Latest / Range Podcast / Why Starting with the Problem Drives Better AI Tools for Rewards Teams

Transcript

Why Starting with the Problem Drives Better AI Tools for Rewards Teams · Range Podcast

• Giac AI: This is the Range Podcast, where comp and Total Rewards leaders share what they're building with AI and how it's changing the work. In this episode, we're getting into what happens when a rewards leader starts with the problem, not the tool, and ends up with a custom AI agent his entire team uses every day. This one's for comp and total rewards leaders who are done waiting for IT to tell them it's okay to start. Giac: welcome to another episode ⁓ of the Range Ryan ⁓ a director of toll rewards and people operations at Admentum ⁓ he's been around for 15 across tech retail and services He is known for his behavioral economics approach, to reward design. And he's AI builder designs custom agents for his ⁓ HR team with zero development In his own words, problem first, tool second. Ryan, welcome to the show. Ryan Buhrke: Thank you. I am thrilled, Jack, to ⁓ be joining your podcasts here for all the rangers. gonna coin that term r rangers, folks that ⁓ wanna hop on ⁓ for the ride. and ⁓ I am thrilled. I am also very caffeinated, so ⁓ buckle in my friend. it's it in the morning here in the US and I realize you're probably on ⁓ the kind of the the end of your day there there across the pond but ⁓ we're we're gonna have some fun today. Giac: Absolutely. Now diving deeper into your music taste, Ryan, if there was ⁓ one song that really pumps you up, puts you in good mood, ⁓ I'm curious, what would that be? Ryan Buhrke: So this wouldn't necessarily be s something I would want as my theme song, like walking onto a stage or anything, but w walking on sunshine, you can't help but love that song. Like like you ⁓ you hear it, the it it starts with the drums and then like it you you can't not move to that song. ⁓ i well if you if you're not moving you are you're either asleep or you're or you're permanently asleep. Giac: I'm wondering, you three kids, you got a ⁓ a a wife, you got mother in law that lives with you, where do you find w how did not just where do you find the time, but how did you come across AI? Like how did you how does did this journey start? Ryan Buhrke: Yeah. so ⁓ am self-taught. th there is no no one ⁓ out there that that is is gonna e equip you for all this and I was really inspired a year ago. So I went to the World at Work conference here in the US, it was in Orlando, Flor Florida, and as part of the other national co conference ⁓ there was a done p panel folks using AI, what's next for AI and One of the the ⁓ presenters was an AJ BP from a large pharmaceutical company and they were telling us about the their GPT that they made at that time that helped them with their their exercise routine. They would take pictures of their food and their GPT would tell them how many calories, protein and so on, and and would log it all into a spreadsheet. And I thought, well, that's kind of a gratuitous use of AI, but and honestly, how hard could it be? So I came back from that conference and I'm like, okay, well, I'm I'm gonna build something, but I'm gonna build something not maybe not gratuitous to use. So the company I was at that at that time, one of the ch challenges we had was we didn't have job descriptions everywhere. So one of the ways that we kind of I kind of meet the business where they're at is well, I made a GPT that in a conversational way, using words, walk leaders through how to write a job description. So I I built into the back end Giac: Sure. Ryan Buhrke: ⁓ write a job description it was not just enter this into the template it was tell me your job. of the examples ⁓ was we had a a leader that had eighty a task of eighty t things. This is what it is. And I said, well just take your list and and put it into the GPT. I didn't know what would happen, frankly, and but what happened surprised me. Giac: Mm-hmm. Ryan Buhrke: Is the the tool took all of the items and indexed them and then using the large language found market benchmarks from each of these surveys, but then not just gave the leader the benchmarks. It that was behind the scenes. And what the leader saw was here is a JD that resonates back to my list of 80 things. And then here, like it walked them through so how much discretion, how much independence is there? And The tool really amplified what the leader was doing. No one wants to write job descriptions, right? So it was I think they it was spending less time at the keyboard and more time ⁓ thinking about what types of jobs do I need in in my team and organization. That's where ⁓ I got really surprised and jazzed about what these tools can do. Giac: Yeah. an excellent way start. you looked at you people were using AI, you thought there must be a more relevant way to use it in the Tory word space and job descriptions are probably a really safe place where you can start experimenting, right? 'Cause you're not necessarily dealing with any personal unidentifiable data and you're ⁓ tackling ⁓ a clear need. ⁓ Right, no one two point no one wants to write job descriptions. I mean there are a few that love writing job descriptions, but they're very rare. Ryan Buhrke: You you know, we all need to understand our our lane in life, our our s our skill set and and ⁓ when I started with this, started with what's the problem I have and then came up with a tool to fix the problem as opposed to thinking, what can I do with AI? It's like like I looked at so what's something I could solve with AI and the end of the day what what was really cool about this ⁓ this ⁓ GPT th again it was so a year ago, twenty twenty five, like ⁓ it Amplify the manager's domain expertise. So the manager knew the specific like e-commerce roles that they have, the specific benefits or bes ⁓ specific manufacturing roles, they know what they want them to do. How can we help them articulate it and bring it to life through just ⁓ common natural language as opposed to helping them or or doing an interview with them and then us try and write it like Giac: Mm-hmm. Ryan Buhrke: it it it removes the middle person, but it also it directly meets folks where they're at to amplify the ⁓ other domain expertise. Giac: Gotcha. And and and looking back, Ryan, do you think this I mean, you were a rewards leader a few years ago, ⁓ you are a rewards leader that now that is also AI enabled. How does it feel like? What what it what is it how does it change your day to day in the good or in the bad? Like Tell us a little bit more about how it feels to be an AI enabled leader, what it means for you. Ryan Buhrke: ⁓ w we are living in an exciting time. am thrilled that that we have the tools today that we do. it couldn't do my my current role across all the domains I'm responsible for from comp to Ben to HRIS to HR operations, HR compliance, payroll, all that fits underneath my umbrella. I have a team, by the way. ⁓ it's not just one person, but I also have my custom agent Giac: Mm-hmm. Ryan Buhrke: As an additional team member to help with the lift. And so I couldn't do what I do today without AI. But at the same time, it's not that I am abdicating and just trusting what the AI spits back. is all about, you know, trust but verify. So AI is like this bright-eyed, bushy-tailed intern. they want to do lots of things, they they can, but at the same time, you also need to to check the output. make sure that that working for for you. ⁓ and along the way as we think about here and in the in the reward space, this is our this is ARIA is not a tool that's just mine. I also have it shared with the rest of my team. So that we can all l ⁓ leverage the intern together while we all might have the same code each one of my team members has So ⁓ who Aria? She is my automated rewards innovation ally. So A-R-I-A. ⁓ I'm also a big Game of Thrones fan, and so like all this kind of just l locked in for me. But everyone on my team uses this tool differently because we personalize it. what is personalizing? It's not saying Giac: Uh-huh. That makes sense. Ryan Buhrke: hi, I'm Ryan. I have three kids ⁓ and and I I help with ⁓ with Mother's Day. It it gets back to thinking what are my goals? Wha who I interface with? What what types of are ongoing? And it's kind of like a little bit of a chief of staff, also a little bit like an also a little bit like an analyst and analyze files or move files around. it Giac: Ha ha Ryan Buhrke: All of us use the same set of code and skills. At this point I think we have about twenty skills built from making just a job description to market pricing to analyzing to moving files to creating dashboards. but what I I love is that my team is also making skills too. So the the so it Giac: Yes. Ryan Buhrke: For what we're talking about with skills. So that And so we have an enterprise from that perspective. And so for folks that don't don't even know what a skill is, ⁓ let me just kind of anchor us here just a little bit. So we have within Copilot, within Copilot, we have agents. ⁓ And copilot agents ⁓ can ⁓ can do different things. ⁓ you can make your own custom agent. ⁓ if you have Giac: Please. Ryan Buhrke: Copilot studio, you can then even do do bigger things with your agents. Then within the open AI or chat GPT area, they have GPTs. So those ⁓ are kind like another agent that you can ⁓ build a purpose. It can do different things. So that's a year ago where I was really starting to learn was with Chat GPT and building a GPT that lived with in OpenAI, but then Anthropic or Claude is another big one that's out there. And then so Claude has a number of different ways that you can work with it, but Claude also calls them agents, kind like copilot, and then ⁓ Gemini another version that they and so I'm not gonna go through all of them in the interest of time, ⁓ but you know, they ⁓ there there are different ways that you can personalize AI to the work that you're doing in rewards. but but now ask me about privacy. Giac: Mm-hmm. What about privacy, Ryan? Ryan Buhrke: I'm so glad you asked. so the I like to use the eyeball rule where if you can see it with your eyeballs, so can AI. So if you're asking AI to open up a file to tell you what's in it, well at that point like like everything that's in that file is accessible through the AI. But if you ask, for example, AI to move a bunch of files. Can I show you a really dumb example? I'm gonna sh I'll share my screen if that's okay. With one of the ⁓ the dumb things. Alright. look out. Buckle in. Whoo! Giac: The stage is yours. We love some action on a podcast about AI and Tory Rewards We always love some action, so bring it on. Ryan Buhrke: Alright. So this is something that I shared on stage at the World at Work conference this year where ⁓ did ⁓ on stage unscripted a debate. and then the audience gave me questions to give back to my agents and also recently I went to one of ⁓ ⁓ local business schools here called Carlson ⁓ college in the US and ⁓ professor also asked ⁓ a question from the final exam. I was a little bit nervous. Arya passed, but but I'm gonna show you one of the dumb things here. So this is the dumb thing. we need to have them all added to one folder. Okay. Giac: Nightmare. Ryan Buhrke: So we're talking like a hundred forty plus different files. They were all saved within different folders. on the left side you see this black screen of death. This is my Claude Code interface. Right. So Giac: Disaster. Ryan Buhrke: I'll just say this. There's a higher learning curve when it comes to Claude Code, but the ceiling is limitless. So within Claude, there's Claude AI, which goes through your browser, you ask it a question, it gives you questions back. Then there's Claude Cowork and desktop that is similar to Claude Code, but and can work with files on your machine, but has a nicer interface. But then there is ⁓ and one of the nice things about Claude. Giac: Sky's the limit. Indeed. Ryan Buhrke: is is that you can set up projects to share with your team that each of you can work within. Then there's clawed code that you see here. clawed code, again a little bit of a steeper l learning curve, but this is what all the developers, all the folks in IT, when you hear Claude code and and you're gonna take it from my cold dead hands, this is mostly what they're using. And this is where I where I built ARIA into here. So this is my request to ARIA. This is the T up here. So For these three years, I need the payroll files. then there's gonna be, you know, I want you to they have all the same file names, but they're in in folders by years. I want you to pull them all together. ⁓ and by the way, we changed HRIS systems in and in 2025. So there's gonna be different file names. This is what it is between the two. And so I'm just gonna, I'm not gonna play the whole video here, but so on the right side, you'll see here's an example one, the folders, here's the Giac: Mm. Ryan Buhrke: the pre check detail the payment register but we need to bring that into a centralized folder and so here I'll just kind of scroll through there's all these by all these years and then so I ask Aria to go through and so she starts writing a script ⁓ and it explores folders and then she ran to an error then I then rewrote the code to find things okay here's the what she found initially ⁓ and she asked me she does anything anything you won't Do you want me to go ahead and and make the copy? Well, I actually have some other context for her that, hey, make sure we know which ones are off-cycle versus regular. So add this in there. ⁓ and don't rename all the files the same. So moving right along, now she starts writing the actual Python script. I use Python every day. Yeah. Giac: Yeah, I was about to ask you Ryan, like it the clock code or ARIA caught a an error in the code, so it it started troubleshooting on its own. How important is it for a comp person to actually understand that line of code? Like is it is it something you pay attention at all? Or is it Ryan Buhrke: So I pay attention to the output. did what asked my tool to do, did it actually happen? And but also have it check itself along the way and audit. So as we saw here, first she went, Aria went and found, you know, where all the files were. But then she before she did anything, she came and asked me, do you want make any changes? So this is an example of Giac: Mm-hmm. Ryan Buhrke: Not just human in the loop. So Claude Co. will ask the human, Are you okay? Are you okay or okay? and most people hit the one button or the two button just to keep going through. But in this case, this is an example where it's humans deciding. So she pulled this stuff together. This is what she found. But before anything happened, I the initial dry run. I validated it, and then here at the end, and just Seven words here, go ahead and execute the copy. So if as we see over here to the right, now this is the payoff. So I'm just gonna scroll through. It's gonna run the code and bam. So on the right side, you you can see all of the files that were just copied over, all 140 and so on, like like this. This was the payoff. And ask me how long did all this take? So so so even ⁓ Giac: Exactly. Right. So 'cause I look, I I think in many people's heads when when we talk about using AI in comp, they're thinking, like these folks are building ⁓ end to end, a new end to end compensation platform replacing all the vendors at once, all the pay surveys in a couple of minutes or maybe in a few days. I mean, cool if you wanna run with that and try it, test it out, but really ⁓ ⁓ Dealing with here a tedious, time-consuming that you could have otherwise done in days, if weeks, because you've changed your HRIS provider. so just think about the amount of time required, not just to retrieve all the files, but then find like amalgamate them together, find like a consistent template to do the analysis. Whereas ARIA did it in long? How much time? Ryan Buhrke: Seven minutes. Giac: Seven minutes the new record. Ryan Buhrke: So and but but no, this was just the version I recorded. And the version in reality, when we went through this, it was me, my payroll analyst. had this request, I'm like, how are we gonna figure this out? It it took us about 20 minutes because we we iterated a little bit more and there were actual files missing. So as our went through and checked the folders, we're missing ⁓ these from one or or in this cycle, had multiple. Final version one, final version two, final version three. Right? And so ⁓ w and actuality. ⁓ it took a little bit longer, but ⁓ I'm using air quotes here. It would take in my analyst at least a day of just mindless clicking, bring it over here, right click, rename. Now we could maybe have written a script if we were in IT, but again, w we aren't techie. Like I I don't know how to write ⁓ PowerShell in Python, but like the ⁓ Giac: Yeah. What's that? Ryan Buhrke: The ⁓ this is the kind of the ⁓ the use case of you know how can we spend less time at the keyboard doing my numbing things. This is an important ask we had to deliver, but we were using a tool to help us get there that also self-aut along the way. Giac: Mm-hmm. Ryan Buhrke: and the file paths, the contents of all the the private employee information in the actual payroll register. So none of the banking information, none of the employee name, mailing address, all that. The ⁓ this example, this is an example of how we can think about using a tool like this, but also maintaining privacy. Again, f ⁓ going back to my eyeball rule, I Giac: Right. Ryan Buhrke: In this eyeball rule, all I saw with the the folder paths and the file names. so as we balance between privacy and being able to do what what what we need to do in an efficient way, one thing I found ⁓ super helpful is I have good relationships with my IT folks that ⁓ I I ch check in with friends over in infosecurity, ⁓ over over in our cloud area, Giac: Mm-hmm. Ryan Buhrke: just so that they're aware of the kinds of stuff that we're doing. Cause everybody is on a continuum right now of learning. the the goal here really is to to bring friends and colleagues along for the ride as look to use these tools. Cause all of this is new, ev even for folks in IT. And if think about from a change management lesson. So I'm gonna bring my behavioral psychology into here a little bit. and and ⁓ we, you Giac: Yeah. Love it. Ryan Buhrke: think about change management, we need to bring folks along for the ride so that the change doesn't feel like it's being done to people, so that it's not initiating that fight or flight response. But but that we are bringing folks along for the rides are amplifying what we are doing but ⁓ but at the end but humans are still deciding what happens. So it's not human in the loop, but humans are deciding. Giac: Yeah. Yeah, so real. And you said that your team, you know, it it it it is adding on ARIA, it's adding new skills, adding new features. One of the questions I had for you is like, you know how one of the key questions you get from reward folks, okay, you introduce a new tool, but what about like who's gonna maintain it? And what does it mean ⁓ maintain it? Does it does it create new workload? Does it does it actually Ryan Buhrke: I mean it. Giac: You know, how is there is there anything there that can say about where the implications are? We we get the time savings. You you've saved days on job that you know you've Arya d has done in seven minutes. But what about like who's maintaining ARIA? If it's if it's everyone, what are the implications having like that decentralized model to maintenance? Ryan Buhrke: Mm-hmm. Giac: Or does it maintain itself? Hmm. Ryan Buhrke: So one of Yeah, yeah. So one of the things that was toying around with early on is as I was building R she said, Well, I could have a shared consciousness that where I could live in a space between everyone's machines. And I'm like, ⁓ I don't know if I'm ready. ⁓ I've seen movie before, w where in theory I could have put all of her files, all of her skills in a shared location and then have everybody ⁓ her locally, but then she would be thinking across all of our machines. I wasn't quite ready for that. So but as we look at how do we main maintain this right now I've I've been the main maintainer where we basically share skills we've built. So every week I sit down ⁓ have a huddle with my team. Giac: Mm-hmm. Ryan Buhrke: Let's talk about AI. What have we done with this week with AI? so that where I am bringing folks on my team along for the ride, because not all of them are builders, not all of them are super jazz, but but as we look at individual use cases, like look at all these files we just moved. Or their cases, hey, I made ⁓ a a skill that can identify the job level for a job description. Cool, right? but As we kind of figure out how do we maintain this, I don't know yet. I'm gonna be honest. I don't have all the answers. I don't think anybody truly does. but I am l and these of cut custom agents ⁓ like didn't three, four months ago. And it one I know is I didn't want to have the shared consciousness thing. That would that was a step too far for me. but as we we sh Giac: Right. Ryan Buhrke: we have a shared location where we if someone makes a new skill, we go ahead and throw it out there. But ⁓ but some of our skills are tailored just to us. Like I have a skill that's just Ryan's voice. I am the voice of Ryan Berkey. Ryan likes to go for long walks in the beach. Mm not really, but Giac: Mm-hmm. Well, aren't you afraid of people impersonating you? Like if they have access to that skill and you know Ryan Buhrke: it if they can get to my hard drive and they can get to it, sure. God bless ⁓ but but am I am I afraid of them impersonating me? Not any more than than anybody else kind of can ⁓ try and impersonate or spoof somebody else, right? At the end of the day, it's about being the real you, but also not abdicating. Like I don't have Arya write and send emails on my behalf. She can triage my inbox all day long. and and and outlook, but she doesn't ⁓ write messages and send and and reply to correspondence. It was a ⁓ so it kind of gets back to where do you have your own personal boundaries with tech and and and how you use it. I think you know everyone thinks the hard part is learning the tool. It's not. The hard part is knowing what to build. So thinking about what is it that what's the problem I want to solve and how can I bring a tool, build something to fill the gap. And in the in the case of of RA, you can even just do it with just generic code. you know, but there wasn't anything big that I built. I just described what I want in English. So as we think about, you know, access to these tools, there's this term called radical agency. radical c candor, you're candid. But but but where I am I am kind of ⁓ pivoting a little bit is radical agency where AI has collapse the barrier between idea and reality. You don't need a development team, you don't need the specialized knowledge. You should bring your IT friends along for the ride, but you don't have to ask for permission to tr try and build something. Whether you're building it with copilot, you're you're you're making your own first agent there, ⁓ or you are a at an a a Chat GPT shop, an open AI shop, ⁓ at the end of the day, it's just going out there and trying because you don't have to get permission to do it anymore. I mean you need to make sure that that you're not that you're having good data governance in place. But but ⁓ right c we're only limited by what we can imagine. So as we think, you know, the door's open, we can walk through it. No one's here to tell us no. I mean I mean No one really wants to be told no at the end of the day. ⁓ but but we're we're limited to what we can envision. for for ⁓ for a lot of us, it's it's limitless. Like like if you can envision it, you can build it. But we also need to make sure that we don't g give up what makes us tick. What makes us h human. We shouldn't i abdicate our thought process. So can I tell you ⁓ a thing I did with AI? This is probably the dumbest thing I've ever done. I'm Giac: Mm-hmm. I think we all want to hear it now, Ryan Buhrke: See this? Like I'm bearing the lead. I'm s am I selling it enough here? ⁓ so in w where I'm in the US in Minnesota, ⁓ I was pl planning a trip to go to the Wisconsin Dells. And this is end December, and I had pulled up GPT and I was using my on my pr pro account to model out okay, so where is the train? When's it gonna come in? Where's it coming from? Are there any w ⁓ weather delays? I had built matrices, I had multiple instances and dashboards coming up, and I was like, okay, we need to get to their Dells by this time, but because we want to get there for reservation, so should I Uber from here or there? And I I had spent the whole evening just trying to map all this out, and I was just sitting there waiting for the next response from AI. And my wife walks into the room and she asks me, What are doing? I'm I'm planning the trip. We're getting the trip. Giac: Hm. Ryan Buhrke: And and she sees all my screens open and she just sits down on the couch and two minutes later she just shows me her phone. Here's the answer. Just buy the tickets. I was fe I felt a little bit accused in that moment. I thought I was doing everything right that I ⁓ was maximizing ⁓ but what I was actually doing was I was ⁓ my thought process. to AI. ⁓ You like you're a super user. You think you're doing everything right, but at the end of the day Yes. It sounds like you ran into this Jack. Giac: Yeah. Yes, the perception. ⁓ every day. Like it's a constant fight, Ryan, honestly. ⁓ and the and the context switching, I think there's gonna be studies ten years from now that show the damage we're doing to our brain. is really important to stay like d to be able to stay focused on one thing, ⁓ and and know what you're doing and without delegating too much, 'cause yeah, that that that's a bit of the like the natural instinct we get, right? you said that imagination is the genuine requirement. You know, it's knowing that learning the tools fine. Like there's always ⁓ a little bit of that. The can teach you, but it's ⁓ knowing what you want to do the tool. I think that's the key message, right? if we if we look ahead, ⁓ know, if you can think about a genuine Ryan Buhrke: The tool can teach you. Giac: Opportunity you see in the total rewards domain or even ⁓ just the frustration you have with how things have been done, dealt with in the past, you think there's a real opportunity now to change and to move from old ways to newer ways, what would that be? Like where where in other words, what what do you want to build next? Where does your ⁓ is your imagination taking you? Ryan Buhrke: So it it really gets back to what's the problem you're s you're solving for. And I want to just s circle back quickly about kind of abdicating, because every tool changes you. We used to print out map quest maps. back back in the old days of the internet to ⁓ to get from point A to point B. Now we use the ⁓ these ⁓ these these magic screens in our pockets, phones, GPS to get us there. that That tool gets us there faster. But if if if we needed to if our phone stopped working, we need to get back to where we were, could we do it? Yeah. Would it be as efficient? No. every ch changes you. But but what's exciting is that we get to choose how it changes us. So it's not that that we have all this context kind of s switching is gonna make us dumber. AI is not gonna make us dumber. Well it it will if if we abdicate our critical thinking and discernment to it. ⁓ exactly. J just because you have a piano doesn't mean you're a musician. just because you have a set of sculptor tools, right, the more you use those tools, you're gonna get some calluses on your hands. Every tool shapes you. We we don't use map quest anymore. well might be somebody out there. ⁓ i if you do, good on you for using map quest. but as we think about, you know Giac: Yeah. If you allow it to Mm-hmm. Ryan Buhrke: w what we can imagine. what I'm imagining n next par part of it is thinking about what are some of the things or or challenges that I have as as have been ⁓ using Aria for the last four months. I have a n number of different meet meetings that she has had notes for me on for over the last four four months and ⁓ one thing that I'm working on is ⁓ a historian skill. where she basically is gonna be compiling up ⁓ an ongoing notebook of all the stuff I've worked on, indexable, so that I can search through it and if am getting ready for a meeting, she can pull up a dossier of here's all the things associated with this and and potentially ⁓ that I might want to consider as as I go into this meeting. And so ⁓ it's still something I am I'm building, but it's it's thinking like Giac: No way. Ryan Buhrke: Okay, I have all this stuff. What can I do with it? Not it's it's asking what w what if or what can we as opposed to what what sh what what are we only allowed to do? ⁓ yeah. Giac: Yeah. I used to used to have a diary when I was a young kid. I used to write whatever was in my mind and learn more about me. And ⁓ I stopped writing my diary more than twenty years ago. But ⁓ one of the things I use AI for is quite similar to what you described there, is to populating story bank. So as I continue, ⁓ you going through my living living life essentially. I'm gonna be thirty-six years old tomorrow. So I'm starting to have a few more stories. Thank you. every transcript that exists in my files, everything I said about myself, my career path, my story, my ⁓ interests, passions, Claude goes in there, ⁓ extracts and adds it to my story bank. Ryan Buhrke: Happy birthday. Giac: And it's quite powerful because you can do so many things. ⁓ I'm not playing on writing a book, but as you know, we get we we get a lot of content out on LinkedIn. And the way to make it feel yours is if you actually open up and share more about yourself. Because any AI can write a a a a post. It's only if you include those personal traits and stories that that's the moment when the content becomes authentically yours. ⁓ so that that's how I use it, but I can envisage one day maybe agent, story bank agent, talking with your story bank agent ⁓ writing book together. Or something else, like whatever they are able to imagine. Ryan Buhrke: I I'm sure it'll be a comedy. It'd be a comedy of errors. Giac: It's gonna be like dark ⁓ stand up show ⁓ comedy show, I think. It's gonna be more like that kinda that kinda thing that you cannot like you cannot delete from your memory. but the say you know, but at the same time you're you're you're amused. so yeah, that's what I imagine. That's what I imagine. Ryan Buhrke: You can't look away. well ⁓ Yeah. Yeah. And yeah, that that is i you know, wha what as we look into the f future, what what what I also envision is that we're gonna everyone's gonna have their own bespoke agent that is their that knows their voice, that they kinda take with them, that kind of is as part of their their C V. We'll see what happens. ⁓ I'm saying this now ⁓ in twenty twenty six when I listen to this again and our agents are are making the the ⁓ comedy book to be like Ryan said this, was he wrong or or we'll ⁓ we'll see what happens. But I I envision folks having their own custom agent that they take with them, like their C V that is is some ⁓ skills taxed so on, like like today folks know like that if you're living in NXL you kind of know like your go to for formulas or your like like like this is a chart I spent hours making I I take and rinse and repeat this for for other reward cycles. So I guess the ⁓ this is kind of the the Ryan Berkey framework as it were for for communicating pa pay and performance. other kind of have these today kind of in N Excel templates as it were, but n Now it's not gonna just be an Excel t ⁓ template, but it's gonna be your own agent that's gonna gonna follow you and and grow and get better as a a thought partner, ⁓ someone that's going to replace you. Again, it's it's humans ⁓ AI together, not AI replacing humans. Giac: We're building tools for humans. So I mean, yes, no one knows what can happen in the future. You know, there are different forces in the labor market. There's not just AI. But what we know for sure is that Arya wasn't built to replace your analyst. It's actually a tool you've built for your analysts in your team. And you're we could say like augmenting or amplify I think you prefer the verb amplify. Ryan Buhrke: Yeah. Amplifying. Yeah. Make it better. Giac: Amplifying them, right? Yeah. It's about you know increasing our productivity, but mostly it's also about you know, going down to why our function exists, the employee experience in the company, the manager experience, and improving the allocation of resources in the company. So that's a win win situation. Ryan Buhrke: And you still need to know stuff, right? ⁓ you still need to have through your your own personal struggle bus. Because more you struggle, the more you build roadways into your brain. There's been MIT studies that have shown that kids that were just given Google and k ⁓ kids were given an ⁓ AI help them write a paper, the AI papers were polished, pristine, they were great, there was A-level work. Whereas the the other students that just use Go Google weren't as great. But but what they found when they asked the students later on about the content of those papers, the the kids that used g Google, their brain scans lit up. Whereas the kids that use the use AI, their brain scans did not not light up. And so this kind of gets to the point of ⁓ still need credentials. You still need to know and have a certain body of knowledge in in order to Giac: Mm-hmm. Ryan Buhrke: you know, discern the information coming out from AI. Is it is it AI slop or is it work slop? I I like thinking about like I like work slop, where it's not about if you're take it and you're gonna use it, you're not putting your name on it, and and it's up to you to n know what's behind it. And and that's where like education, certifications, credentials comes into play because you still need to have that ⁓ background in order to stress test what's coming out from AI because if it looks very polished and and AI is super confident, that's the time when you should super push back. th the only way that that you know to push back is if you have the the credentials, you've gone through schooling. It's not that you necessarily need to have gone to Harvard. You could go to a regular university but but it's you know it Giac: Yeah. Ryan Buhrke: It used to be about hiring the smartest person in the room. It's no longer about that. It's about hiring the person that has the the vision for their future, but that vision com coupled with discernment, be able 'cause 'cause not everyone should be I'll be hiring artists without discernment. We shouldn't hire critics without imagination either. Giac: Right. Right. So going back to your previous you said ⁓ is what I got wrong with AI. What's your what's your vision for your next vacation ⁓ ⁓ you ⁓ you gonna ⁓ your wife you're not gonna use AI to plan it? Ryan Buhrke: No. I I am still gonna use AI, but I'm not gonna just sit there and wait for AI to make the decision. I'm using AI as an it an information ⁓ potential options opposed to waiting for it to make the decision for me. And and and that's where I found myself kind of abdicating was all right, this is the one thing, I'm just gonna let it optimize and and and let me know. Well, I'm still using AI, but I'm also deciding what's going to be happening. So having that kind of watershed moment, that re self-realization that am am to make make my own decision because the this kind of gets to my Captain Picard moment. So I'm a nerd. ⁓ I l Star Trek. And you know like to use the analogy of Captain Picard on the Enterprise. He has all of his officers, he's a science officer, his weapons officer, engineering, his communications. Well, you know, here's a ⁓ here's a scenario. Aliens are coming, they're gonna gonna start sh shooting at us, but we need to react, we need to do something back. So all of the AI are telling Captain Picard, we you need to do this. What does Picard do? He sits back in his chair, sips his Earl Grey tea, not even coffee, just the Earl Grey tea. And He meanwhile the AIs are all t now telling him you gotta do this, you gotta do this, you gotta do this. He sits back. what ends up is that ⁓ no, this was a commu a computer hallucination. It was a simulation. If he had actually fired the the weapons and in response, he would have caused World War Galactic War, whatever it is. and so ⁓ in this case, like we need to be, you know, we need to discern what's coming out from AI, but we need to be courageous. To make the call, the models won't. At the end of the day, AI won't ever care about humans. I mean, I mean, ChatGPT will definitely want to ⁓ try and be your friend and all. but at the end of the day, like the the human connection to what the decision is and how it impacts others. a AI is great about optimizing options and situations, but can't care at the end of the day. ⁓ And we to be courageous. And have the guts to make the call that the models won't. So like we have access today. We if you can envision it, you can do it. But we need to stay sharp while we're doing it. Like like not give up our thought process. We need to judge what's coming out from it, but then be human. We need to have the guts to act on on what we believe. ⁓ leaders, we have been in the room for five, ten, fifteen, twenty years. We have earned the place in that room. Be not because of how we've used AI, but but by how we have shown up to leaders. We have that cr credibility. It's that gut feeling you get that that makes us all hu human. It's also that gut feeling that Captain Picard had as he was sitting with his chemile tea. He knew better. He didn't know why, but but he he knew better. And and it's important for us to recognize and realize that AI is here. It's it's it's it's not going anywhere. We ne Giac: Mm-hmm. Yeah. It's gonna stay for a while. Ryan Buhrke: We need to use it, but w we also need to know when we just don't have to follow it blindly. 'Cause at the end of the day that that's what do do the thing the models won't predict. Sorry, Skynet, not sorry. Giac: That's a perfect that's a perfect note to close the podcast episode, Ryan. Thank you for walking us through your philosophy, how you your story and how you started, Thank you for at podcast we wish that other leaders get inspired from your story and can start building cool tools as well. Without forgetting about applying their judgment and trusting their guts. Ryan Buhrke: Thank you, Jack. This been fun.