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.
  

This is Part 2 of our our interview with Bradley Reynolds, successful tech entrepreneur, Artificial Intelligence and Enterprises LLM Consultant.  In this second part of our chat with Brad, he shares:

• how AI is impacting the job market
• how companies will need to evolve to adopt AI to operate and compete
• his personal capabilities in helping companies adopt and implement an AI strategy
• the importance of building a personal brand to differentiate yourself in your job search as well as in your current role

Summary transcript of our interview below:

Hello, and welcome back to Part 2 of Episode 17 of my interview with Bradley Reynolds Enterprise AI consultant. In this part of the conversation, Brad and I discuss two primary areas. First, is the impact of artificial intelligence on today’s job market, on businesses, now and in the future. And specifically his expertise in helping guide companies of all sizes especially at the enterprise level through AI adoption and implementation. 

And secondly, we focus on the concept of building your personal brand, it’s impact not only on your job search as well as the role in your current company, and into the future. 

I hope you enjoy. And please don’t forget to subscribe for future additions of the focus on talent video series. Thanks a lot. 

[00:01:00] Bradley Reynolds: Just to me, AI ignore the stuff that I’m doing. The feel of it is the same energy and feel, if not more. Then I had in 1993, ’94 on the bulletin board systems and the early internet. At that point, it was getting the information. You didn’t have to go to a library, you could get to information and oh, but by having the information available and easily distributed, great things will happen.

[00:01:28] This is like that, probably ten times bigger or a hundred times bigger because this isn’t just information, this is actual thinking and a reasoning and there’s all kinds of philosophical arguments about whether the machines think and their sentient terminator going to exterminate us and all that type of stuff.

[00:01:48] But this is like something that I can outsource. Right now and I do this just as an individual 20% of my day making presentations writing email ideas creating some graphics. What is 25% of your life and business worth? It’s a huge amount of efficiency. You could use it to not work. You could use it to work more. Whatever it is. I’ve never seen anything like that. So that’s exciting and It’s a nerdish discipline. It’s highly data intense. To actually understand what goes on inside of the black boxes. Deep math. You need to understand data infrastructure. You need to understand things that I’ve done my whole life.

[00:02:33] Where Securable evolved out to becoming more creative and well, actually, you’d probably do that with AI now, but is it evolved to things that I wasn’t good at this area of what AI is and how it works and why it does what it does is just highly technical and the people that are making policy right now are nerds. Like they’re not business people, like Sam Altman, nerd, Yann LeCun, nerd, and they’re the Deep Mind guys at Google, nerds. And, but they’re making these huge impacts across society, and people realized when ChadGPT came out last November, and they could talk to an artificial intelligence like they were talking to somebody on a podcast.

[00:03:16] It woke all of us up. I’m, considering myself understanding of AI and whatever, it woke me up. It was like, oh my gosh something huge has been fermenting and it’s now available and how do we get our hands around it? And everybody’s blind. How do we get our hands around it? And I decided okay what’s your nature, ground view? What do I have to start a business around this? And then as you start reading and getting deep into the education and the math and like seeing what people are talking about, I felt there’s no way I have my arms around this thing enough to figure out some sort of a defensible product because I feel that it’s changing so much so quickly.

[00:04:00] That no matter what your idea is, unless you’ve been doing this for seven, eight years, very small amount of people that have been doing that. How do you know what isn’t going to be stolen from you in two months? Because smarter, faster, younger folks in the Silicon Valley with more financing are just going to take that thing. And so I’m like, okay how do you get your hat in the ring? I know I want to be involved in this thing. I don’t have that product idea. Just hang a shingle and be a consultant. 

[00:04:29] That was it and it was just and start to triangulate some broad areas where you think there’s a defensible niche at least from a consulting perspective and then maybe a business idea comes out.

So the thing about the consulting is a path to get to a business idea, but who knows maybe it’s a path to get to running a division of a company or maybe it’s a path to just being a permanent consultant. Don’t know, but you’re getting paid while you don’t know.

And you’re figuring that type of stuff out. And the area that I ended up honing in on is very basic concept of, I love what chat GPT can do. I want it inside of my company as a CEO. I don’t want the data from my company going out on the internet.

[00:05:15] That’s it. So however, wherever you call it, if you call it private chatGPT, I ended up calling it Enterprise LLM consulting because the chat or GPT is an LLM, but it gets to the point of I want this like super intelligence available to me, and my employees and my processes to make my business more efficient, to make them do more, have assistants. Like we all have these like super intelligent assistants to learn from, to help us create an idea and all that stuff. But I have customer data. I have employee data. This is sacrosanct. Some of my businesses could be regulated, banks, medical or whatever, can’t go out there. So how do I get the best of that internally?

[00:05:58] And there’s technologies to do it. In Cleveland, not a lot of people are deploying them yet. They’re talking about what do my next 12 months need to look? What do I need to be concerned about? What are the big rocks that are out there? But that concept which I think has a lot of legs for the next 10 years is How do I have enterprise grade artificial intelligence? And I think a lot of it will start like the big use case now is how do I get that kind of like chatting? How do I chat with my data in English language and have this kind of system spit back stuff for marking all the stuff you can do with chat GPT and more. And there’s just a lot of interesting spots in there.

[00:06:38] So I don’t know where the actual business idea is. If you go on LinkedIn and search for LLM, one of these like kind of technical terms, there’s like crickets in Cleveland. Zero. So if you’re like a young person going to these meetups about AI, there’s a few of them. There’s some through North Coast Ventures and there’s some through the Marketing AI Institute. They host these things. I’m like, put it on your resume, put it on LinkedIn. People search for these things and you just by having those words on there and they’re relatively unique words right now, but raise your hand, and so put that LLM, Enterprise LLM, put ChatGPT on there, put Databricks, put all these technologies that you have experience with. Get them out there and talk, call, add AI ML into your title. If that’s what you’re actually legitimately doing, figure out how to be that expert at your company. There’s billion dollar companies in Cleveland that do not have anybody chasing AI down right now. No champion internally that champion can come from accounting, champion can come from programming, that champion can come from the data section.

[00:07:55] But somebody just needs to say, Hey, I want to be the AI expert at XYZ company. And so there’s a huge kind of opportunity, at multiple phases of your career, whether that you’re on the youth side.

So if you’re in high school, college right now, you better know how to be great with these tools. That’s a huge asset. Like if you’re in high school right now, you’re, the number one thing you can learn is how to use AI effectively because it covers the umbrella over all subjects. You’re going, if you’re going to college, it’s like it is the best teacher you could possibly have. Your professor might be great if you ever see them. Your TA might be great when you see them, but you literally have somebody who’s maybe more versed than your professor in their particular subject matter. And you can ask them pinpoint questions about certain nuance areas, like hey, I get three out of those four points, but I need a lot more on that fourth one.

[00:08:54] No textbook can do that, the TA might not be capable, and you can keep drilling into the AI until you truly understand what’s going on. And that’s, it’s like magical type. 

[00:09:06] Ron Laneve: Yeah. And I think it’s going to be a huge opportunity for, what I’ll say, liberal arts majors and creative people to, make use of this technology and, think outside the box to solve those problems and create again, new opportunities, but, separate from that what skill sets should I would say younger talent be thinking about adding to their repertoire and companies be thinking about needing to add to their teams? Obviously what comes to mind is data science, experience and machine learning, right? That’s, the core to building these big systems. But, what else do you think is a pretty valuable skillset to have? 

[00:09:45] Bradley Reynolds: Yeah, it’s been around for a long time. It’s just everybody paid attention to it after ChadGPT came out last November, but the traditionally, it’s been a scientific mathematical realm, like the folks that were doing AI were data science, were machine learning people coming out of those types of courses and the background of those courses very deep. The thing is now is that there are like open source locations like a place called Hugging Face, which is a hilarious name. But where and there are scientists tuning the open source models to have optimizations to those things.

[00:10:28] So really, if you wanted to have a chat bot that answers questions, that’s almost as good as GPT 4 the highest level on the OpenAI has. It’s available right now for free on Hugging Face. You download it, do a little Python, front end work, in 10 minutes, you can have a rudimentary chat bot serving up answers to some constituent, and this is like the highest of the high tech in terms of what underpins these things.

[00:10:59] So to me, that says that the premium on talent is not going to be on scientists. Because there will be scientists out there doing that, and there is certainly a premium there, but it’s the folks that know how to weave together the kind of building blocks of these. DevOps would be maybe what somebody’s called in the market, but like somebody who has an acumen for Python. But more of a notion to almost like I want to do the least amount of code as possible to get the output. So like an entrepreneurial mindset of what are the tools and building blocks. I’m going to stay on top of what those tools are because last week it took 200 lines of code to do this chat front end. Now it takes four because I know what the right tool is. I know Python, so I can orchestrate and build those things together. But I don’t have to be a scientist anymore. 

[00:11:55] And so that level, there’s not a lot of scientists, but there’s a lot of engineering capable people. And so I think that person that knows which tools to pull together is the person that has on the technical sphere, a lot of capability kind of long term. So that’s one area. So probably python and entrepreneurial or DevOps type spirit, cobbling together commercial technologies or open source technologies. I think that person is going to have a long runway. 

[00:12:25] There’s another runway, which isn’t data science, isn’t ML, but it’s this notion of these large language models like GPT or the self hosted ones, they have been trained on the giant section of the internet as of some cutoff date. So like GPT cutoff date is late 2021. It knows nothing after that period of anything that’s happened. So at the point that you want to be topical. I want a specific answer or I want a reference like a trouble ticketing system at a company of some ticket that’s happened in the last four days. You need to augment those with external data sources, whether you retrain the models or just do, we’ll call them database lookups out there.

[00:13:12] The notion that these things don’t have memory, but we can augment that with stores of memory. They’re even talking about taking the whole internet. And turning it into one of these databases so you can search it really quick without having to go through Google. So that you can stay topically up to date and relevant where you think about the big LLM is more of a reasoning, reasoning engine, it knows the interrelations between things, but it gets really crappy when you want the one thing give me the review for the Mazda Miata from Car and Driver. It doesn’t do this, it’s not meant for that. It could tell you why a Mazda Miata is better or worse than a BMW something, but it doesn’t know that very pinpoint. That’s where all that other stuff comes in. 

[00:13:56] So what is important there is the orchestration layer that the person we talked about in the first part does and how they pull data from different sources and integrate different kind of we’ll call them API’s. That person is very valuable, but like, how do you get that good data, say, like inside of a company available for that other person that we talked to, to be able to reference, Oh, I want to pull this data really quick out of the trouble ticketing.

[00:14:24] He says there’s a lot to that. And so I don’t know what the title of that job is, but essentially it’s a person that builds data pipelines because getting to the data and feeding the data and present in a format that AI can consume is something that not a lot of people are talking about, but it’s super important. It could be somebody that evolves from being a DBA but it involves code too. So the way that I look at it is. Can you present this really interesting data in an API kind of consumable format so that programmer could just yes and grab this trouble ticketing data from here super simplified so abstract a lot of stuff under the hood How do you keep that up to date in and fresh and how do you D- anonymize it take out the PII and all that there’s a lot of stuff. But the notion is I will build these pipelines and where that comes in the future is companies are going to be using this AI to talk to all of their data. Their trouble ticketing data, their server maintenance data, their power system data, their financial data, their sales data.

[00:15:34] Great. That’s all in a bunch of places. So how do you make it simple for the AI to talk to the data? That’s the data person that has to present it simply. The AI programmer person will make sure you have the right AI or set of AIs. It could be hundreds of AIs that you have. It could be a financial AI that knows balance sheets and profit loss statements. There could be a SQL AI and there’s database language, there’ll be a whole bunch of this.

That person would be responsible for choosing that tool and then the data pipeline person responsible for presenting it in a way and getting it in the right spot and latency and all those kinds of things.

[00:16:11] Both of those jobs will. Have a long runway if people are scared about is the AI going to replace what I do, but. I think the two technical disciplines are super simple. 

[00:16:22] Ron Laneve: And then probably every, I would think that every group within the organization, whether it’s marketing or sales to your point, finance has their subject matter, business analyst or product person that needs to design or ask for what they want. As well out of the AI for that enterprise. 

[00:16:38] Bradley Reynolds: Yeah, I think so for the time being, yes. But I the vision of where you would want it to go is. If you’ve designed your system right between the front end programmer and the data folks, you will want the folks in your business the subject matter experts, not the policy people to be able to speak in the English language to their data.

[00:17:04] Like you’ve designed it in a fashion where you don’t know exactly what they’re going to ask, but you’ve given them the sandbox to, to ask those questions. Things that they had previously had to specify and then send to a data team who would then have to create a statement to generate a business intelligence report to send back to you for you to say, that’s not what I want.

[00:17:23] If the AI might spit back something to you, that is not what you want it, but if you’re in the chat now and you say, ah, that’s not what I wanted.. Can you re allocate this and change this over here? Okay what about, how about doing a linear regression of this thing? The plumbers have plumbed it between you and the AI. You’ve cut out all of the kind of middlemen and so you’ve disintermediated the conversation to be like, now I can get that answer and I can tune it and tweak it to what I need. I didn’t have to pre specify it and play the telephone game of somebody misinterpreting it down along the way.

[00:17:58] And so SVP, VP, manager, they can get the answers they need and run models and do all that kind of stuff without that kind of layer. So the difficult part is how do you make it easy for them to speak in English to the data? That’s a difficult problem and there’s no way around that.

[00:18:16] Ron Laneve: As we wrap up, can you talk to me a little bit about advice you would give experienced people in this market around looking for their next job, differentiating themselves from one person to another. You’ve been fortunate where you’ve never really had to go through it. You’ve been the starter of businesses and you’ve been the employer of other people. But in that position, you’ve seen a lot of people interview apply. What have you seen along the way? And what would you tell other people to help them? Like I said, get through this time and also differentiate themselves.

[00:18:52] Bradley Reynolds: Yeah. So I’ve thought about this because I’m even in my consulting looking to, make a mark and differentiate just because I have a network doesn’t mean any of those people could care about AI. So relative to my experience of just unique behavioral pattern. A lot of people work from home. It’s difficult to get maybe FaceTime, Zoom calls. I know it’s anecdotal. I don’t know if this is indicative of anything. I can’t get anyone to answer an email from me. I also am slow answering emails and missing emails from other people because my inbox is like 500 long every day. And so like I process through it serially and i’ve been how you know I need to get back to Ron or you back this and then sometimes I miss it. And sometimes it pops back on my head sometimes it doesn’t and it’s not intentional just somehow that’s just the way it rolls right now.

[00:19:42] And I see that across the board. I do think like just how do you provide some sort of a signal that gets out of that? Persistence, to me is even more important now in the notion that just because somebody doesn’t respond to you doesn’t mean that they dislike you, they’re uninterested in you. Just assume that they’r overloaded. And that assume they do want to talk to you, but it might take where it used to take an email or two, it might take, ten. They’ll tell you if they don’t want to talk to you or just filter you. But I found that my number of knocks on the door that I need is a lot higher.

[00:20:29] And this is from people that I have a network with and that I know. So at the beginning was like I made me question like do am I providing any type of value or did I not have a good relationship with this person? But then when I talk to people we are like, oh, yeah, I do that same thing, too so it was is more of that. And so you gotta like Just get rid of the any type of self doubt around then and if it was like, hey I’m applying for something or whatever they can tell you no or whatever but like I reach out to all those people on linkedin and multiple times and send emails and you know mention things about their company all that kind of stuff for sure. Do that and if they don’t respond they just probably getting a lot of linkedin messages, but eventually that signal will come through. But I think the, to me, the biggest thing, and this is a strategy that I employ for my just consulting practice, but I think you should just be employing this as a human.

[00:21:26] That we’ve seemed to have pivoted from being company centric to human centric, like individual centric in terms of the brand. And so what do my kids want to be when they grow up? They want to be famous YouTubers. They don’t want to go to the guru. But, and what is that? It’s about building an individual brand and not everybody is going to be a rockstar at doing that. I’m not great at doing it. So it just takes a intentional thing. And so like for me, it’s like I want to post one thing that is insightful in my own voice about ai every single day. If there’s nothing interesting i’m not going to post garbage. And it has to be in my own voice. It can’t be AI. And That one thing. Now, I do connect with people on LinkedIn and do that type of stuff, but that one thing has driven more communications and interest than any other thing. 

[00:22:22] Because there’s no I’m not soliciting anyone. I’m literally just trying to provide signal and the noise of AI, which is a Something valuable, but i’m not saying hey come to Yellowfin and get my consulting. So it’s like I would say in that kind of maybe individual brand focus thing if you’re looking for a job middle stage of your career start pushing value out to the world without expecting explicit reciprocity. You’re doing it, you’re building your brand to build your career, to build your money making capability, to get a job, get it like that’s what you should do. But just you have something that is valuable. You have something that’s worth listening to. It may be in a niche. It may be a very broad thing there’s folks that are going and being career coaches like there’s all kinds of ways to do it. But it’s like going to the gym. You just have to put that discipline on your calendar and say hey I’m gonna do one really deep thing a week or Ron what you’re doing.

[00:23:31] I’m gonna do these podcast episodes. Like It is hard, it takes work, a lot of planning, a lot of communication, it’s all this stuff takes work. But as long as you do that, you’re gonna look back and say, I have a string of that, I’m on episode 17 or episode 200, I’ve made a hundred of these posts, good things come.

[00:23:50] And I, I think in the era of… AI, which we should all embrace and anybody is in their career early, late, middle, they should become an AI expert. But what AI doesn’t do is it doesn’t provide an authentic human experience. It sounds like it’s hollow. It’s like drinking beer out of a plastic cup versus a glass bottle is. And so the things that let you as a potential employee or a business owner, whatever, speak with your own voice, I feel that’s just going to be getting more and more valuable. And so show that. And it takes work and not everybody’s creative. And in this case the one case where don’t use AI To write things. 

[00:24:33] You can use it to generate ideas. I want to write about this, But what are some areas I could focus on great do it for that. But do not let it write. Nobody’s hiring AI for a job right now. So at the time that you interview or meet somebody in person, there’ll be a disconnect If you use that voice for your posts and what you can actually produce you want when somebody first interacts with you To be a one to one between what they’ve heard and the story that you’ve built up And what you’re able to deliver because they’re hiring you. They’re not hiring your ai you might be able to use an AI to do things. But I think that just being intentional and building an individual brand around what you think, what value you think, Hey, I’m great at sales in technical area. Or, Hey, I’m awesome at marketing.

[00:25:20] You’ve done it as part of your career. Maybe you’re 20 years into your career. You have 20 years of insights that you can give. So build your brand. Say you want direct employment and you’re not like finding it We’ll look at consulting look at fractional opportunities Look at ways that you can continue to keep that saw sharpened.

[00:25:41] You might find that’s a permanent gig for you. Hey, consulting could be a permanent thing for me. Maybe not, probably not, but you don’t know. There’s many opportunities to not sit on the sidelines. And there’s a couple of folks in AI, they just start webinars. We’ll start talking about this. And they build their brand that way. If they feel they have enough creativity to supply a webinars worth of stuff host it for free. That’s how they get business is they just do webinars and then business comes in from there. If say like the tech hiring is slow you got to do something.

You can’t just sit on your hands and hope that the market changes, start raising your hand, talking about things and looking at maybe non traditional stuff like the fractional stuff or direct consulting stuff. Direct consulting is a little tougher because you got to source your business. Fractional is a little bit better because some expert or set of experts are out there doing the sales kind of aspect.

[00:26:37] Ron Laneve: No, that’s fantastic. And I couldn’t have said it better myself. And it’s funny. It, I have these conversations with people multiple times a week. Oh, I applied to this job and there’s 800 people that apply to it. And I didn’t hear back. To your point, did you find that person on LinkedIn and reach out to them? What have you done to be any different a brand building perspective? Another.

[00:26:55] Entrepreneurial leader in town, another guy named Brad who’s a pretty good expert at interviewing taught me a question a long time ago. And it’s, and we love to ask people, what is your brand? And it always sets people back. They don’t think about that. And I ask that to CFOs, I ask that to CTOs, I ask that to people who aren’t sales and marketing people.

[00:27:12] They’re like, what do you mean? And I explained it to them. They’re like, wow. Never thought about it that way. I couldn’t agree with you more about your point about developing that Individual brand so thank you for that. This has been fascinating I really appreciate it and I can’t wait to share this with with my followers and And hope to continue to work with you on your enterprise consulting work.

[00:27:31] Bradley Reynolds: Thanks Ron. Keep building the brand!

September 27, 2023