Brett Waikart Podcast Transcript
Brett Waikart joins host Brian Thomas on The Digital Executive Podcast.
Welcome to Coruzant Technologies, home of the Digital Executive Podcast.
Brian Thomas: Welcome to the Digital Executive. Today’s guest is Brett Waikart. Brett Waikart is the CEO and co founder of Skillfully, a public benefit corporation that’s on a mission to build a fair and more inclusive future of work. The Skillfully platform generates customizable virtual simulations that help employers see applicant skills in action during the hiring process, letting them look past traditional resumes to see real applicant skills in action and spend more time with great talent.
Prior to Skillfully, Brett founded and led Portfolios with Purpose, an edtech non profit that used realistic virtual simulations to help young students develop critical financial and investment literacy skills.
Well, good afternoon, Brett. Welcome to the show.
Brett Waikart: Hey, Brian. Thank you so much for having me excited to be here.
Brian Thomas: Absolutely. Love this. Appreciate you making the time hailing out of that great state of California. They’re up in the Bay area. Appreciate that. I’m in Kansas city, but Hey, we’re making a podcast out of this today across the country, halfway across.
So Brett, let me jump into your first question here. What inspired you to co found skillfully and how does your vision for a fair, more inclusive future of work shaped the platform strategy and offerings?
Brett Waikart: To start, let me just step back a half step here. So I’m the co founder and CEO of a company called skillfully.
As you mentioned, we are a new type of employment platform. What we focus on is using the technology of the day using AI, but using it a little bit differently. Then the way a lot of other employment platforms use it, many other platforms will use AI to maybe better filter incoming resumes, maybe improve the quality of resumes might use it as a part of an applicant tracking system or to automate some part of the process.
We actually don’t focus on any of that. What we do is we use AI to replace a lot of that very resume driven hiring process and instead supplement it with virtual simulation scenarios where, which are powered by AI engines. We can get into exactly what that means, but we create. What’s basically a digital twin of any of the given jobs that we will support.
So when somebody applies to a job through skillfully, or if an employer is using skillfully to support one of their open roles, what that means is that in addition to being asked for a resume, you’ll also be invited into one of our simulations or several, but what that will give you as the applicant, the chance to do is to demonstrate, to show your skills, not just describe them.
For the job seeker, this is great. It gives them an opportunity to be seen for what they can actually do, not just necessarily be seen as a piece of paper. And then for the employer, it’s a huge advantage because for them, it lets them make every decision downstream from those simulations with full visibility.
Into exactly the skills that this applicant is bringing to the opportunity, the interview, ideally the role. So it just helps kind of promote better transparency on both sides of the market. It leads reliably to more efficient, more effective outcomes for the employer and really more accessible opportunity for, for job seekers.
So now if we reel this back and focus on kind of where this got started, skillfully actually grew out of, uh, an education nonprofit. That I co founded and ran for years and years and years before skillfully, but kind of like our approach at the employment company and skillfully, the nonprofit portfolios with purpose use simulations to teach skills, to help folks develop financial and investment literacy skills that they may not be getting the education for in the classroom.
And at its peak, we were reaching 10, 15, 20, 000 young aspiring job seekers every year. And we actually got approached by some of the biggest names in the financial services industry, Barclays city, others, all of these conversations always started the same. It was always a knock on the door and, Hey guys, wonderful charity you have here.
How can we support?
Thank you very much. And then the second question, like clockwork, the employer would always lean in and ask, okay, can we, do you think we can look at the data and what they were really interested in?
Was essentially this idea of demonstrated versus described skills. This was an education focused nonprofit.
We were not in the employment space, but we found ourselves continually getting old into this employment conversation. So after a couple years of kind of recognizing that. Employers had a very real appetite for this kind of information, this kind of insight into what a job seeker is really capable of, what their real skills actually are.
We decided to honor that and we took that idea and basically spun out a separate for profit. Public Benefit Corporation, it’s a for profit company that has a dual mission, a financial and a social mission. And the financial mission, of course, is to grow the company and to make this employment platform as big and as scaled up as possible.
But we feel really fortunate. Our social mission to create a more accessible, skills driven pathway to meaningful employment opportunity. We can fulfill both by delivering this platform. And we’re just super excited to be here and get to share this now with audiences like yours.
Brian Thomas: Awesome. Thank you so much for sharing really the genesis of everything here.
What I really like that you’re doing, though, is really providing a solution to an age old problem of applicants and employers trying to get that right fit and having it a better screening process by creating these simulations is phenomenal. So thank you. And Brett, how does Skillfully’s use of customizable virtual simulations enable employers to assess real world skills?
And what impact do you believe this has on leveling the playing field for job applicants?
Brett Waikart: Listen, great question, and I can just build on kind of your commentary there to answer that. This is a very interesting moment in time to be building a company in the employment space. We hear from employers constantly that there is this pervasive sense of overwhelm of this incredible incoming wave, a volume of applications they’ve never seen before.
And what’s happening here, what’s causing this is a near universal adoption. Of these generative AI tools that we hear about, we read about, the chat GPT’s, the quads, the Gemini’s. When we look at this technology, just in kind of a historical context, the race to the first 5 million, 10 million, 50 million, 100 million users, these tools have beat every record.
And it’s especially concentrated at kind of the gens, the type of the seniority stack of job seekers, those folks who are just coming out of school, just entering the workforce. All of them near 100 percent have not just adopted these tools, they’re not just fluent with them, they weave them into their everyday life.
What that means when those job seekers enter the workforce, when they go and they start crafting their resume or they apply to a particular company, their thought, the first thought is to say, well, how can these tools help me in that process? Let me. Take my old resume and take that in the job description I’m applying to.
You can stick them both in chat GPT and ask the model, the AI tool to spit out a perfectly keyword matched job application, a resume. And in a single instance, that’s a wonderful thing for that job seeker. They have used those tools effectively to create. And craft a better suited, more aligned application.
But the problem comes when we realize that it’s not just that single person who’s doing it. It’s thousands. It’s millions of other job seekers who are moving into the workforce, who are all submitting application after following exactly the same process. The felt experience for an employer is one where the tool that they have relied on for the last 10, 20 years, really applicant tracking systems that.
We’ll filter incoming resumes based off of how well aligned is the text of that resume to the text of the job description. How well is the application aligning with those requirements? Well, every single one is perfectly aligned. And not just that it’s been Shakespearean prose of why this is the only job this job seeker has ever wanted.
But In reality, many of these job seekers are doing this exact same process, not just dozens, but hundreds of thousands of times in the course of them looking for that next job. The supply and demand dynamic in the workforce right now is so heavily biased against those recruiters. The odds are stacked so deeply against them and in the favor of the job seeker who has this powerful new tool.
So enter our simulations, enter this new approach. Where instead of using AI to try to find those tiny little nuances or differences in these really AI written, AI generated resumes, what we offer an employer is a chance to sidestep that entire process, that unending resume review entirely. And instead of relying on how somebody is going to describe their skills, let’s actually ask them to demonstrate those skills.
And let’s make hiring decisions, interview decisions based off of visibility into exactly that, who has exactly the skills for the job. Every employer, every recruiter is in their seat because what they really want at the end of the day is they want to be able to identify, meet and hire the very best talent for the job.
There is so much noise. Out there in the job market right now that these employers need to sort through our tool. These virtual simulations are a wonderful way to be able to cut through that and to kind of get to that really accurate hiring signal. This comes down to exactly how we built our platform.
But when you interact with chat GPT, it’s you in one model exchanging information. What skillfully built and we just announced this in a recent product release. We have an infrastructure that we call Lego LLM, literally like you’re playing with Legos. You can take individual models and stack them to be able to build these beautiful, dynamic, very textured virtual scenarios, virtual simulations that can map back to any kind of interaction, any kind of task, any type of tool usage that might be relevant for the job and create that very accurate digital twin of what it looks and feels like to be in the job.
What this does is help employers really satisfy what they want, help them to really quickly hone in on who actually has the skills they’re looking for. But the beautiful thing, the mission work on the job seeker side is that, importantly, We don’t care what path a job seeker may have taken to develop those skills, to be able to demonstrate those skills.
We got started working with the City University of New York system, 23 urban community colleges, one of the largest urban college systems in the United States. These students are overwhelmingly first generation college students, they’re probably working a couple different jobs, they’re probably there on scholarship.
These are not the students who rise to the top of a resume pile. This is not going to be in the target list. The CUNY school won’t be really in many of the target list of some of the top employers in the U. S., but these simulations give those students an opportunity to be seen for the hardworking hustlers.
The highly skilled and highly qualified job seekers. They really are. What this means is that for the job seeker, they get to be seen for their real potential. They get to be recognized for that ability. And that’s a really beautiful outcome for both the job seeker and for the employer.
Brian Thomas: Thank you.
Appreciate you unpacking that. I love your platform because it meets the needs of both parties, right? The applicant and employer, which is, I think, awesome. But I do like the fact we talk about AI all the time and it’s being applied in so many different spaces today. But love the fact that you can filter through all that noise, find that right candidate or may a particular skill set.
So I appreciate that. And Brett, in your opinion, how are virtual simulations revolutionizing the talent assessment landscape and what potential does it have? Do you see for these tools and other areas of professional development?
Brett Waikart: Yeah, this is where we get really, really excited, Brian. So if we accept that it is possible today to be able to build these, again, these digital twins, these virtual experiences and simulations that are nearly identical to real workplace challenges, how work is expected to be done.
It workplaces across the workforce, across fortune 500, all the way down to small startups, the availability of that as a sandbox, as a virtual environment that’s available, not just for hiring, but think about the availability of that when we’re thinking about not just demonstrating skills, but helping people to develop skills that are necessary, maybe for that first job, but especially for the second, third, fifth job that they may have in their career.
We started at the tip of the spear for us is the kind of point of hire. This is everything that we’ve just described so far, but let’s think about a giant timeline. Let’s think about somebody who, uh, let’s start all the way back when they’re in college before they’re even thinking about entering the workforce.
And then let’s extend that timeline all the way out until they’re a seasoned professional. The availability of these simulations of this platform means that for that college student. They suddenly have this rich, tactile, detailed environment where they can dip a toe in the water. They don’t have to go get a summer internship.
They don’t necessarily need to go get a job. They can use these as a way to demystify and explore the skills that are relevant for quite literally any career path they could possibly imagine. That’s transformative. We know, especially job seekers who might be underrepresented in the workforce, but any student, anybody who’s thinking about this, we have blinders on.
We don’t consider the full range of options, the full range of opportunities. And what we’re seeing today is that introducing these simulations through the Career Service Center, quite literally in the classroom, where a lot of universities are using these today, that’s transformative in terms of the potential just to help people realize, well, what else they can do.
Now, let’s fast forward beyond that point of hire when somebody comes through our platform and gets a job through us, that employer gets a very detailed map of all of the skills that that new hire has been able to demonstrate. It’s our skills profile. It’s the skillfully version of a resume. Well, that document is like a map.
It is an incredibly useful tool. When you start thinking about a new hires 30, 60, 90 plan when they’re first coming on board, well, okay. What skill gaps do they have? Maybe they have a good raw talent in sales or in engineering, but maybe they don’t quite yet know how that skill should be applied. With that particular employer, well, this is a sandbox again that they can use.
They don’t have to risk live deals, a customer relationship. They don’t have to risk looking silly in front of a colleague. They can use this as a learning and development tool in the same way. And this is what we’re again seeing right now, which we get so excited by. This can be a resource that sticks with that higher through their career, and they can continuously come back and practice and develop skills that could be relevant for the 5 or 10 or 100 different roles that they can move into that 2nd and 3rd and 4th job.
This is a fascinating time, like I said, to be in this industry because this just explodes wide open the full cycle of employment from rehire in college learning and training to get a job all the way through being a seasoned executive. These simulations let you be seen. For exactly what you can do and then give you that opportunity to develop and demonstrate further skills in a way that will help you advance that career beyond your current job.
We’re seeing that put into practice right now with some of the nation’s biggest employers and it is just beyond exciting in terms of thinking about how this could grow in the next couple years.
Brian Thomas: That’s awesome. I appreciate you again going through some of the different nuances and obviously use cases, you know, having those digital twins or virtual experiences as you call them of these real world scenarios is certainly leveling the playing field, but I liked you mentioned starting in the classroom, giving folks that head start.
I think that’s amazing and I just love it. And Brett last question of the day. If you could share What emerging trends or technologies do you believe will most significantly transform hiring practice in the next few years, and how is Skillfully preparing for these changes?
Brett Waikart: In a lot of ways, this is the most important question of the day, and I might answer it a little bit differently.
Which technology is going to play a role in reshaping how employment is done?
It is undoubtedly artificial intelligence. And let’s break this down further. That’s a big hyped up type of acronym that’s used everywhere. Let’s get really, really specific about this. I think that the first wave of AI solutions in the hiring space There was this joyful application of AI to any problem an employer or hiring manager might have.
There’s AI to automate certain processes, there’s AI to run interviews, to be a better filter of resumes. It was basically this, let’s throw everything against the wall and let’s see what sticks. We’re finally coming out of that phase and we’re walking into a new chapter where we have a much more refined idea.
Of exactly how AI can be used to be that most transformative application. What we’re finding is that AI is most powerfully used when ironically it’s paired with maybe more traditional software, what’s called deterministic tools, tools that are pre scripted or written already, instead of just letting AI run amok, instead of just allowing it to be some kind of terminator intelligence in the sky that yes, this person is qualified or no, that person isn’t.
What we’ve been finding is that when you pair AI and you place it into a more structured environment that the impact is actually amplified. To give a specific example, for us, we pair our AI with a very structured skill taxonomy. We are asking our AI to just constantly loop between these simulations and the observed behavior.
And then a fixed set of definitions of not just the skills that are relevant for a particular role, but more importantly, definitions of functional proficiency, what proficiency with these skills looks like at all different levels of proficiency. And so what that then allows us to do is we can create these incredibly rich tactile textured environments that allow people to try their hand, get their hands dirty with a particular role and demonstrate those skills.
But bounding it in this kind of a structure, a hybrid AI structure. That allows us then to, to kind of harness that intelligence, to harness that reasoning ability and to be able to make sure that it’s applied specifically to the problem at hand and the employer’s instance specifically to helping them vet talent far, far faster than they’d be able to do by themselves.
A favorite thing is. Chat GPT is like you have the power of 80, 000 interns in your pocket. They’re not smart enough to go off and run your company. They’re not probably smart enough to go off and just do all of this work on their own. But if you give them a very structured task, this is an incredibly effective tool.
When we look at the impact. That that hybrid AI fixed software approach yields, we see that this is a decreasing total cost to hire for an employer by up to 70%, purely just through the time savings of making sure that they’re spending time with the most qualified talent and not necessarily spending time with the folks that are still needing to develop their skills for the job.
That’s a 50 percent reduction in screening time. That’s a 10x improvement in conversion yield between identified qualified candidates and those who end up but in the seat in the actual job. We’re still finding these tactics that can take AI from a really interesting laboratory experiment. To a really useful, extremely valuable tool.
The goal really today, it’s not this march to AGI or super intelligence or kind of the more hyped up vocabulary that we heard in these early days. What we really want to do is we want to use these tools to unlock a never before seen level of efficiency, workforce efficiency of helping employers find the very best talent for a job reliably.
That’s what’s most exciting. That’s the emerging trend here is really saying, Hey, it’s time to take these tools out of the research laboratory and bring them to work, bring them to the workplace and those tangible ROI benefits. That’s the pot of gold at the end of the rainbow, but that’s what we get most excited about.
Brian Thomas: Very cool. Love that. The thing that I took away from it, you know, you talked about, we went back a little bit, how some of these ATSs, I think it’s what they’re called now. Applicant Tracking System.
Brett Waikart: Tracking System, yeah. ATSs. Everybody has one. Yep.
Brian Thomas: Yep. And back when we were, oh, we’re using AI. Well, that’s just doing some of the things that now is just kind of a second thought.
But the hiring process from where we were and where we are today, but where you said that you supplement or you augment those softwares where there’s some structure. So, you know, some of those pre deterministic software, I think, as you mentioned, really amplifies the power of intelligence to get the better results, obviously better talent.
So I love the fact that we are truly scaling workplace efficiency because of platforms and entrepreneurs like yourself that are getting out there and getting after it. So I appreciate that.
Brett Waikart: If I could just add one metaphor to this, I think what you just put your finger on is specifically the right point.
I’m a bit of a history nerd. And if you look back in time, the moment that we’re kind of passing through right now is exactly the moment we’ve seen before. But think about we go from the golden age of radio to the introduction of the television. The very first syndicated dramas for television that ran were black and white, essentially retellings of stories where the actors quite literally got into costume, sat at a table, and then still read off of a script.
Into a camera, but right off of a script, and just took exactly the same radio program, and that was their version of adapting it to TV. Now, fast forward a couple decades, and here we are in the world of cable, and of streaming, and of all of these different things that we could not have imagined then.
That is exactly where we are right now with the world of AI that those initial early applications were us just trying to connect with what was most readily accessible. The most relatable use case, but that was just a shallow, shallow picture. That was quite literally just the tip of the iceberg of. How these tools will be applied in the future and the utility, the value that’s going to come from them.
Um, I don’t mean to interrupt, but that was such a wonderful point that you made there.
Brian Thomas: Thank you. I appreciate that. And Brett, it was certainly a pleasure having you on today, and I look forward to speaking with you real soon.
Brett Waikart: Thank you, Brian. This was such a pleasure. I appreciate it.
Brian Thomas: Bye for now.
Brett Waikart Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
