This is a special episode, recorded live on stage at TA Tech Europe in London earlier in November. It’s a wide-ranging discussion about the state of our industry and where it’s heading with one of recruiting’s true pioneers, Jeff Taylor, the founder of Monster.com and the soon to be launched Boomband, . We debate AI’s true impact on hiring, discuss why traditional tools and approaches are failing, and explore what recruiting could become.
In the interview, we discuss:
• The story behind Monster
• How Monster almost bought LinkedIn
• Why has Jeff returned after two decades out of the industry
• What has changed in recruiting in the last 20 years, and what hasn’t
• Why resumes and job postings are failing
• AI’s real impact on jobs
• What is Boomband?
• Rebuilding trust in recruiting
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Transcript:
00:00
Matt Alder
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01:20
Matt Alder
It’s a wide ranging discussion about the state of the industry and where it’s heading. With one of recruiting’s true pioneers and Jeff Taylor, the founder of Monster.com and the soon to be launched Boom band. We debate AI’s true impact on hiring, discuss why traditional tools and approaches are failing, and explore what recruiting could become.
01:44
Matt Alder
Hi everyone and welcome to Recruiting Future with me, Matt Alder. We are recording this live at TA Tech. So we are on stage and we have a live audience. Make some noise just to prove that. Yes, thank you. Absolutely. Now it’s my privilege to welcome the legendary Jeff Taylor back to the podcast. So just for the benefit of people listening to this on the audio, give us a very quick introduction to you.
02:10
Jeff Taylor
So I’m Jeff Taylor. I’m the founder and CEO of a brand new company called Boom Band. I am the also the founder of Monster.com.
02:19
Matt Alder
Fantastic. That was a short introduction. That’s, that’s, that.
02:22
Matt Alder
That’s cool.
02:22
Matt Alder
So let’s start with a little bit of history because I think we have to talk about Monster a little bit in this. So thinking back to 1995. It was 1995, wasn’t it? Thinking back to 1995. First of all, who was in the world of work in 1995? A few people. Was everyone born by 1995? Anyone born after 1995? Okay, a few people. There we are. Just to get a bit of sort of context in the room. So some of you may not know or might not remember what a big deal Monster was when it launched and for the years afterwards. So My first question to you, Jeff, is when you launched Monster, what was the problem that you were trying to solve?
03:03
Jeff Taylor
So the idea, actually I started working on it in December of 1993, and were coming out of a fairly difficult depression. I don’t know if it was a recession, but it was a difficult moment and the growth was starting to happen and recovery was in full process. And were placing full page ads. I owned an ad agency that’s called Adion. We were placing full page ads in the Boston Globe. I’m from the Boston area and the ads weren’t working. And one of my biggest clients said, figure something out or you’re going to lose me as a customer. And so just the environment was the Boston Globe, the San Jose Mercury News had like 150 page help wanted sections at that point on special weekends.
03:59
Jeff Taylor
And all of the recruitment advertising that we know of today as job postings online was all done in the newspaper. So the thing people said to me recently is, oh, there was no competition when you started, because There were only 200 websites in the world when I started. By the time we registered it, were the 454th. But the idea of who our competition was the legacy newspaper companies, the dynasties of the era. And the newspaper was where you got your information at that point. And so the impetus for this was unhappy customers, both job seekers and employers. You had a marketplace where the Internet was nearly the same buzz, I would say, as AI today with the same sort of growth happening. You had the brow Mark Andreessen at the University of Illinois developing the first Mozilla browser.
04:59
Jeff Taylor
And you had free email, 1994 with Hotmail. And so you had this environment that was like building up of a ton of excitement, but you had unhappy customers. And so if I were to just compare that quickly to right now, you basically have the buzz of AI and you have a different overlay. 2022, beginning of 23, that was when everybody made salad. It was such a good environment. But since then it’s gotten very tough. So it’s a slightly different environment in terms of in 1994, it was low supply and high demand. Right now in 2025, it’s high supply and low demand. But the parallels in the market are incredible. And the main thing is unhappy customers. I asked last night at our executive session, you know, were the employers unhappy? And it’s like, absolutely, yes. The job seekers unhappy? Absolutely, yes.
06:01
Jeff Taylor
Perfect environment for disruption. AI is the overlay and our ideas are what we got in front of us.
06:08
Matt Alder
So I think you’ve actually already answered this question. I’m going to ask it anyway. So 20 years out of the industry, why now? Why make the. Why make the comeback now?
06:19
Jeff Taylor
So there’s a couple little chapters in there that might be fun. So I ran Monster from me as the first employee, first job posting, first resume on the World Wide Web, 200 websites in the world to 11,000 employees, 2,000 salespeople, couple billion in sales, close to 10 billion in market cap. And we survived 9 11. And the dot com bust basically happened in April or May of 2000. And so you had a struggling marketplace and were profitable. And so coming out of 9 11, sort of like the pandemic. Let me keep the challenges associated with both of those separate from this. But there was no recruiting for 90 days after 9 11. And so imagine having 5,000 employees and no recruiting for 90 days.
07:21
Jeff Taylor
And so there was a lot of pressure from my board and that pressure was that I needed to lay off people. We were talking about this last night in my spirit and my commitment to my employees was second to none. And I didn’t want to lay people off. And so at that point I lost my CEO role and I became the chairman and the chief Monster. And so that was the transition that happened in 2001, 2002. But I was still very active, opening offices all over the world. I opened 36 offices under my leadership. And also I had the opportunity to buy LinkedIn. And I went and met with Reid and we agreed. Call it 300 million. 300 was too low, 305 was too high. We had a back of the envelope for 304 million.
08:20
Jeff Taylor
I took it back to my board and my board turned it down. So I resigned and I gave 18 months notice. It wasn’t a big temper tantrum, but I resigned. And so that started me moving out of the business. Is this crazy story, right? You know, LinkedIn sold for a little bit more money. I left. It’s interesting. I’m having a monster reunion tonight. But I left very quietly, having signed a bunch of paper that said I wouldn’t make a big deal out of leaving the Monster Worldwide. At that point, we should talk about that. Monster Worldwide put a small investment into my new idea, which is called Eons, and I effectively walked away from our industry to answer the question for 20 years. So we can come back around to why I came back in. But let me just tell one little side story.
09:25
Jeff Taylor
There’s a lot of acquisitions happening right now that are very high profile. And through time for our business, there have been times when a lot of acquisitions happened. But I can’t think of another example where the TMP bought Monster. And then through about eight or nine years of good leadership in the marketplace, TMP acquiesced and Monster Worldwide became the parent. And I think it’s one of the. People talk about paradox and smart recruiters and what that will do to these companies. And I think it’s really interesting to see. Will these companies that are on the leading edge of AI, will they be able to shape the parent companies that have bought them? I think that’s an open question, right?
10:16
Matt Alder
Yeah, I think that’s a really interesting. Really interesting point. There’s definitely some. Definitely some parallels. There aren’t that.
10:20
Jeff Taylor
Yeah. So you asked why now? I think there are only a few moments in our lives where there’s, I would say, dynamic disruption. And I think this is one of those moments. And were talking earlier at this conference about whether you’re an AI optimist or whether you’re a pessimist or whether you’re a realist. And I’m a AI optimist. I can see some of the challenges ahead of us. And I think it’s gonna be a rocky road, but I think it’s gonna change everything. And so I’m not only preparing for that for myself, but I’m also building a business with those ideas as the anchors.
11:03
Matt Alder
And we’ll come on to talk about the. We’ll definitely come on to talk about the new business soon.
11:06
Matt Alder
Just before.
11:07
Matt Alder
I’m just kind of really interested because it’s such a snapshot being away for 20 years and then kind of dropping back into it, as it were. I checked back and we connected last September. So over a year ago now, because you’d be listening to the podcast, you can kind of got in touch. What kind of shocked you when you came back in terms of what had changed or what hadn’t changed, you know, in terms of the industry that you sort of left a couple of decades before.
11:29
Jeff Taylor
So one of the things that I noticed right away is I didn’t know what Programmatic was. Programmatic really started in like 2012, 13, 14. And it’s funny that Chris Foreman was retiring from the business as I was coming back in to start Boom Band, and an entire segment of the marketplace and spend and efficiency had been invented and was fully in bloom and was starting to be second curve. And so that was the first thing. I think there were a handful of applicant tracking systems when I stepped out of the business. 200 Applicant Tracking Systems now. And so I guess what I would say is I was amazed at how much infrastructure had been built to handle the volume increases from help wanted local applicants.
12:26
Jeff Taylor
The advent of the H1B program, I don’t know if it’s called something different here, had allowed US companies to be able to hire outside. There’s some recent rules that have changed or added to that, but the concepts of real change in the industry were both profound. And I did an audit of the top 10 competitors that I felt were the competitors of Monster. They were still using basically my buyer, seller, patent and resumes behind a paywall after those patents are 30 years old. And so one of the things I was disappointed about and then ultimately really exhilarated by was the fact that the business still had a lot of the same habit and the same motion that it had when I left.
13:20
Matt Alder
And I think one of the, you know, one of the things that you’ve kind of flagged up a lot is that there are aspects of recruitment that haven’t changed in hundreds of years. Still. What, what do you kind of see as the biggest problem now? What is it that we have to address and fix to keep up with the technology, but also the changes in the way that people think about work?
13:41
Jeff Taylor
It’s a great question. I’m sorry, there’s a little bit of repeat of last night. We had an executive session. We talked about some of this. But if you look at the primary tools. Let’s take the resume. The resume has been the same since around 1900. I have a resume from 1914. I was talking about it last night. If you look at an automobile in 1914, you look at a telephone in 1914 and you compare them today, they are unrecognizable. You can very clearly recognize a resume from 1914. It has an objective, it has a current education and supporting education. It has your current employment, your previous employment and some hobbies and interests. I’ve joked about this a lot, but the resume I have, the person enjoyed fox hunting as an interest.
14:34
Jeff Taylor
And first of all it’s fascinating, but you probably wouldn’t put that on your resume today. And the second thing was that he was happily married. And it’s like, oh, good on you. But I’m not sure that you’d put that on a resume or CV today. So the resume is now, from my perspective, a pile of keywords and performance statements almost unrecognizable to the person that it’s about. And one of the things that I’ve laughed about is someone Being asked in an interview, can you just walk me through your resume? And it’s like a heart attack because you have no idea what your resume says. Two resume writers have written it, AI has run it through three times, and it is, I think, a document that has run its course. A job posting is a job announcement.
15:22
Jeff Taylor
Job announcements been around for 350 years since anvil put a posting on the side of a tree, you know, outside of his studio. And I think we’ve seen job postings evolve. But really the limitation of a job posting is still acting like a job posting from the newspaper. It has pretty basic information. It’s meant to be edited. It’s interesting. Resume means summary, it’s French. And job posting means summary, it’s English. But the idea of these two documents is they really fail with AI. I just heard someone at Wreckfest talking about make the job descriptions really skinny. Everybody knows what they do. Just get it out there as announcement.
16:07
Jeff Taylor
And my view is that you may want to make a concise posting out there, but you want to bring a dump truck of information in the back end because all of the components of the job requirements all become vectors or embeddings in the back of an AI search that will help you make a better match. And so I’m a little bit in conflict maybe with where I think the market is right now. The job posting is failing. I have a theory, and it’s one of thesis for my new company is that I think outbound is going to become outsourcing. Direct recruiting is going to become much more active than inbound job posting recruiting.
16:51
Jeff Taylor
The idea of making announcement and having 1,000 people queue in line to come into your company for the job, I think is, if it hasn’t melted down completely right now in the next, let’s say six months, it’s just getting worse and worse. And the thing that people underestimate is the reputation of the companies are at risk as more and more people apply for the jobs and don’t hear anything or hear very little. Just a little side note there. I talked to a woman, had applied for 920 jobs, 325 of them. She got rejected outright within 90 seconds. And so that has its own set of issues. The other 600 or so, she had gotten a response that said, we’ll get back to you for about 300. And they never did. And then about 300 of them basically never responded at all.
17:45
Jeff Taylor
17 responded, got interviews. Half of them were robots, half of them were, you know, digital Interview and got two volunteer offers and one full time job offer and took the job. And so that’s a 15 month journey for a woman that I know that I would have hired if I had the ability to do it and how motivated she was. So failure in both those areas.
18:10
Matt Alder
So we’ve set out the problem, you’ve talked about what you think is failing. I suppose the obvious question now is what’s the answer? What is it that you’re building with boomband?
18:21
Jeff Taylor
Okay, bear with me for two minutes. So I’ve had a dream ever since I was a recruiter. I started as a recruiter and I mapped all the Programmer analysts on 128 and 40, 495 in the Boston area. And once I knew all the programmers, I had the ability to move them around. And I did very well as a recruiter because I understood the whole market. So I’ve had this dream on the seeker side, I call them players, to map all the players in the United states. So there’s 177 million, there’s about 90 million knowledge workers. And so what I’ve done is I’ve done deep partnerships with about 10 big data providers and some smaller partnerships with another six or seven. And what I’ve done is ingested 3 billion rows of people data on career, web, social, consumer and demographic information.
19:18
Jeff Taylor
And what I’ve done is I’ve built a layer cake where I put all those databases on top of each other and then I’ve looked and most of you have had a cell phone number for 10 years, 15 years, 20 years, and I can see it’s the same cell phone number in all the cells. So in that layer cake I can give a five out of five on that is your cell phone number. And I’ve done the same thing with every row. And then I built a derivative product which is the Boom band database. Maybe we can talk a little bit about LinkedIn as it relates to that, but this is not LinkedIn data. So I’ve taken every source that I can find of publicly available information and I built what I call a North Star where I basically create in that derivative product.
20:02
Jeff Taylor
For Stephen, I would actually build a derivative product that’s all of your information in a graphical cool interface. It’s neat. And then what I’ve done is scored you as you so hard skills, soft skills. And so if you’ve, let’s say that you’re a full stack and you have Python for the last four jobs and you have 9,000 hours of Python, I can figure that out in the system. I’m scoring you effectively against yourself and it’s transparent. And then I would do soft skills the same way and leadership or creativity things that I can pull. And then I would do time, enroll time at company, your education, the industry that you work in. And then I would have your summary, I would have your description of your current role, et cetera.
20:49
Jeff Taylor
I suck all that in and I score that based on what I can learn about you. And then what I’ve done is I’ve. I’m doing that for 177 million people starting in New England with 17 million what I call players in New England. And then I’ll pretty quickly expand to the whole United States. And then on the job side for corporations, there’s 16 million companies that have over eight employees. I’ve ingested all the information about the companies. And so what I’m doing is I’m building a corporate dossier, which is like a career landing page on the company side and an individual dossier on the player side. And then what I’m doing is ingesting all that data into a metric space, creating embeddings for all of the data on both sides, and then using a semantic.
21:41
Jeff Taylor
It’s a combination of machine learning and a large language model to create neighborhoods. So all marketing people start to go to this area. All full stack start to go to that area. And then I’m using Gemini, Google Stack and Supabase as my basis for then doing a combination of unsupervised learning and supervised learning. And I have 11 people right now scoring resumes to help me have some human contribution to that process. And then what I’ve done is I built an arena, and that arena is visual and you can put yourself in the center. And so that’s a big part of what I want to do, is introduce the idea of a new business that’s for all the players in the United States. Put yourself in the center, and the jobs visually that you match come right to the center where you are.
22:32
Jeff Taylor
And then as a scout, as a recruiter, you put your job at the center, and all the people that match visually come to the center. And then you have a whole bunch of controls. So if I want hybrid versus remote, I can see the marketplace changes. If I say I’ve got a unicorn skill as a scout, wonder if I back off that unicorn skill, it actually changes the market and changes the matches. About this point in my presentations with recruiters, with companies, they start shaking and they’re like, I want to use this right now. And so that’s been an exciting part of doing something that’s very different. What do you think of this idea? I’ll start with you, Matt.
23:16
Matt Alder
It’s certainly interesting. I think you are obviously playing to all of the strengths that AI brings doing things that would be impossible for that before that happened. I suppose there’s two things I’d ask about it. I think the first one is a kind of little sub question just because of where we’re sitting. And I know probably everyone in the room is thinking about this, which is about, you know, data regulation in the eu, you know, outside of the US where some of those things might not be possible. So that’s the first question. And the second question would be, I know that you’re, you talk to a lot of job seekers, you know, just in terms of, you know, what do the job seekers think about this way of, you know, this way of working.
23:55
Jeff Taylor
Yeah. So around regulation, one of the things we’re doing is we’re operating a marketplace that sits outside of the stack. And this is a marketing platform. And the way we’re marketing it to players is that this is a marketing platform for you and to. The other thing we’re doing is I think a resume is a mostly historical track record. And somebody said to me that a job, a resume is a pile of things you never want to do again. And so a big part of our building of our dossier is to get you to come in, claim your record, and then bring your passions and interests and side hustles and all of your extras that are your life work in.
24:44
Jeff Taylor
And that includes being a stay at home mom or dad, that includes being a caregiver, things that are classically where inside LinkedIn you’d be on a career break. And in fact that’s sort of what everybody thinks of in those times. I think those are some of the biggest learning times in our life work. And so what I’ve done is you have a pick list of attributes for every one of your passions and interests. So if you’re a marathon runner, like my COO is, he’s run 60 marathons and he’s run 20 triathlons. Imagine how much he has learned in his work life and also in his life work. And so I want to find that balance and then create a picture of what somebody’s like, where it merges those things together around the data. So it’s contact information is hidden.
25:34
Jeff Taylor
I have a message system that is how you communicate on the platform. So you don’t have anybody’s contact information. You do have their full name. And so in the United States it’s an opt in scenario but I can create a search and then I can use effectively jobs as the engine for going out and saying this company I’m sending on behalf of this company who’s interested in your background. Would you like to engage and come in and claim your dossier? And so that’s a big part of our strategy. But we also have some additional strategies we’re already testing on TikTok and Meta to do outreach to just go after the pain points because there are some huge pain points. It’s counterintuitive but I think this timing right now is the perfect time to launch a new career, our program opportunity.
26:26
Jeff Taylor
So you know, so I think that’s the first thing GDPR I think is going to my track record in the United States. It’s funny, I did this with Monster too. There were some things that with the way Monster set up that weren’t ideal for Europe. We made some adjustments for Europe when we came over and it worked. And I’ll make those same adjustments and there’ll be may be more opt in, there may be more and different sorts of outreach and what we can share in the United States. There’s California rules, there’s New York City rules. There are already some AI overlays. I have to make sure that I follow those and we will follow those. The other thing is our business is completely transparent.
27:12
Jeff Taylor
You can see everything and it’s the first thing that I know of where all the jobs are available for free and all the people are there and you can search them. So the big difference is even using ChatGPT to go look for full stacks. You don’t have any idea how far into the system it’s looking for full stacks until it gives you some back and you get excited about it. But in our system it actually will look at the best performing full stacks in the country. Or with your limitation, if your filters are Boston, five years of Python, two years of Rust and I want somebody that’s been a manager of at least three people. Those are your filters.
27:55
Jeff Taylor
We will match against in the metric space against embeddings that match those and you’ll be able to see where the matches happen transparent on both sides.
28:04
Matt Alder
And I wanted to just zoom out a bit about AI and what it’s doing to the industry because it kind of did strike me when you were talking that one of the things that always slows innovation down is adoption amongst employers. And the recruitment process and these things that are kind of embedded. But I really do think that, you know, AI is just an incredibly disruptive revolution that hasn’t started yet, rather than a kind of incremental change for what we do as an industry. Can you just speak to that for a second? I mean, what do you think is going to happen to the industry as we know it when AI kind of fully kicks in?
28:40
Jeff Taylor
All right. I think Hung Li did a good job of this morning, basically saying, if I could predict the future, I’d probably be in a different seat. And I think I have some thoughts and I have a pretty strong opinion, so I’ll share some stuff out there. Last fall, the saying AI isn’t going to take your job, but someone using AI will take your job. Right. And I don’t even know who that Rob was there last night. Thank you for at least showing me that you’re listening. Right. It’s so beautiful. But I think last fall that was like, oh, okay, so I’ll just learn AI. It’ll be fine. And then McKinsey came out with a report that basically said, we’ll be 30% more productive by 2030 using AI.
29:31
Jeff Taylor
And I was like, okay, that’s good because we’ll get to do the things we like to do. And that was the answer that everyone was saying, you’ll get to do more human things and we’ll be more productive. I don’t think that’s the way it’s going to work. In fact, we’re already seeing it happening live, is that I think if AI is going to make us 30% more productive, I think the reality is that we’re going to have 30% less people doing the job. And I think the people then doing the job are going to start out with in the skill based areas, going to be very exciting because you’re going to lean into those skill based areas.
30:07
Jeff Taylor
But the reality is two, three years from now, as AI is able to eat more of the tasks, I think it is coming for all of our jobs. And our fight is going to be to do things that AI isn’t good at. And I think that we have to stop being so naive and you don’t have to do anything. I think that’s the key here. But my feeling is that we cannot be naive about this. So my simple coaching is make a pie chart of everything you do in your job. Give your own rating of whether AI could do it or not do it. And then as much of that pie chart is something that could be done by AI is how much more. More you need to learn about the things that humans do.
30:52
Jeff Taylor
And so I think that’s a great kind of challenge. I was saying your typical upskilling for an average person is one hour a month. And that’s. You read an article, you’re like, oh, that was a really interesting article. I learned a lot. That’s my upskilling for the month, right? I’m saying five to seven hours a week for everybody right now. Whether you’re using multiple LLMs to do the play that you’re doing right now or whether you’re. I have not done this, but if you try lovable and build your own agent. We were talking about this idea of starting to kind of build and explore these things. All of this sort of learning, I think, is going to be very important. And then I look at the bigger picture.
31:37
Jeff Taylor
I think I was talking to, I think about 70 Tas on a call, and they were like, I feel so bad. Not me. They were saying, feel so bad for customer service reps, for photographers, for creatives. And I basically said to the group, I said, who is in between the talent that wants the jobs and the hiring manager that’s going to hire them? Everyone said, okay, it’s the TA folks, right? And I’m saying, if you’re in between there’s going to be efficiency that’s created. And we’ve been talking in different meetings today about those efficiency. But I think that we’re all going to go through a very difficult journey over the next three to five years. And in that difficult journey, there’s going to be interesting companies that form. I think there’s going to be new jobs that form, which is going to be exciting.
32:29
Jeff Taylor
And I think that we’re also going to see that there’s going to be people that struggle that maybe aren’t as facile with the idea of learning something new. You know, it’s funny, last night I was the oldest person in the room. I think I might still be. And I was the only one, or actually I was the first one to basically say, we’re 40 minutes into this conversation and no one has said AI one time. And I think it’s one of the challenges of our industry that we have got to step up.
33:01
Matt Alder
It’s Professor Scott Galloway who came up with that quote. Someone who’s not going to replace. Yeah, absolutely. There we are. I learned that the other day.
33:10
Jeff Taylor
So can we play that quote for a minute? Because I think it’s still true. I just think the way it came out was like, okay, this is a relaxed quote where it says, you won’t lose your job, you’ll just learn AI. And I think that is true, but that means you actually have to do it. And that’s the point. I think it lulled people into some sort of calmness last fall, and I think it’s anything but.
33:35
Matt Alder
I hate that quote for that very reason, because I think people look at it go, oh, you know what, I’ll just use a bit of chat, gcp. And my job is, you know, my job is safe because I can’t be replaced, and all this sort of stuff. And I think that. I don’t think we even know what I can do in the recruitment process yet. And also what candidates prefer to deal with humans, what they don’t, all that. All that sort of stuff.
33:53
Jeff Taylor
Can I. Can I put a fact in? So, my developers, I have three. Three full stacks. And I asked them about two months ago, and I said, tell me about AI use and are you using. I call them coding buddies and they’re editors, I think is the category. But I think the reality is they’re actually writing code. And the feedback was, yeah, it was kind of like, yeah, I don’t know. Yeah, we’re using them, right? And so about three weeks ago, I asked the question a different way and said, I want you to use these and I will encourage you to use them as much as possible. How much are you using them? And so this is Cursor or Windsurf or whatever your favorite is. My team’s favorite is something called Warp. One of my full stacks, 95%.
34:47
Jeff Taylor
One of my other full stacks, 99% usage. So 99% of their code is being written by something that two years ago it was creating zero code. And so if you just think about the impact of that in terms of the profound productivity of my team and that I may not have to hire as many full stacks because of that and how proud I am of my team that they’re actually fully embracing it. I think it’s extremely exciting, but. But almost jarring in the same breath, if you think about it.
35:27
Matt Alder
I’ve got one final question for you before we kind of give people the chance to ask any questions they might have, and we could talk about the AI thing and the productivity. I could talk about this for hours, but we don’t, unfortunately, don’t have hours, which is. Which is. Which is annoying. I want to ask you about trust in the. In the recruitment process, because one of the things that Is a really sort of clear memory for me when 1. So it was kind of in that sort of growth period. And I used to work for TMP Worldwide, so I was quite close to. It was the kind of the brand that you built, the super bowl ad with all the kids, when I want to grow up, and all that sort of stuff.
35:59
Matt Alder
And there was a real sense that it was a cultural brand. There was a kind of emotional connection that the kind of people had to finding a job. It kind of really played, you know, really played on that. We don’t really have that anymore around recruiting people. People just have complaints about it. I don’t to see people going out to the market and trying to rebuild that candidate trust. And what happens is that with things like AI interviews where, you know, you look at the data and actually candidates are loving them, but the narrative that goes out there is that candidates hate them. It’s computers. It’s dehumanizing things. How do we get that trust and that kind of emotional connection back around finding a job?
36:38
Jeff Taylor
So this is sort of sensitive, I guess, but I think our industry is sad and not every bit of it, but I think there’s a lot of sadness, and I think it’s just broken. It’s not working. And I’ve asked in big groups for the last six months, are we better off than were 30 years ago? And generally, and almost, let’s say universally, it’s like, no, it’s not better. Right? And sort of shame on us. I blame me for part of it because I decided not to change the resume. When I started Monster, I decided not to change the job posting because I said, this is going to be so disorienting to distribute in this new way that I wanted people to have this recognition. I just had no idea that 30 years later it would still kind of be the same thing.
37:27
Jeff Taylor
I asked last night, who owns the job posting? Who owns the resume? It was a difficult question, right? Because some people said, well, the job seeker owns it, but they don’t own the motion. They own their little piece of it. And I think one of the things I’m excited about, first of all, I love this business. I mean, you’re going to have a hard time finding somebody that loves this business more than I do. And sometimes passion can be confused with ego. And I hope. I hope that I can lean into the side of passion, because that’s me in a nutshell. And the other thing is this is all about people. And the thing I did well at Monster, I think, is to treat people like gold. That is basic expression. Treat your people like gold, they’ll treat your customers like gold.
38:19
Jeff Taylor
That was it. And we worked hard and played hard. And I think a lot of people think that Monster to date was their favorite company to work at, or at least one of them. And I’d like your feedback on that. That’s fine. But I think we have to reinvent ourselves. And what I’m trying to do is turn the sweatshirt inside out and just say that there’s no way that we’re going to keep up with the pace of the Internet. ChatGPT just went over a billion weekly users. We didn’t even have a daily user stat in the millions and millions until tell the last two years. Everything is moving so much faster than we are. And it’s scary as hell when you’re building a business because it’s like the goalpost keeps moving.
39:06
Jeff Taylor
But if you’re not already moving toward the goalpost, it is going to be so far from your sights. And so that’s been a big, I guess a spirit call for me to the industry is let’s go.
39:19
Matt Alder
I think related to that. Just so we don’t finish on the industry. As sad as the final note, what is the vision? Where do you think recruiting, job search, all that stuff could be in a few years time? What is. What does amazing look like?
39:32
Jeff Taylor
It’s going to feel like it’s an ad for my product. So I want to try to like raise it up a level, but I don’t. I think job postings are going to go away and everyone’s going to say no. Job postings been around for 350 years, like, come on. But I think it’s going to change. I think I have this idea of a signal. And you’ll put a signal out into marketplaces, not just the marketplace I’m building, but you’re going to signal out to people where you’re not telling the whole world you have an opening. You will signal to very targeted groups and AI will be able to help you with that. I think the idea of a chatbot being agentic AI is sort of people’s confusion right now.
40:14
Jeff Taylor
But when it becomes an agentic motion that I’m incredibly excited about is when you’re talking and it’s saying, do you want to build this? And then you build this and you say, do you want to connect this? And then it connects itself and goes and does a bunch of other activities. And I see the market is going to move faster than us and that agentic layer is going to get more and more exciting. You know, I like the expression the Internet’s the worst it’s ever going to be today. I do believe that. And a lot of people spend a lot of their time saying, you see, that’s no good. That hallucination right there, that’s the thing. That lawsuit that’s happening over there, that’s the thing.
40:59
Jeff Taylor
All of that kind of negative side, you know, the glass is half empty, I think is calories that we should be spending trying to figure out how to reinvent our business. And I’m not trying to predict more than right out in front of us, but my main thing is it’s going to change. And anybody that says it’s not going to change and it’s going to be fine. That’s the naivete that I’m trying to break people free from.
41:24
Matt Alder
Jeff, thank you very much for talking to me. I’m going to turn the recording off so you can ask questions without the fear of being broadcasted. Several thousand people.
41:32
Jeff Taylor
Can I just turn it on? I have to say I am very appreciative of the work you do. I’ve had some fun with you. Just, you know, kind of coaching. You were coaching me and I’m coaching you. And I. I couldn’t do what I’ve done if last summer weren’t having those conversations. And I listened to at least 50 of your podcasts. And so thank you for doing what you do.
41:50
Matt Alder
Thank you.
41:51
Matt Alder
And I’m glad I didn’t turn recording off.
41:55
Matt Alder
My thanks to Jeff and the audience and organizers of TA Tech. You can follow this podcast on Apple Podcasts, on Spotify, or wherever you listen to your podcasts. You can search all the past episodes@recruitingfuture.com on that site. You can also subscribe to our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time and I hope you’ll join me.
