Each week, we interview proven leaders from our network, to learn from their experiences, and share their Talent Attraction and Candidate Experience stories with you.

• Our mission is to promote the accomplishments of our guests
• Highlight the companies where they work and the services, and products that they offer
• Share success stories from their experiences and, most importantly
• Provide strategies for job seekers and advice to talent seeking to accelerate their careers.
  

Today’s guest is Taylor Radey, Founder Randall Pine.

I met today’s guest a little over 10 years ago, as a candidate that was referred to me by a mutual friend.  We reconnected over the last year and she has been an incredibly helpful advocate regarding everything AI. The foundation of her career started in the corporate environment focused on content marketing, before spending the bulk of her experience in consulting with Hubspot’s first ever agency partner. Over the last 8 years she has been helping marketing teams in small to mid sized companies, and more recently she has been focused on guiding AI Adoption for these businesses.

Taylor shared many great insights including:

• Her journey from a journalism major at Ohio University to becoming a guiding force in AI adoption for small to mid-sized businesses
• Her work on AI services at Randall Pine, including providing AI adoption strategies and real-world case studies
• Advice for emerging business professionals, the importance of AI literacy, and effective strategies for navigating the rapid advancements in AI technology

From Journalism to AI: Taylor Radey’s Journey

[00:00:05] Ron Laneve: Hello and welcome to episode 37 of the Bell Falls Search Focus on Talent Podcast. I’m your host Ron Laneve. Each week, we share the career stories of tech experts and marketing mavens, operational gurus, and sales leaders to illustrate how they have navigated the nonlinear career path.

[00:00:23] Ron Laneve: I met today’s guest a little over 10 years ago as a candidate that was referred to me by a mutual friend. We’ve reconnected over the last year and she’s been an incredibly helpful advocate regarding everything AI. The foundation of her career started in the corporate environment, focused on content marketing before spending the bulk of her experience in consulting with HubSpot’s first ever agency partner. At the time it was called PR 2020.

[00:00:50] Ron Laneve: Over the last 8 years, she’s been helping marketing teams and small to mid sized businesses and more recently she’s been focused on guiding AI adoption for those businesses as well.

[00:01:01] Ron Laneve: I’m thrilled to introduce, Taylor Radey, founder at Randall Pine. Taylor, thanks a lot for being here.

[00:01:08] Taylor Radey: Yeah, absolutely. Thanks for having me.

[00:01:10] Ron Laneve: You’re in Tokyo and it’s 6 a. m. one thank you for doing this so early in the day halfway across the world. And secondly you win the award for the furthest away individual I’ve ever done an interview with. Thank you for that.

[00:01:23] Taylor Radey: Absolutely. Yeah we’re global.

[00:01:26] Ron Laneve: Super excited. Like I said it’s been fun to re engage with you and get your guidance on AI. The common theme in your background has clearly been content marketing and heavy and professional services. As I focus on nonlinear paths it’s interesting. A lot of my guests have become entrepreneurs. I’m curious, can you walk us through how you got there? What decisions did you make and when were they intentional? Were they serendipitous? How did you get from point A to where you are today?

[00:01:55] Taylor Radey: Yeah, of course. I was actually a journalism major. I went to ohio university their scripts school of journalism and At the time they had different tracks So you would specialize in newspaper or magazine or broadcast or something like. They also actually had a public relations track. In addition to learning the bulk of the journalism curriculum, I had some extra classes that were focused on basically how PR professionals work with journalists and corporate communications.

[00:02:26] Taylor Radey: By the time I graduated, I was actually leaning more toward getting a job with a company in more of a corporate communications type of role. I ended up joining a steel manufacturing company in Cleveland as a marketing communications role. And so at the time it was a great fit because it was clearly very communications and writing focused.

[00:02:47] Taylor Radey: But even in just the couple of years that I was there, it really transformed from internal communications and copywriting into a full fledged content marketing and digital marketing type of role. That is because they hired a new CMO, our mutual friend, Steve Chiles. He is, a brilliant digital marketer, came in with a lot of ideas.

[00:03:10] Taylor Radey: Working with him and under his mentorship, I got a ton of experience in learning the tools and also just the strategy and tactics of running a digital marketing program.

[00:03:20] Taylor Radey: By the time I left there I actually followed Steve because he was joining an InsureTech startup. He was looking for someone to run content marketing. I was like maybe employee three or four and I was the only person actually I think with marketing in my title. It was a very content marketing, but also just anything marketing digital marketing I got to focus on and really build the program from the ground up there.

[00:03:45] Taylor Radey: After that I started to want to get agency experience, and I knew Paul Roetzer. He’s a Bobcat, so he used to come down to OU to the campus every spring for recruiting trips. He still goes there a few times a year. I had known him over the years. I had met some of the people on his team at PR 2020, and I was really impressed by them, so then I went and joined them.

[00:04:10] Taylor Radey: That was a great opportunity for me to not only get to work with different clients in different industries with different business models, different marketing and business goals. I also got to learn about client services, account management, consulting, agency management. That gave me a much broader business knowledge.

[00:04:33] Taylor Radey: Then in 2017, I started my own firm, Randall Pine. I was focused on being a digital marketing consulting firm. I have been adding more AI services since around. 2020 2021. Lots of stops along the way somewhat intentional, but certainly a lot of good fortune as well.

[00:04:53] Ron Laneve: What made you want to go join professional services? Given my experience, I think that was a great decision, but not everybody views that or sees that as an option. Why’d you choose that at that time?

[00:05:06] Taylor Radey: There were a few reasons. The first was that I wanted to learn about working with different clients in different industries. It seemed like a great way to just constantly be learning about get a broader experience with different industries and different types of businesses.

[00:05:25] Taylor Radey: I liked the idea of being surrounded by peers. Up until then, I had been working in very small marketing teams, and I was often the only person who did what I did. So the idea of being surrounded by peers that I could learn from was really exciting to me. I ended up learning so much from the people that I worked alongside.

[00:05:46] Taylor Radey: It’s hard to pinpoint the exact moment that I wanted to actually start my own business. Looking back, there were more signs along the way, but I definitely think around that time, I started to get a sense that I would, at some point, want to start my own company.

[00:06:01] Taylor Radey: I had no idea when that was going to be and what it was going to look like. But I knew that if I worked for an agency, I would get a better understanding of how I To package services, how to deliver services and how that actually worked. That ended up being a great way to do that, especially because PR 2020 was a smaller agency and it was an agency where there wasn’t a lot of specialization, everyone was expected to do everything, to have a lot of autonomy. You did do a lot of account management and account development.

[00:06:33] Taylor Radey: In my last year there, I was the director of marketing and so I was part of the leadership team. I was able to see the type of data we were looking at how we made decisions about the business.

[00:06:44] Ron Laneve: It seems like Paul did a really good job at providing operational opportunities in the business as opposed to, just delivering solutions to clients along the way, Paul Roetzer, that is.

[00:06:54] Taylor Radey: Yeah, absolutely. We generally would develop our own accounts again. You would be, so you’d be doing sales, you’d be doing business development, you would be sending invoices. Even just those kinds of administrative things again, when I started my own firm, I had some baseline knowledge of how those types of things worked, we didn’t just pass them off to some other department within the company. it gave me a lot of foundation for that as well. It helped me with technology onboarding, with change management with digital transformation and new technology adoption.

[00:07:28] Ron Laneve: As I was reminding myself of your background and I remember that PR 2020 was HubSpot’s first agency partner. It’s interesting now how that’s come full circle with everything that Dharmesh is doing with Agent AI. I’ve proudly completed your course recently. Can you expand upon the AI services that Randall pine is offering today? You provide a lot of great content out there and a lot of great methodology around how to think about it. What niche are you carving out?

[00:07:57] Taylor Radey: Yeah, absolutely. So right now I’m focused a lot on adoption really wherever a company is along that path. We have services all along the way. So I teach five stages of Ai adoption or five steps that companies need to go through.

[00:08:16] Taylor Radey: Whether that is Identifying initial use cases and guided pilot projects. Building a case internally if needed for budget for buy in. Ai ops, so focusing on putting Guidelines and guardrails systems and processes in place for AI roll out to the team. Creating an AI policy so we can help with those types of things. Training and onboarding. So that’s where a lot of my courses to help people just understand how AI works and how to apply it to their roles.

[00:08:49] Taylor Radey: Accountability change management and support. That is, I think, the piece that is going to be missing. That’s the thing that I’ve learned over my career is often missing is actual follow through after the initial training and making sure that I use is easy. It’s habitual is consistent across the team.

[00:09:08] Taylor Radey: Then I transformation, which I don’t think a lot of companies are There yet. But I think that you’re going to start to see that more and more where people start thinking about if I were rebuilding my business today from the ground up with AI, how might I do it? How might it change my org chart, my services, my pricing? Taking that first principles approach.

[00:09:30] Taylor Radey: That would be more of a one on one consulting engagement. For the rest, it would either be a direct consulting engagement with the company, or do one to many through Live in person trainings, virtual trainings, and now some on demand courses as well.

[00:09:46] Ron Laneve: Sounds like it goes beyond leveraging AI for marketing or digital marketing?

[00:09:50] Taylor Radey: A lot of times I am talking with leadership. In those cases, a lot of my early pilot projects and early adoption was with my marketing clients. It was in helping them with their marketing. But I’ve been expanding more and more when I’m talking to a CEO, they’re just thinking about either just what was the greatest opportunity for value operationally.

[00:10:11] Taylor Radey: That might be market marketing and sales are often a great place to start. But sometimes people are just looking for low hanging fruit. Maybe they’re not quite ready to dive all in and they’re just looking for what are some small wins anywhere in the company where there’s some sort of repetitive process they can apply AI to.

[00:10:27] Taylor Radey: Really just taking a big picture look at the business and where the opportunity is.

[00:10:31] Ron Laneve: Are there any case studies you can share from the clients you’ve worked with?

[00:10:35] Taylor Radey: Yeah, of course. The first client that I’ve been working with, I was using originally a tool called HyperWrite to help them with some blog post creation. This was pre ChatGPT. I had already been working with them on some early stage generative AI solutions. Once ChatGPT came out, we were looking for opportunities. The head of the department I was working with, they were looking to launch tons of landing pages that were focused on lots of different industries. So they wanted to create a lot of content that was fairly formulaic in nature.

[00:11:12] Taylor Radey: It was in insurance, focusing on lots of different industries. So insurance for plumbers, insurance for health care. So they asked, is this an opportunity where we could use AI to create that content?

[00:11:25] Taylor Radey: we identified that this was a great pilot project because it was highly repetitive, but also would have required far too much manpower to actually create. The company was running pretty lean. They couldn’t create hundreds of pages manually. It just wasn’t in the budget. We figured out what the process would be. I broke down the steps. To create those landing pages. We identified the tools that we were going to use. We selected ChatGPT, along with things like HyperWrite and Grammarly. We were using a few AI tools for different parts of the process. I wrote the prompts that we would use and we tested that then pulled together a team. Of course you need the human in the loop, you need people along the way that are running the information through the prompts, they’re double checking it, they’re proofreading it.

[00:12:14] Taylor Radey: This was in the first half of 2023 that we did this and we created I think around 150 website pages. if had they written all the content themselves or hired us it was the equivalent of basically saving $200,000! I think we had a 92% percent decrease in the amount of time or a 12 X output for, what we could produce in one hour with AI compared to having done it, the old fashioned way with writers.

[00:12:48] Taylor Radey: This is with, I think, ChatGPT3. I think 3. 5 maybe came out partway through the process. So it was an earlier form, too. The writing, it wasn’t as good. It could have actually been more efficient. The problem with this case study is, I think, that these numbers, $200,000 92% reduction in time. The numbers are so big that it sounds too good to be true.

[00:13:15] Taylor Radey: I think that’s part of the problem with AI is the scale and the efficiency gains can be so massive. If you have prompts that work, clear processes in place, a team that has been trained on how to do this. It almost, it sounds too good to be true

[00:13:33] Taylor Radey: In the end we wound up saving them basically the equivalent of 200,000 and we’re able to get all these landing pages up and live and they were able to test a marketing strategy that they just wouldn’t have had budget for otherwise.

[00:13:45] Ron Laneve: Two things. It’s funny that even a year ago is almost outdated. Considering what you could do with Claude today or, all the AgenticAI that’s coming out so fast. It’s just crazy. Then 2, we’ve talked about the economics. How do you price these types of things? you got to always think about, and this is for all of us, not just you, or are we leaving money on the table?

[00:14:07] Ron Laneve: Is there some other way to generate revenue around these services? Very fascinating. Thanks for sharing.

[00:14:12] Taylor Radey: Of course. In this case, this was a great opportunity for me to run a massive pilot project. 18 months ago was still pretty early for a lot of people and a lot of companies.

[00:14:24] Taylor Radey: In that case We sold them, the billable hour model worked because we were able to say this is going to save you a ton of money and gave us the opportunity to do this project. Yeah, for professional service business, they’re going to need to rethink their pricing strategies. They’re going to need to think about value based pricing and how they can use AI.

[00:14:44] Taylor Radey: But the pitch is not this is deeply discounted. It’s we’re building you a system that’s going to save you money and help you scale and there is value in that. And not basing pricing on the actual hours that the team is putting in. I think that’s just going to wind up being a race to the bottom.

[00:15:03] Taylor Radey: We need to think new ways of how we’re adding value in these types of relationships.

[00:15:08] Ron Laneve: Exactly. So that’s a good segue. And whether we recorded this conversation today, or 3 months from now, or 6 months from now, we’d be talking about some new hot thing. But today, in December of 2024, it appears that AgenticAI is, the hottest thing in AI, at least from my perspective, from all the reading, studying I’ve been doing.

[00:15:29] Ron Laneve: Are you leveraging that at this point or what impact are you seeing with that?

[00:15:35] Taylor Radey: I think the tricky thing with agentic AI or AI agents right now is how we define what that even is. There doesn’t seem to be a lot of consensus around what an AI agent is even among some of the top people in this space that are creating them. I’ve personally see AI automation, bots, AI agents used somewhat interchangeably. The lines between those terms are a little bit blurry right now.

[00:16:06] Taylor Radey: Personally, what I would think of as an AI agent would be where it is able to actually complete an action. Order me a pizza, book me a flight type of technology. When it comes to that, I don’t see that right now. And even if it were available, I would not be using it for the same reason that I would not give a stranger remote access to my laptop. You don’t necessarily know what programs they’re able to access, what data they’re viewing, what data they’re storing. I don’t want it booking me a non refundable flight or ordering me 500 pizzas, like taking some action I wouldn’t want. I don’t think we’re there yet.

[00:16:47] Taylor Radey: But there are a lot of other things that are either what I might consider automation, which is where you might string together a series of prompts or custom GPTs or API connections through something like Zapier or make.

[00:17:04] Taylor Radey: What you’re able to do is, let’s say, to create a case study, you give it some basic information and it goes out, it researches the company, it feeds the information into a GPT that writes the case study that then gets, emailed to you. So you’re able to just set it and forget it in a sense. But it’s a very linear sequence of actions that you are creating. But that’s still Highly valuable.

[00:17:34] Taylor Radey: There’s also specialized bots. Agent.ai that Dharmesh Shah of HubSpot created. They call them agents and the call to action button is Hire To me, they feel a little bit like bots because they’re like custom GPTs in a different wrapper. They’re very structured and narrow tasks like generate a transcript from a YouTube video. Analyze a pricing page qualify a lead. They’re very, fairly narrow in scope. But again, I think that could be highly valuable and you probably will eventually have a collection of these that you’re working with.

[00:18:13] Ron Laneve: Yeah, I think here they are clearly laying down the foundation to start connecting these, their versions of bots together, their versions of agents together to make them do more in an automated fashion. I finally got accepted into the agent AI builder program. So now I got to figure that out.

[00:18:31] Ron Laneve: Which is another good segue. It’s overwhelming how much content is available to us and in studying and learning and reading and watching videos and trying to accelerate or, be as AI efficient, if that’s a thing, as you can be is tough.

[00:18:49] Ron Laneve: It’s tough to focus and tough to stick to a plan. Do you have any suggestions or, for individuals, trying to do the same thing? And it probably widely varies if based upon where you, where your starting point is. I get it. So that’s an unfair question, but what are your thoughts on that?

[00:19:06] Taylor Radey: First is I personally would recommend getting some baseline level of knowledge in AI. I have a course, but there’s free courses. I think it’s helpful to have some sort of foundational understanding of what generative AI is, how a large language model works. It’s just going to help you better understand how to use it effectively and the benefits and the risks. Especially if you’re a manager, An executive a business owner, you’re gonna have to be making strategic decisions about AI. I think having some foundational knowledge will give you a better framework and foundation for those decisions. You’re probably gonna miss things if you’re just reading lots of one-off articles. So having some sort of structured content as a foundation I think is really helpful.

[00:19:52] Taylor Radey: As far as keeping up with things I actually just covered this in my newsletter a couple of weeks ago. How to keep up with AI when you’re already overwhelmed. This was a topic that felt like it really resonated with me because I get it, it’s a lot to keep up with, and I think the biggest thing is to be clear on what your goals are.

[00:20:14] Taylor Radey: You need to be selective. You can’t follow all of it. You need to be really selective about what your main goals are so that you can filter out the news and the sources that are really relevant to you. Then to have those trusted sources of information that can do some of the curation for you.

[00:20:32] Taylor Radey: Tim Ferriss talked about this in his Four Hour Work Week book. He talks about this kind of selective media diet where the goal is to not follow everything, but to follow the things that matter. You can choose people that you trust that are going to tell you separate the signal from the noise and help you understand what really matters and what to focus on.

[00:20:52] Taylor Radey: The last thing I would say is I actually think that it can be simpler than people make it. A lot of what I teach is focused on work. It is not focused on tools because I actually think that there’s a ton of value that you can get out of those frontier large language models, ChatGPT, Claude, Gemini.

[00:21:13] Taylor Radey: It is so easy to get distracted and to try out new tools and capabilities rather than thinking about, oh, that’s a cool tool, how could I use it? I recommend that people look at your day to day work that you have to get done and then figuring out how you can apply the right tools to continually like you’re saying, become more efficient and continually upgrade and up level that work.

[00:21:38] Taylor Radey: I think that makes it a little bit less overwhelming and more concrete and certainly more practical. You’ll get more value out of it in the short term.

[00:21:46] Ron Laneve: I love that last point. I’ve signed up for every newsletter under the sun, to read daily and weekly updates in AI, which they’re good. Then at the end, they’re like, here’s the latest tools. I start clicking through each one. I’m like, oh, that one’s cool. That one’s cool. And then I’m down a rabbit hole and then it’s over, and I’m like, what am I going to do with this? I should have just, I can leverage to your point Claude or ChatGPT to do what I need to do and don’t get lost in all these other things. Obvious point, but hard to focus on. So love that point.

[00:22:16] Taylor Radey: I think that it’s hard. it is valuable to keep an ear out, keep an eye out for what’s possible, because I think some of this is like you don’t even realize what’s possible until you see some of these tools. That can open up some new ideas of things that you hadn’t thought about. I think in general it’s better to start with the work itself. I also really think that for especially executives and business owners and, entrepreneurs ,want to be entrepreneurs I think focus is going to be a competitive advantage in the future.

[00:22:46] Taylor Radey: That has always been true, but I think as we see Just these cycles of technology, just moving faster and faster. There’s going to be so much distraction. There’s going to be so many shiny objects and the default will be to get distracted. So if you’re able to focus, you’re going to be ahead of the competition because you’re focused on your goal and applying the right technology to your strategy.

[00:23:14] Ron Laneve: Great advice. All right, let’s switch gears. I want to talk about an area that’s near and dear to me is our next generation of business people. Emerging college graduates, people entering the work world here shortly.

[00:23:27] Ron Laneve: My overarching question is what suggestions would you give to them on where to focus their time and energy and in either classes or subject matter or how to approach and get ready for the transition into the work world. Things are changing faster than I’ve ever seen. I never thought a year ago that a software developer would be out of work ever. And in this year, I’ve seen a lot of people out of work and I’ve seen AI start to chip away at roles really, marketing and even content development and creative work starts starts to worry me a little bit. I don’t wanna be too cynical but I am worried about it. So what are your thoughts? And answer that any way, you’d like.

[00:24:07] Taylor Radey: Yeah, of course. I was actually speaking with high school seniors last week, and we were talking about this exact thing because they were asking, what should I major in? Will my employer even care about my degree? Are we going to need to work? Is AI going to take jobs? We were talking about all this and they already in high school were seeing, the problems that they were going to have.

[00:24:27] Taylor Radey: I told them, I dated myself and said, when I graduated from college, Twitter was brand new. The iPhone was brand new. Instagram didn’t exist yet. There’s even in the span of my career, there’s been so much change. And I said to them that there are probably jobs that they’re going to have in their careers that just don’t exist today. Advice for really anyone in any stage of their career is to learn more about AI, which is just baseline advice, because I think that right now it’s a really good way to differentiate yourself.

[00:24:56] Taylor Radey: But I think in the not so distant future, it’s going to be a prerequisite for a lot of jobs.

[00:25:02] Taylor Radey: I think that the way that you use AI depends on where you are in your career. So I asked them if they had used chat GPT and a hundred percent of the hands went up. Meanwhile, I asked them if they owned a PlayStation and 40 percent of the hands went up.

[00:25:17] Taylor Radey: So more of them have used ChatGPT than own this gaming console, which did surprise me. I said, that’s great. You’re learning about it, you’re experimenting with it. But I also really cautioned them not to use it as a crutch. There’s no shortcut to becoming an expert, at least so far, it seems that 10,000 hours, you have to put in the hard work and you just won’t get there if you turn to ChatGPT, every time you don’t know something and every time that approach something hard. I think, be a really hard line to walk for a lot of young professionals and college grads cause it’s going to be so easy to just lean on chat GPT, but I think you need to learn how to use these tools and also become an expert in some domain.

[00:26:05] Taylor Radey: So why does expertise matter? And that kind of gets to my advice for people later in their careers who maybe have 10 or 15 or 20 or more years of experience is they have an opportunity to meld their experience and expertise with AI.

[00:26:21] Taylor Radey: They essentially have an opportunity to scale their experience and expertise now. Sure, a young, recent grad is going to be able to get a pretty good answer, produce something pretty good with AI. But someone with more experience is going to be able to write better prompts because they have better context of the industry, the company, the role, the project. They’re going to be able to better assess the outputs because Again, they’ve done the work. They might make connections that a younger professional might not make. ChatGPT, your AI might be able to create you a blueprint, but are you really going to start construction on that house without a professional who’s going to assess whether it is structurally sound? We still are going to need those people to double check things. They’re going to be able to write better prompts. better assess the outputs and they’re going to know what to do with that information in the real world.

[00:27:18] Taylor Radey: I think being mediocre, to be honest, is going to get a lot harder. But if you work really hard and you become an expert in a specific domain, that can actually be incredibly valuable. If you’re job hunting, I think the narrative is go to the job opening and scroll down to the requirements and pick one of those responsibilities and figure out how you could build a custom GPT make that task more efficient.

[00:27:45] Taylor Radey: I don’t think that you should be afraid of this idea that oh, I could just do this job. I think the way that you sell it is I can be so much more efficient in this role because I know AI and also I have the experience and the expertise and the domain knowledge to be more effective in this role. You can bring those two things together to be a supercharged version of the job candidate that people are looking for.

[00:28:14] Ron Laneve: Did you have you seen Chris Penn’s latest video series on job hunting and putting together?

[00:28:21] Taylor Radey: I was actually going to suggest it, but then I saw you commented and so okay, you’ve seen this because yeah, he is just brilliant and really seems to just. Put so much value out there for free, which is really nice. I saw that he did that as a holiday thing to help job hunters. And I haven’t looked closely at it, but I’m sure knowing him that it’s great and an extremely great resource for anyone who is job hunting right now.

[00:28:46] Taylor Radey: Use it to make yourself a compelling candidate, but then probably turn around in your interviews, be able to speak to the ways that you can use AI.

[00:28:54] Ron Laneve: It was great for the job hunting process, but there was a bunch of what I would call indirect learnings related to just how to use chat more efficiently, or how to better write a prompt to get what you want, or the whole concept of a scoring rubric. It was interesting. His video is great.

[00:29:11] Ron Laneve: I know you published a post recently around the top people you follow in, in AI. I think a few of them, we share Ethan Mollick, Chris Penn, Paul Roetzer, Mike Kaput. I would include you in that list on my list. Can you refresh my memory who else would you suggest that people watching this should follow as well.

[00:29:30] Taylor Radey: Yeah. So Paul and Mike, the the artificial intelligence show, I think is the new name of the podcast.

[00:29:35] Taylor Radey: That is a great source for keeping up with the weekly kind of onslaught of news. Ethan Mollick is great for a lot of research especially because he is actually collecting real data on a lot of these tools and gets early access. Allie Miller. She came from Amazon. She’s constantly putting stuff out and creating free content. Chris Penn and Trust Insights, again, tons of great insight and also he seems to really have a deep knowledge of how the models work. So he can provide a better context around why things do what they do. He can explain at a more fundamental level how these systems work and therefore why these different strategies are more effective.

[00:30:20] Taylor Radey: I follow some other people that are more To get ideas for use cases. But as far as really broad knowledge, I look for people and I outlined recently my criteria is I really look for people who have real experience, who provide real insight but beyond just repeating headlines. There’s enough headlines out there already, and I want them to have a distinct point of view on AI. I follow a lot of other people, but I see a lot of the same things. And I think from that list, what you get is people who have a distinct point of view about how you should apply AI or what it’s going to mean for work. I think that’s really valuable too, to make sure that You’re getting different perspectives. You’re getting someone who’s really thinking deeply beyond just the surface level here’s this new tool of the week. Here’s this new use case. I tried and really drilling into those kind of bigger picture questions, but then making it extremely practical and applicable in my everyday life and work.

[00:31:26] Ron Laneve: Perfect. Taylor, thanks again. It’s a pleasure chatting with you and look forward to continuing to follow all your success. Thanks for your time.

[00:31:35] Taylor Radey: Thank you so much.

December 6, 2024