What is the future of recruiting talent, specifically for remote-first companies? This is a topic Alexander Torrenegra has been researching and learning first-hand for over 18 years, and how it has eventually translated to Torre's powerful first question, "if recruiting were to be reinvented from scratch today, what would it be like?"
Support Us! We'll be posting new episodes every Tuesday AM (EST), so please subscribe for updates or follow us on social media.
Please leave a rating and review on Apple Podcast & Soundcloud! You can also find us on Spotify.
Tweet us @Remoter Project.
Follow us on Instagram @RemoterProject.
Give us a like on Facebook @RemoterProject.
Check out some other creations:
The Founding and Growing Remotely online video course with informative details about going remote-first.
The Remoter Guide, created to help you hire and onboard remote talent, efficiently and effectively. Remoter Salaries, an on-going research project noting benchmarks for remote workers' average, median, minimum & maximum salary ranges.
If you have any additional questions, feel free to e-mail j@remoter.com.
—————-
A big thank you to our post-production wizard, Vanesa Monroy.
[A moderately paced, trip hop song that is best described as chill and cruising. Synth and techno drums are the primary instruments in this track. This is our podcast background music, it starts playing at the very beginning]
[00:00:00] Andres: [00:00:00] Hi, I'm Andrés
[00:00:04] Josephine: [00:00:04] and I'm Josephine. Welcome to the Remoter Podcast.
[00:00:07] Andres: [00:00:07] Follow us on season one of this journey as we cover anything and everything you need to know, in order to successfully build and scale a remote-first team. Someone who's been working remotely for over a decade, our CEO, Alexander Torrenegra shares his personal experiences, lessons learned, and advice for those of you or curious and interested in exploring the future of work.
[00:00:33] Josephine: [00:00:33] This podcast is brought to you by Torre, the end to end recruitment solution for remoters. Get our free AI powered sourcing and processing tools, or let Torre recruit on your behalf at Torre.co. That's T O R R E dot C O.
[Music stops playing]
[00:00:51] For listeners out there, uh, tuning in today, Torre CEO Alex has other companies. He [00:01:00] co-founded Voice123 and Bunny Studios and those are pretty much market... Would you say they're like, marketplaces for people to find voice actors, at least for Voice123, and for Bunny Studios, it's for people to find copywriters, voice actors, and the whole kind of like creative shindig, everything you can get in one place.
[00:01:21] Andres: [00:01:21] Yeah. Creative, mission critical and creative outsourcing. It's like Amazon, but for creative.
[00:01:26] Josephine: [00:01:26] For creative. Yeah. Yeah.
[00:01:27] In my previous job, in like the studio, I was working in, I was working as a post production producer and from a business mindset, uh, after I learned about Voice123 and Bunny Studios... it's a very smart business move. And I kind of wondered why people didn't go that way, uh, within agencies. Cause that's like such a, um, cheaper alternative and faster way to get things done. However, I remember that, you know, in more traditional agencies and bigger [00:02:00] companies, that's why you have a set creative team there. And if you outsource all the creative work, then what is the creative team really doing? And I then remembered my past experiences where the creatives obviously want more control of what um, is being produced. And for example, if we were ever to go to a voice marketplace, like Voice123, to get, um, to get voice actors, they wouldn't be able to direct or have the voice actors sound the way they want them to sound in like a live session where they can actually see the voice talent.
[00:02:39] So that's something that's, I think that's why a lot of places still kind of go, you know, the traditional route where we get people in or it's just happening synchronously.
[00:02:51] Andres: [00:02:51] Yeah. You know, the, the future is all about optimizing for value. And there is no value in having someone have to go to a recording [00:03:00] studio, having to negotiate with a paymaster and with a casting director and with an agent, all these different professionals.
[00:03:08] Um, there is no value in having someone having to commute to an office for three hours like you did. There is no value on that. So, um, humanity is constantly optimizing for value. And, um, you, you have examples in, for example, self-driving cars. Self driving cars are going to be way safer and way more optimal.
[00:03:29] I don't know if you've seen it, that there are some, um, renders, um, and concept of how autonomous cars will be able to cross intersections in a faster and more efficient way than human beings with no traffic lights. So, because what they will do is they will connect to other cars and they will figure out the position if you want each one and decelerate or accelerate, um, giving whatever the best of the optimal way of crossing the, the, the cross, the crossroad.
[00:03:58] It's a, yeah, [00:04:00] it will be. And, and you see these in everything. Like for example, when we went from trains to planes, um, what happened is we stopped having. Um, whatever you call the train pilots, I don't know how you call them. Train conductor. Okay. You will stop having so many conductors. And we started having a lot of pilots because that was the optimal way of transporting human beings from point A to point B.
[00:04:21] So with that in mind, it's a matter of where the future of work is going to be and where the most value is going to be created, and I believe, and we believe that the most value in the future will be created by human beings working remotely. Of course, some physical jobs are still needed. Someone needs to pave the roads, someone needs to maintain airplanes, someone needs to work in banks... perhaps? I'd, although that one, I think we're not going to have any more. Banks, physical banks and you, but that's a different question anyways. Um, but the majority of value is going to be transacted through human beings working remotely, and that's where we're heading.
[00:05:01] [00:05:00] Erik: [00:05:01] So, Alex, many times recruiting is just a chore. And you've been researching this for the last three years. What is the future of recruiting talent, specifically for remote-first companies?
[00:05:12] Alex: [00:05:12] Well, I've been actually researching this or learning about the topic or over 18 years, right? I mean, when we created Voice123... Voice123 is a system that automate and to a large degree, revolutionize the way in which people find voice actors. Now granted voice actors are not full time and remote workers, which is what this podcast is primarily focused on. But still, it is an industry that used to be location based that, uh, thanks to the work with the, uh, to a significant degree, uh, has evolving to being an online industry, where people work from home and they connect with clients all over the earth.
[00:05:55] That was the first exposure, alongside the fact that [00:06:00] that we built it with a remote team. That led me to start thinking about the topic more and more, not only limited to the voiceover industry. Eventually, many years later, we created Bunny Inc when we took it to the next level. So not only remote, but how to better recruit people for certain kinds of creative work. What we have accomplished in there has significantly led me to believe in why the ideas, so I should probably provide an example. Imagine that you need a voice actor for something, or a writer or a translator or a video editor for a project. Most people today, they would ask their colleagues for someone that you know, or they would go to an online website.
[00:06:46] Post the project and wait for offers to arrive. Usually you have to wait several hours to one day for the, for the offers to arrive. You start interacting with some of them eventually, potentially within two days or so, you pick [00:07:00] the vendor that you prefer and you start working with that person right. Now, let's do some, some little scifi here. Um, now imagine that instead. Of you getting 10 different offers or 20 different offersm you got only one offer because some artificial intelligence machine identified that that's the best one and that there is no need for you to review the other ones because that's going to be the best one and it's going to be one you're going to be the happiest with.
[00:07:30] Erik: [00:07:30] Okay, so it may sounds simpler.
[00:07:33] Alex: [00:07:33] It's simpler. Yeah. If it happened that way.
[00:07:35] Andres: [00:07:35] For you as the person, trying to find the other person
[00:07:38] Alex: [00:07:38] For both. Right? Because on the other side, there were 19 people that didn't have to submit an offer that didn't get selected. So for everyone, everyone will be cooler. Now imagine that it didn't take 24 hours for you to get that offer and 48 hours to close the deal.
[00:07:53] But that you could do all of that in a matter of, you know, an hour or 15 minutes even. Okay, [00:08:00] now let's do even more scifi and now imagine that, instead of you getting the offer from that person, you actually get the work done and delivered within those 15 minutes.
[00:08:11] Erik: [00:08:11] Wow.
[00:08:12] Alex: [00:08:12] And so do you don't even have to negotiate, like you already got it.
[00:08:17] And it comes with a big button that says, if you like it, it's yours. If you don't like it, you get the money back for what you paid here.
[00:08:25] Erik: [00:08:25] Wow. So there's no risk. Fabulous.
[00:08:27] Alex: [00:08:27] And no risk for both sides, right? No risk for the person buying it. But also no risk for the person creating the work where if the buyer ends up rejecting the work, the creator of the work still gets paid for that.
[00:08:40] Well, that sounds like scifi, but that's what we do with Bunny Studio every single day, thousands of times per day. So we have many clients today that either manually or using the API, our API, they come to Bunny Studio. They request work, whether they need a voiceover recorded, something translated, something [00:09:00] transcribed, et cetera, et cetera, and within 15 minutes to an hour, it depends on how much time they have- we actually accommodate to many different types of deadlines. We deliver the work for them, and that happens. If they don't like it, they get their money back and they get a discount for the next project, and the success ratio is over 96, 97% on the first try, and it goes up to 99.8% on the second try ,in case the person didn't like it the first time.
[00:09:28] And the reason we do that, or we can do that is because we use a lot of algorithms and artificial intelligence to predict who's going to be the best creator for that project. And it includes a lot of different variables and a lot of different factors. Algorithms optimize for quality, time and cost. All of them, at the same time, and it makes life much better for everyone involved in the project. I mean, clients, they get surprised because in many instances they get stuff that they didn't even imagine they could get. [00:10:00] It's better than what they were thinking of.
[00:10:02] Erik: [00:10:02] Okay.
[00:10:02] Alex: [00:10:02] And for the creators, well, they can focus on their craft. They don't have to worry about, uh, submitting offers to different projects. Or they don't have to worry about dealing with clients that don't pay. They can really focus on what they're really good at. The record that we have in, in Bunny, in Bunny Studio was actually a demo that we did for NPR back in the day.
[00:10:22] Andres: [00:10:22] What's NPR?
[00:10:23] Alex: [00:10:23] National Public Radio, which is the large news organization in the U.S., one of my favorite ones. We did a live demo where we were pushing our algorithms to the limit. From the time the project was submitted, to the time it went through the selection of a person somewhere on earth, the recording of the audio, the performance of quality control on the audio and the delivery of the audio to the client, NPR in this case, was two minutes and thirty-eight seconds. That's how quick it was. Now, we don't do it that quickly, usually, not because we can't, but because clients usually have more time to do it. The success of those companies and [00:11:00] how they've grown and the traction they had, and now the hundreds of remote employees that we had with them, allowed me to think even bigger.
[00:11:08] One of the most important insights is that, in the not so far future, the vast majority of the allocation of talent is going to be done by AI. It's going to be done by machine learning. So the idea of sorting through hundreds of job openings for you to find one that you may like, or sorting through hundreds of the resumes of applicants, for many of which probably are not relevant for what they applied.
[00:11:33] But even the concept of recruiters as we know it today, are going to be a thing of the past. I get started, Torre, to create that future. Or at least to create the network and the platform to power that, that future. So we started with a very, uh, first principles kind of question. And that is, "if recruiting were to be reinvented from scratch today, what would it be like?"
[00:11:58] And we set ourselves [00:12:00] to, to do it. Um, there are many ways in which is different. In Torre, we don't use resumes. Instead of resumes, we use, uh, structure, biographies of the individual, which include a lot of data, some of the data provided by the person. Most of the data provided by others about that person. It's not a summary, which is what the resume is of that person's life. It's as extended as we can have it because most of the audience of that biography is actually machine learning algorithms.
[00:12:28] Andres: [00:12:28] So they can, they don't have a limit in terms of how much they can read.
[00:12:31] Alex: [00:12:31] Exactly. A recruiter and probably read just a couple of paragraphs in, in 30 seconds or so, which is the average amount of time a recruiting better invests on that, on that resume, machine learning computers, they can read your entire biography in microseconds and then make decisions based on that. That's one of the things, uh, another element for example is that we are not matching candidates with opportunities alone. We are matching candidates with opportunities with the members of the team that [00:13:00] the candidate would end up working with if selected for that opportunity, whether it's full time or freelancers on that regard. And we not only compare the skills of all these groups of people, we analyze the skillsets, the aspirations, the areas where they want to develop professionally, their personality traits, their values, and many other things.
[00:13:22] So we are bringing down to a math what people consider cultural fit. Which, if you were to ask 20 people what is cultural fit, you're going to get 20 definitions, but we are actually taking the time. We took the time of identify what are the most important factors in that regard. Actually, what are all of the factors that determine what cultural fit is, weighting them, and then identifying ways in which we can capture that information and make decisions, or at least, uh, significantly automate the process for people when they're doing that as recruiting. And many other things, referrals are very important when recruiting, yet today, referrals are [00:14:00] manual. I mean like, "hey Joe, here is a job opening we have, can you think of anyone for these roles?" Right? When most people already know the people they might enjoy working with or people they might refer. So, we created the concept of signal where you can build a list of signallers of people that might consider working with you. Signalees as well, people that you have signaled that you might work with them and you can share those leads with your friends, your colleagues, with your company, and using that fully automated process of referrals and, and many, many, many, um, other, other things.
[00:14:34] Andres: [00:14:34] So essentially you have a list of people that you know that you would recommend for any kind of job that the system considers that is relevant for that list. So, if I have someone that is, I don't know, I have three people who are really good at, I don't know, SEO. And you, Alex, were to ask me, hey Andrés, who do you know that is good at SEO.
[00:14:52] Then instead of you asking me, you make a posting and the system goes through my list and recommends you automatically those three people.
[00:15:00] [00:15:00] Alex: [00:15:00] Yeah. I mean, if we were already connected somehow and you had given me access to that, indeed. Like I don't have to ask you for that because you already have that information somewhere.
[00:15:08] Now, I wouldn't necessarily get those three people recommended, but the algorithm is going to take those signals that you had. That list that you had as one of the manufacturers to take into account when making a recommendation, because maybe there is a person that has been signaled by multiple people that happens to have a recommendations from people that I have recommended as well, that happens to be on the same time zone, but for example, it's outside of my salary range, what I can offer. So that people isn't going to get recommended because there is one filter which that person would be unfit, but there may be another person relatively similar. Maybe with not as mainly recommendations, but that happens to be within the salary that I'm willing to pay. That person gets recommended. So there are many, many, many factors that we are using to determine who might be good for what.
[00:15:53] Andres: [00:15:53] Sometimes companies, I've heard them say, well, if the candidate is so good and I, it's such a good fit, I will be willing to [00:16:00] move a little bit within my, within my budget.
[00:16:02] And reality is, the vast majority of job openings out there don't show salaries. Even though it's one of the most important factors for someone to consider working at a company, they don't show salaries precisely, so they can be, they can judge whether they would pay X or Y or Z based on the candidate and not based on the work that a candidate has to do.
[00:16:21] Alex: [00:16:21] And it's an unfortunate reality, especially in the U.S. There are some countries where that's more common than others. In the UK, for example, seeing the salary in the job openings is, is almost the default, but it's becoming more and more important and I think it's going to be the default way for recruiting to happen in the future.
[00:16:39] Whether you're sourcing people, whether you are like manually looking for candidates or whether you're making job openings or posting job openings, you're going to need that information upfront. When you go remote, it's very iffy to find job openings attracting thousands of candidates, unless it is some level of automation.
[00:16:56] We are going to find ourselves with job boards, with a job [00:17:00] opening that is attractive, may attract several hundred thousand applicants. I mean, this happenned in Voice123. Back in the day, when we were getting started in a very specific niche, where auditions attracted over a thousand different applicants that actually took the time of recording an audition for the client and sending it.
[00:17:17] So we ended up eventually creating ranking algorithms that would show the best voice actors at the top and eventually flow control mechanisms that wouldn't open the doors to everyone to apply to the job, but only the ones that we predicted were going to be there, the best ones so that we will save everyone time.
[00:17:36] Some of that is in Torre as well. Just the fact that there is a job that you might like doesn't mean that you need to apply. We upfront, we show you how you are going to rank on that job opening so you don't waste your time, maybe applying for something that your chances of even getting being seen by the recruiter are going to be too low.
[00:17:53] On the other hand, we can also proactively tell you, "hey, here's a job opening, and we know you're not looking for a job, but you told [00:18:00] us to tell you every now and then about good job openings. Here's a job opening for you that you might love. Just check it out or just ignore the, ignore this.
[00:18:08] But if you apply, there is a very high likelihood that the recruiter is going to be looking at you.
[00:18:12] Erik: [00:18:12] I find that a lot of recruiters sometimes contact me because they have a job to sell. They don't work. They won't tell you what the salary is or how much do you need, what do you know? There it's, it's seems like it's a sales pitch and all that, and you're talking about kind of turning that into the online shopping bot that takes care of everything for you.
[00:18:31] Alex: [00:18:31] And more transparency. Like I'm in favor of of salary standards, for example. And there is a reason for that. And that is, if you were a recruiter, how many times per week are you negotiating salaries? Chances are that you do it multiple times. Now, if you're a candidate and employee, how many times per week are you doing the same?
[00:18:51] Zero, right? I mean, like you negotiate your salary every year or every three years or four years when you're changing companies. So candidates in [00:19:00] general are at a disadvantage in that, in that regard. And I think that being upfront in terms of how much you're willing to pay and upfront in terms of how much you're willing to to work for, uh, makes it easy and reduces discrimination of it all.
[00:19:14] Andres: [00:19:14] You launched the flow control mechanisms and the ranking algorithms at Voice123 and you had a lot of backlash.
[00:19:21] Alex: [00:19:21] I had a little backlash back in the day, but I also had many other people quite happy with that. The backlash came from people that were abusing the system, people that were applying to every single job that came out there.
[00:19:35] So the straw that broke the camel's back was an audition submitted by a voice actor. Actually, I recognized the voice actor in the Spanish speaking world for a project that was in English, looking for a female voice actress that spoke English. And his audition, I listened to it, he said, "hey, I know you're looking for a female English speaking voice actress, but if in the future you decide to localize your [00:20:00] content to Spanish, here I am."
[00:20:02] So it was pure spam because eight chances, and I noticed that he was doing it with many projects. If I look into that, I noticed that many other voice actors were doing something like that. So the result is that the many of the people that were getting the projects were don't necessarily, the best ones were the ones that were spamming the most, the system.
[00:20:25] Erik: [00:20:25] Right.
[00:20:25] Alex: [00:20:25] And that definitely happens today a lot when it comes to recruiting. Who gets the job, the one that can lie the best on the resume, the one that can submit the most applications to the most companies today, and it doesn't always happen, but for companies to avoid that from happening, they need to invest a significant amount of people going through all of the resumes, to the extent that many companies give up and they only search, they don't even publish their job openings.
[00:20:51] They only go look for talent manually. It's also an issue that shouldn't exist to begin with. So...
[00:20:58] Andres: [00:20:58] It's crazy however long it takes way [00:21:00] more time to source than to, just post an opening or...
[00:21:02] Alex: [00:21:02] A lot and you tap to an audience that is significantly smaller because you're only tapping the people that you can actually reach out to do that, end up opting to read your message, right?
[00:21:13] While ideally you broadcast your opportunity to as many people as possible that is relevant to the opportunity and relevance is what's not there today and what we are trying to build with Torre. By the way with Torre, we are not going only after remote work. The goal of Torre is to build the global network that enables everyone to find fulfilling professional opportunities easily.
[00:21:34] We are going after remote work because we see, A, a significant opportunity there, and B, we are quite passionate about remote work.
[00:21:42]Erik: [00:21:42] But to realize the advantages of remote work that diversity, the global talent, things like that, you do wind up, it's just like the internet in general. You wind up with spam and way too much information, so you're solving a problem that just out of necessity.
[00:21:57] Alex: [00:21:57] Yup. Necessity is the mother of [00:22:00] innovation. Another thing is that most recruiters, because of the limitations of their cognitive capacity, which makes sense, we are human beings. They prefer to hire people that have already experience on the role that they're hiring for.
[00:22:16] Erik: [00:22:16] Yes.
[00:22:17] Alex: [00:22:17] And as a consequence, you hear them saying, "I am hiring a senior software engineer."
[00:22:23] When in reality what they should say is, "I am looking for a person to fill the role of a senior software engineer." Because the best hires are not going to be the people that are moving horizontally from the same role to another company, because that means somehow that they got stuck where they were.
[00:22:42] The best hires are the people that are growing professionally into that role. So I potentially want to hire a mid level engineer that is growing professionally at a speed that allows me to predict, you know, the next step for this person is going to be senior software engineer. Recruiters, usually [00:23:00] I find they don't do that in part because it's very difficult for them to predict, to know, to take that risk.
[00:23:06] It's safer for them to bring a person that is already kind of a successful senior software engineer somewhere rather than to bring a person that they don't know whether that person might end up filling that role.
[00:23:18] Because it [00:23:19] Andres: [00:23:19] requires an analysis and that's an analysis that takes time. And if you have to do that with hundreds of resumes, you just can't.
[00:23:24] Alex: [00:23:24] But it's an analysis that includes many, many, many, many different variables because you have to analyze cultural fit. You need to analyze the delta of growth of the person. You need to do because migrating or graduating from being a mid level engineer to being a senior engineer is kind of a straight forward thing, but there are many other roles where there is not necessarily an obvious linear progression into that role.
[00:23:45] You might have developed a lot of different skills in different areas that might allow you to be really good somewhere else, but you don't even know it as a candidate. That's the kind of prediction that we are trying to, that we are trying out, that we are building into the system so that we expose [00:24:00] people to the best next thing they could do, even if they don't know that's the next thing they could be doing.
[00:24:07] Andres: [00:24:07] I've seen many people that I've asked many times, "hey, would you quit and come work with me?" And they will be like, no, I could offer them more money, or I could offer them a, a challenge that might sound more interesting, but they're committed to the, their missions in their companies and they're committed to the culture of their companies and they're committed to growing professionally within their projects.
[00:24:28] So the more, the more you can engage companies and employees that way, the more that you can engage people and talent from a perspective of cultural fit and sharing values, sharing missions. There was this Apple engineer that, he wanted to go to live in Colombia because his wife was Eissa from Medellín and he used to be a, an engineer at Apple earning a half the salary.
[00:24:48] And he took a significant, I think it was somewhere on the 70% cut in his salary. So, and then ended up working at a startup, I imagine, as a CTO, uh, just [00:25:00] so he, he could go live with his wife and build a family in Medellín. Yeah. So it's important for people not only, not only to be valid for the skills, but also, and it's important for companies who value people, not only for the skills, but also for their progression and their missions and their values and culture, etcetera.
[00:25:16] Alex: [00:25:16] Going back to your original question, and that is what I believe the future of recruiting is going to be and what I'm, what am I doing about it? Well, I, I do believe that the future of work is going to include a lot of automation. A lot of AI machine learning is going to end up replacing, uh, people, uh, at any of their jobs.
[00:25:36] But I do also believe that artificial intelligence can also help everyone find the best job they could be working at. And that way make work fulfilling for all, and that's what I'm working on.
[Podcast music background track - stinger]
[00:25:58] Josephine: [00:25:58] Wow, so listening to that [00:26:00] episode, I totally understand what you mean. Uh, when you were talking about, um. Optimizing work in the introduction and everything. Like, honestly, I am all for it. If I can do what I want to do in all these different places around the world, for example, like I want to produce TV shows and films and uh different media in different countries, and I don't have to worry too much about physical, like work visas and all that because I'm working remote for all these international projects. I am honestly down for that.
[00:26:31] Andres: [00:26:31] Well, Josephine, now's your turn to build it. And speaking of builders and CEOs, next week, we've had a very interesting episode coming up. I think you guys are going to love it.
[00:26:43] Alex: [00:26:43] So guys, the surprise is that I'm going to be interviewing you today. The same way that I interview people that are going to be joining my team. So ready to get started?
[00:26:52] Andres: [00:26:52] Let's go.
[00:26:53] Erik: [00:26:53] Born ready!
[00:26:54] Alex: [00:26:54] Okay, good.
[00:26:57] Andres: [00:26:57] Mine is, mine is very basic. I'll, I will [00:27:00] be.
[00:27:00] Alex: [00:27:00] I think I know.
[00:27:01] Andres: [00:27:01] What?
[00:27:02] Alex: [00:27:02] The Ironman guy.
[00:27:03] Andres: [00:27:03] Ironman, any day of the week.
[00:27:06] Alex: [00:27:06] I interviewed Andrés when he joined the company. And I asked some of those questions to him. I don't know.
[00:27:13] Andres: [00:27:13] Yeah, but you know, except...
[00:27:15] Alex: [00:27:15] Tony Spark.
[00:27:16] Andres: [00:27:16] Except... Stark. Tony Stark. Please get it right.
[00:27:22] Thank you so much for tuning. A few last words. If you enjoyed that episode, please...
[00:27:31] Josephine: [00:27:31] Follow us on social media @remoterproject and let us know what you think about the latest episode.
[00:27:36] Andres: [00:27:36] We'd love for you to join us as we continue building the Remoter library on our website, remoter.com that's R E M O T E R dot com.
[00:27:45] Josephine: [00:27:45] If you want even more resources, sign up for our free Founding and Growing Remotely online course. You can find that on our website or check the description for links. Don't forget to follow and subscribe to us on Spotify, Apple Podcasts, SoundCloud, [00:28:00] wherever you listen to your podcasts.
[00:28:01] Andres: [00:28:01] And by the way, we've got some exciting news. We're gearing up for season two this time. We're going to go further into interviewing remote work leaders all around the world, and we'd like to ask you, what are some questions or topics you'd like to hear covered next time? Who would you like to hear on the show, and let us know through Twitter, Facebook, Instagram, email. Um, you know, carrier pigeon, whatever it is you like, we're all ears.
[00:28:26] Josephine: [00:28:26] And remember, we're here to make work fulfilling. So what part will you play in shaping the future of work?
[Cue podcast background music track, same one used in the introduction]