00:16:33
Speaker
Yeah. So um from an agent perspective, like what like I'll just tell you, so that from that company's perspective, they're they're focusing in first role base, right? as Sales SDRs, right? Outbound SDRs, picking up the phone, AI agent calling out, sending emails, things like that. um There's other agents that they've spun out to. So they had about five or six that they were trying to say, hey, these are, you know, staffing, ah you know,
00:17:02
Speaker
agents that you can use and and hire. um I'll tell you from Cadian's perspective, we've already got a couple that we're selling. um When I think about our screening technology, conversational AI to call to a candidate um and screens to say we have those 200 candidates, we can actually have a a smart screen is our is our tool that will set up a phone time a call time, then call the person, have a conversation,
00:17:28
Speaker
track and report so that the recruiter can then look across those 200 and say, okay, these are the top five that I'm interested in Now, we're not trying to decide for the recruiter. We still want the recruiter on hand on the wheels and in in in charge of this, but that recruiter doesn't have to have 200 conversations. They don't need 10 recruiters having conversations with people. They can leverage AI now I think that experience, the the jury's still out. Will that experience let you know stand the test of time? Will candidates want to work for a company that's leveraging that or not? Like I think some of this technology we're we're launching, we're working with our customers to try it out um and we'll see.
00:18:14
Speaker
That's one example. Another one is a product we have called Smart com Communicate, which is basically a level one HR support desk. that's an agent.
00:18:26
Speaker
So we have just like ah ah we've got a special kind of ah proprietary LLM that we've designed around this. You load in your PDFs, your documents, your, you know, your, um your benefits programs, all those things. And then, um you know, have a question about my vacation balance, or I have a question about, um you know, what is the policy for, you know,
00:18:51
Speaker
ah parental leave for maternity leave or something like that, I ask the agent first. And then you know if I get need to get something more, I go straight to the, the or it escalates fast to the human behind it, supporting it.
00:19:05
Speaker
My point is, is that this these kind of layers are going to help make the recruiting team be more strategic will you But you can't avoid the question of like, well, does that mean you only need one or two recruiters for a business instead of 20? Like that is a question. That's a question. when I'm curious when we when I think about these autonomous you know recruiters calling and having these conversations, having hundreds of conversations so that the that the human doesn't have to –
00:19:37
Speaker
um what kind of guardrails What kind of guardrails are up to make sure that in this this distillation process of information, right just the distillation of information that goes on in these conversations, that it's being put together in a way so that that candidate has that best foot forward? is that ah do you ever hear that as being a concern? Does it ever miss things?
AI's Role in Organizational Culture
00:20:03
Speaker
Oh, yeah. So there's probably two kind of in the in the recruiting space. There's probably two um big lighthouse moments right now of what's going on. We've got a lawsuit that has been filed that goes to court later this year um against Workday.
00:20:20
Speaker
And they had automated. And really the the the guts of that, when you boil it down, is um the hiring, the the candidates got together and sued Workday because they were applying to jobs for different companies that were running Workday. And then they were getting automatically declined, like within seconds, right, after application. So no human interaction overseeing. It was automated and it was automatic and um They raised a um a lawsuit for that. The net the last the second one just hit ah two weeks ago against Eightfold.ai, and that was around –
00:20:58
Speaker
And not that, not the the the auto, ah but it was it was really the auto ah matching without giving um any kind of notice or, um you know, getting approval from the employee to be measured or the candidate to be measured by AI about their capability. So you have to get consent. You have to like, so what we've tried to do is be very careful about, you know, we're not having AI automate the task.
00:21:27
Speaker
um without human interact interactivity. That's one aspect of it. But there's heightened scrutiny. There will be continued to be heightened scrutiny and legal focus on this area.
00:21:39
Speaker
um The standard that we've got, and we've built an entire kind of anti-bias ah page and document to prove kind of ah transparency, right? We want transparency to anyone from the candidate to the company so they could defend why they're, you know, that this isn't some kind of magic black box. This, so we built all that.
00:22:02
Speaker
The next step is to take that through a process, which we've started, which is ISO 4245,
00:22:10
Speaker
001, I think is the ah specification. So that's a standard, um which is an anti-bias AI standard, which is gaining traction. And I think all B2B AI platforms will have to adhere to that, just like you have to adhere to SOX, to compliance, and like all of these kind of security requirements and AI requirements, like there'll be an hardening Things are moving so fast, but there will be heightened scrutiny. And then an outcome is a higher focus around compliance and making sure that your solutions are not biased.
00:22:49
Speaker
um You know, in the recruiting space, I'll just end on this. ah you You have to maintain seven years of hiring records. The EEOC is very focused on discriminatory hiring practices. So you have to be able to defend that you've hired in a non-discriminatory way um and that is at least seven years of data you need to maintain for companies of any kind of significant size.
00:23:13
Speaker
You know, I'm kind of curious. that First of all, you just covered a ton of ground. And so, which is good. no like i I like that. um I love it. But it it it a lot of different things kind of make me come to the same or a similar question, right?
00:23:31
Speaker
when it comes to how we're hiring, who we're hiring, the role that AI has in the hiring, um whether it's in the sourcing or in the ah you know workflow of of of interviews, right? Or distilling that information.
00:23:52
Speaker
if... or if we wind up hiring the AI bots. I guess the the question that I was having, and I feel like I'm about to get another waterfall of information here based on the question alone, but there's there's a cost to these things, not just financially, but culturally and operationally, right?
00:24:18
Speaker
There's a, of of even, and and sometimes it's the cost of getting it wrong. right? Sometimes there's ah a cultural cost of of even getting it right when you start using a lot of these tools um either to replace or enhance or augment somebody's work. And I'm just kind of curious, like you talk to customers all the time. What do you see in terms of their own, you know, organizational health, right? That that sort of cultural or operational cost that comes along with these changes.
00:24:51
Speaker
Yeah, I mean, look, it's it's ah it it really becomes almost, ah i mean, a cultural, but it's it's almost an existential question as you start you know looking at how integrated this technology is coming in in now into our into our lives. um It really is pervasive. If you're a knowledge worker,
00:25:11
Speaker
and it's and you're not leveraging kind of all the tools, then you're you're just behind, like you can't keep up. um you know and and ah But I'll give you one thing that I thought was was fascinating. um There was a study last summer that got released um that showed somewhere around 15% millennials would prefer an ai manager then a a real manager.
00:25:37
Speaker
Wow. I will tell you that I have since questioned my daughters at the university, freshman, and I've, I've questioned personally her friends and almost all of them.
00:25:52
Speaker
ah answer was they would prefer an AI um manager. And I start to question why. Well, like what's is as well, we don't have to deal with the like the the i mean, the way I heard it, the human bias.
00:26:08
Speaker
Right. And that's the you know, I don't have to worry about trying to deal with my manager who's, you know, emotional wreck because they didn't have enough coffee this morning or whatever, like it's consistency.
00:26:21
Speaker
And Now, you know, it's always, I always think of it as like, well, you know, there's the carrot and then there's the stick and eventually like consistency, you know, to get you in the door and, you know, ah but, but as, as the, as the, the pressure gets turned up in any business, uh, performance, you know, needs to stretch and increase and all of that. Um, and you may not have with those kinds of technologies or those management structures, the, um,
00:26:51
Speaker
the latitude, right? To be able to discern risk and assess like, okay, I'm going to give this, because some of your best employees, i'm mean, the best people that I've ever employed, like I had to help them and they helped me on a mutual journey to get to a very successful state. Like that is an investment of time and energy. And that nuance is going to be really interesting to see if if these systems would ever be able to pick up on that. um I tend to think that is the secret sauce of human, but, you know, time will tell um whether that's that's true or not. um But yeah, I think the last thing I'll say on it is we have a technology called smart feedback, which...
00:27:37
Speaker
does this conversational AI not for the candidate, but for the employee. So imagine polling your workforce in a non-biased way and a non-confrontational way, new employee, day one, day five, day 30, exit interview. You can pull that in a consistent way to say, okay,
00:28:02
Speaker
Are you happy? you know where Where are you at with your – and where they may not be comfortable telling their manager that they're really mad that there's no Twinkies in the break room anymore because they they changed that way. They would tell the AI that, right? Because they're like, oh, you know, and or if they're looking for a job, if they're really unhappy with their pay or something else, they may expose that to a non-confrontational like ah polling AI. And then think about the management bias that exists in human bias that exists in the management chain of organizations. Sure.
00:28:42
Speaker
For a C-level executive to be able to get insight into their workforce and the real risk that's going on there, that's kind of a ah a different idea and maybe addresses that, what we talked about before, having a 130% turnover. If you could change that dynamic, you start to have real-world results for your business and for the people working there.
00:29:05
Speaker
so yeah that's um Yeah, I can totally see how interacting with ai it's ah yeah there's this technology veil, right? Where you don't necessarily feel or wouldn't feel judged the way that you might by a human.
00:29:26
Speaker
So your answers could be more open or, you know, more honest, or I don't know, think of another adjective, but, um, just simply because you're not being stared in the eyes by another human being that you might look up to, or you might respect, or you might not like, or you might be terrified of, or, you know, there' are a whole, a whole bunch of things. Um, that's really interesting.
AI's Influence on Job Dynamics
00:29:52
Speaker
When, and when, when, when a candidate is going through this, this pre-hire process, um, you know they i feel like they learn a lot about the company's culture. and um you know Even insofar as how they use ai you know or how they're incorporating it into different you know elements of the business. um What do they learn about a company before they even start the job? What what are the signals you know that you think are are louder than others that you see just most prevalent?
00:30:27
Speaker
You know, I think um that, you know, people that are that are really out looking, you know, for and and of course, the whole spectrum is is ah in the high volume world, you're using job boards like Indeed. And and and and by the way, that's kind of a facilitating, ah you know, technology of why there's one hundred and thirty percent.
00:30:48
Speaker
ah turnover because in that retail world, they do things like, hey, there's a concert next Tuesday I want to go to. So I'm goingnna quit this job because I got two other jobs that I can go apply to through this easy access for automatic applying to jobs. But, um you know, I think to your point of like, what do they find out about the culture of ah of a company like,
00:31:13
Speaker
I do think, I mean, AI can actually support ah more effective communication in some ways, um being able to do things like give a chat, an LLM chat experience on the front end of a of a job listing, right? To be able to find out about what is the culture of this company and have real answers, uh, given up without having to feel like you're Sherlock Holmes and go into glass door and find all these things out, which you should do anyway, right? You should go, you should investigate any kind company before you decide to hit your wagon to it.
00:31:48
Speaker
But, um, I think that it's, it, it can help that. I, I don't know yet if, if we're at that, that tipping point of, you know,
00:32:01
Speaker
There'll be an anti and there already is an anti AI reaction and repulsion as well. So it's like, were you know, finding that balance is probably going to be something that organizations have to figure out how to do.
00:32:15
Speaker
um Because, you know, it it's I don't think it's going to be a one size fits all kind of situation. I think I like you can leverage some technology to actually surface things like this is the culture. This is how we operate. This is our values um and help.
00:32:32
Speaker
Any candidates understand that. And then, you know, there'll be other organizations that just go over the over the line. And, you know, i mean, you take a look at some of the the big news, the big layoffs and and kind of radical transformations that are going on in some of the big tech companies right now.
00:32:51
Speaker
The developer is under extreme pressure and fire because that has been one of the first places that AI has yeah automated its scale.
00:33:04
Speaker
um And the ability to, to I mean, VibeCode is, is i mean, yes, VibeCoding and being able to create a simple app and deploy it to test it out. Will it then be productized? Can you, but the idea idea ideation and the deployment of that stuff, I mean, you can, you can do things in, in minutes and hours that used to take weeks and days and months. So, amazing so it is, so it's like that.
00:33:31
Speaker
And you go look actually the data. i i wish I would have brought the the graph.
00:33:38
Speaker
2022, 23, the spike on on Indeed for software engineers, it was in the US, hundreds like hundreds of thousands of job postings. It was like couple hundred thousand job postings. Now it's down to like less than like 25,000 or whatever it it is it across the US. It was...
00:33:58
Speaker
completely fallen off a cliff because not that there's less code being written, but the people that are in seat are not scaling by hiring extra dev devs. They're, you know, they're rolling out that, you know, Claude or whatever they're going to use to, ah to, to, to write across the faster. So that, that whole dynamic is happening too.
00:34:23
Speaker
And then some, but I do think there'll be ah a bit of a kickback, um, And some companies are going to, they're going to have to navigate this and come up with the right policy and governance so that they, you know, they can hire. i mean, companies that are fully AI and have a CEO and isn't good. Like that's not competitive. Like you have to, you know, i think you need the human element, I believe, but again, time will tell on that too.
00:34:52
Speaker
Let's look at the, towards the future. I want to hear some predictions for, you know, kind of what's coming down the pike. um You know, what what you feel like the next generation of candidates will want from an employer, maybe in how they work and where they work, um maybe in some expectations of the hiring process, you know, everything. Is it agents?
00:35:19
Speaker
Is it a smarter hiring? um Feedback tools? So I'm going to tell you couple couple stories. and But before I do that, um I mean, I am a technologist and have spent my career in software and SaaS and technology. And overall, I've been um very optimistic about you know how technology can increase the you know profitability and company. x you know it's It's been a um There's a lot of good that's come from where we're at. does It feels like we're at this kind of really interesting inflection point now where, um you know, the the technologies that we're talking about now.
00:35:57
Speaker
um And, you know, it very well could be, by the way, that the people at the start of the Industrial Revolution were having the same, you know, doom chicken little experience that a lot of people are having today of like, hey, this is going to, you know,
00:36:12
Speaker
destroy our our our jobs and who knows what the future is and that kind of uncertainness of transformation and change. But I think that's ah that's a constant of like human um you know society and culture. And we're always doing that. We're reinventing. We're trying to change things. And um There's a lot of good things that are happening because of the the boon of technology and AI with gene therapy and solving genetic disorders and all kinds of stuff. It's crazy.
00:36:40
Speaker
um Crazy good. The head of um anthropthropic Anthropic Claude AI resigned this week and kind of – very public fashion, sent a public resignation letter, basically said the the world's falling apart. um The um people don't really understand what's going on with AI, even though we think we do because we're using LLMs to write our emails. um He goes, you don't really understand. So I'm going to quit and I'm going to go into the woods and write poetry. Basically, that was his.
00:37:17
Speaker
The world's falling apart. So I'm going to go write poetry. um which I thought was ah was fascinating, um you know, as outcome of of of that. um You know, I think that that we're going to see um the continuation of adoption to these things. I i think are our governments are going to respond. They're they're not a very proactive. They always respond. I mean, pretty much every government in the world responds reactively to something that's changing. So whether it's policy and controls, like they're going to have to figure out um because the game on the on the playing field of work and, you know, the monetization of your hours to product to is
00:38:07
Speaker
um And I don't know if universal basic income will you know fix it. i don't know I don't know what's going to fix it. All of it doesn't seem like it's it's going to solve some of the the changing in work you know situations that we have. But as far as like companies hiring um and taking advantage, I really think you're going to be able to see companies launch with very few people and go unicorn, like, you know, solo ah at level people that could get to, you know, huge valuations, huge impact to our society with new products and services that are very small teams. So the future could look very much more like gig economy could be we're having, you know,
00:38:55
Speaker
multiple things we're doing simultaneously and, and it becomes less like W2 employees and more, you know, part-time gig world.
The Future of HR Technology
00:39:04
Speaker
I will tell you this horror story. The first AI agent last week I saw on they went, um I think it was a Claude bot, ah spun up and,
00:39:16
Speaker
actually hired a human completely autonomously to go rent a human.com or whatever went on you and hired a human to go across town and pick up a package and deliver it somewhere else, completely independent of any other human interaction.
00:39:34
Speaker
We've had the first like observation where an agent hired a human to do a task for a completely disconnected kind of entity that that was ah you know saw a human behind the agent, obviously, but that human didn't actually go through the hiring process. The agent did.
00:39:50
Speaker
That's fascinating because you could then start to really like if if if you were to say recruiting becomes completely automated, which I don't see that in the near term, especially because the scrutiny and legal, you start to see that could that could really be interesting of like hiring, firing. And you know I just don't think with the laws, even as they're in place today before they evolve, that's there'll be a lot of lawsuits flying and all of that. So there's going to be an interesting dynamic of how that, that, that happens in the future as well.
00:40:25
Speaker
Any predictions for, for, for the future of HR tech, like, you know, shifts for, for that specifically, you know, bigger or, or small, not just ah predictions in the future of, of work and how it's yeah actually done. But what about them that the, the tech side, the technology side on, on HR tools?
00:40:43
Speaker
So the tech side, i think, needs to get a lot more specific. I think the SaaS industry built a product and for many years, and I benefited from this as part of that industry, and we would lay down that product over and over and over for customers in the ah HR tech world. And basically, kind of they would align their products.
00:41:07
Speaker
their workflow to our product kind of under the umbrella of best practices, right? And we kind of got consistent. and then there was value. All organizations were kind of doing some things that are very similar. And there was some legal checks and balances and things like that.
00:41:21
Speaker
However, I do think that there was also at times Not always, but at times you lost the nuance of that company, the problem that they had and maybe the culture that they had all of a sudden had to sit within a framework and a process that they didn't design. They didn't really have.
00:41:39
Speaker
I think the future of the technology can be a lot more specific and custom, ah even under the umbrella of of subscription software or you know, however that looks in the future.
00:41:51
Speaker
um i think pricing models will change. I think you'll be more outcome based versus subscription. They still want cost certainty. So they got to figure out a way to have cost certainty in budgets, but they want to be charged on outcomes versus, um you know, actual, you know, just ah an annual subscription. So that's a whole level of complication and that we have to navigate. ah But things like dashboards, you know, in integrated, um you know, data, how do you do that? Well, the future is going to be more like, okay, tell me, um you know, what my hiring trends are in in New York and how many people are i behind, how many people are behind And it can just answer that question.
00:42:38
Speaker
You don't need reports dropped into your email, you know, once a week, you need actual live interactive data that you can operationalize in action. So all of those things are up for grabs now in a, in ah in a new way than they were even two years ago.
00:42:57
Speaker
Yeah. I think I see a lot of that stuff coming. I kind of love this idea of how software can become hyper-personalized, you know, which, ah which I think is,
00:43:09
Speaker
actually really promising. I mean, i think that that's, that that's, that would be an incredible thing to look forward
Building Resilient Teams
00:43:16
Speaker
to. um To wrap it up, I'm always really interested to hear um, Bill, you know, if, if, if a business leader, you know, wanted to, to build a strong team, but really kind of feels maybe overwhelmed by hiring or sort of uncertain, you know, the best way to kind of go about doing these things or even making a decision if it's human or non-human that they need to go.
00:43:39
Speaker
Well, what's the single most important piece of advice that you would give somebody in this, uh, you know, who's, who's sort of approaching these things right now. What do you tell folks? You know, i think I think when I'm looking to hire um really throughout the organization, whether it's leader or someone that's, you know, relatively, you know, individual contributor um on ah on a project level or whatever, it's it's about their ability to adapt and learn. And, you know, it's it it's one of the reasons I kind of had always fallen in, you know, in HR and learning technologies and all of that. I got
00:44:15
Speaker
really excited about it because there's always so many angles to it. um But someone's ability to, you know, willingness to not stand on their learnings and their history and say, you know, hey, I did this, I did that. Yeah, it's fine. But there's really, especially in the climate we're in, there really is no cut and paste. Like you have to put your hands on keyboards, you have to play with things, you have to learn, you know, even in retail where you're selling products for a store, like the buyers have changed, what attracts them has changed. um
00:44:53
Speaker
You know, so it really is. and and maybe that's some of that's in that climate, ah social media, um in a knowledge workers climate, like the technology, um But we are in a massive like period of change. i think there was a period of time that felt very stable.
00:45:14
Speaker
um I don't think it was, but I think it felt stable in a lot of ways, especially in the US. But that time's gone now. And now it's like back to like scrappy learning, trying, which means you're failing and building a, like being able to participate in a learning culture. And then, you know.
00:45:36
Speaker
that's That's what I would say is if people can do that, then they can be successful anywhere. I love it. That's good advice. Thank
Conclusion and Listener Engagement
00:45:43
Speaker
you, Bill. Appreciate you joining me today. Thank you. it was great. I felt like I talked to him. felt I wanted to hear more from you, but I i spent the time talking. Sorry about that. We'll save that for the next time. Big thanks to ah all you watching and listening to Mustard Hub Voices Behind the Build. Be sure to subscribe so you don't miss the next episode.
00:46:01
Speaker
Please visit mustardhub.com to learn more about Mustard Hub and discover how we help companies become destinations for workplace happiness. and turn culture into a competitive edge. Until next time.