Strategies for the Future of Work with Toby Phillippe

s1e26 Strategies for the Future of Work with Toby Phillippe

"Something Big Is Happening" — AI: Fear, Opportunity & Your Career
The Wired Garage With Pops | Hosts: Brian ("Pops"), Steele & Toby

The crew reacts to Matt Schumer's viral article "Something Big Is Happening," dissecting AI's real-world impact through the lens of IT professionals who've lived through every major tech wave — from CNC machines to cloud to containers. The episode runs in two halves: Fear and Opportunity, with raw, honest stories from the trenches.

Part 1 – Fear: The hosts tackle the uncomfortable reality that AI can now do in seconds what used to take skilled workers hours. They discuss job displacement, government unpreparedness, AI security risks (cyberattacks on water/power grids), prompt injection vulnerabilities, and the danger of blind trust in AI output. The concern isn't the technology itself — it's people using it as a crutch without critical thinking.

Part 2 – Opportunity: The tone shifts to what excites them most — eliminating "zombie work" (repetitive, low-value tasks) so IT professionals can focus on what humans do best: relationships, trust, accountability, and innovation. Real examples include ServiceNow's BuildAgent, AI-powered ticket routing, and using AI as a "round table of nine experts" to challenge and sharpen your thinking.
The episode closes on an optimistic note: be the giraffe, not the ostrich. AI is coming either way — the question is whether you'll adapt or get left behind.

Something Big Is Happening by Matt Shumer, Feb 9, 2026
https://shumer.dev/something-big-is-happening 

✅ KEY TAKEAWAYS

• AI is already here — and faster than most realize. Schumer's core argument: this isn't a future problem. It's a now problem.
• Stop using AI as a smarter Google. Treat it like a round table of domain experts — challenge it, argue with it, push back.
• The "Brian vs. AI" trap. Employers who cut skilled staff to save money will quickly discover that the human judgment, context, and accountability don't transfer.
• Zombie work is the biggest opportunity. Offloading repetitive, low-value tasks frees teams to innovate. That's where the real ROI is.
• Critical thinking is the new superpower. The better your input, the better your AI output. Garbage in, garbage out — but brilliant in, brilliant out.
• The two emerging trends: Technology will manage technology. Humans will get better at managing humans — empathy, trust, and relationships become the premium skill set.
• AI is not one-size-fits-all. Know when to use it, when to review it, and when to trust a human instead.
• Upskill now or fall behind. Like the machinist who learned to program the CNC machine, the goal is to evolve with the tool — not resist it.
• You're still the 10th person at the table. AI gives you nine-tenths of the answer. Your judgment, experience, and context complete it.
• Be the giraffe. Head up, eyes open, long view — not the ostrich with its head in the sand.

🔑 KEYWORDS / TAGS
AI and jobs, Matt Schumer Something Big Is Happening, AI fear and opportunity, artificial intelligence career, future of work AI, AI replacing jobs, IT career advice, AI in the workplace, AI upskilling, technology and employment, ServiceNow AI, AI automation IT, zombie work automation, AI critical thinking, ChatGPT vs Claude, AI prompt engineering, AI job displacement, generative AI for IT professionals

#ArtificialIntelligence #AIJobs #FutureOfWork #ITCareers #AIAutomation #TechPodcast #GenAI #UpskillWithAI #ServiceNow #CriticalThinking #AIOpportunity #WiredGarage #AIFear #ZombieWork #BeTheGiraffe

Transcript

SPEAKER_01 0:00

Steel, like it can help you be that, uh, help you be that trusted advisor by helping you strategize, right? Don't think of it as uh an executive assistant or an eager, you know, all a never tiresome uh intern. Think about it as a round table full of experts. Okay, we've solved the problem of you know auto-adjudicating tickets that come in first pass to service now, right? We've offloaded that to an agent, it gets it right 99% of the time. Now, AI genius, help me figure out how to run a better service desk. How do I, you know, how do I build this great thing that I've always wanted to build and never had time? Challenge me on that. Let's talk about that for a while. Let's strategize around that.

SPEAKER_03 1:35

So this is the fear part. We're gonna we're gonna look at this as a fear and opportunity. So the first half of this will do fear, second half will do opportunity. So in this first part of fear, this is this this theme is like this already happened to us in technology. So Matt says in his article, I am no longer needed for the actual technical work of my job. When did you would you guys say you felt a task you were good at was suddenly better done by AI?

SPEAKER_01 2:01

I'll say that I don't think that's happened for me personally yet. I will say that I've used it in my work to do things that have surprised and amazed me. And it's not that I couldn't have done it, but it saved me a ton of time. I'm, you know, that that was kind of, you know, eye-opening the first few times that I did that. So it wasn't like, you know, it could it could replace me, but if I'm looking at it from a from a employer to employee standpoint, I'm thinking, well, you know, I don't have to pay Toby to do that thing that would have taken him 40 hours because you know, he figured out how to do it with AI in 30 seconds or three minutes, right? And that's a yeah.

SPEAKER_03 2:45

I think the rush to judgment is what you're scared of, right? You're we're we're scared of businesses, people looking at spreadsheets. You know, we've always had this issue, right? Where they look at the spreadsheet only and and rank an employee according to the spreadsheet, you know, the numbers that way, not really what they've they probably done personally or as part of a team or as a solution. And I think to hear, wait a minute, you know, I can do X. I'll get rid of Brian. That rush to it when they because what they'll find out is, wait a minute, that's not working as well as Brian did. And now I still need someone else to bring it along to adapt, to adjust, and they make them they make a mistake, but you're well gone. You know what I mean? So I think Kalabath's scared to me is the rush of judgment of people just jumping on it as a new shiny thing and think it's the miracle cure, and there never is one.

SPEAKER_00 3:32

I think the in certain areas, it's helped me prototype things. It's helped me kind of see the art of the possible sooner and without having to ask maybe three or four different people, hey, could you do this or this or see this? I can dig in and do more so that I can share more. I can have an opinion and a stance that is a little bit better informed. I think to the example that you just use, Brian, and and kind of add to it, I can type in some kind of goal or spec, ask it to do something. How do I know if that's right? Am I relying on the wisdom of the model? Who is actually gonna review to make sure that that thing is right? Because I can't hold it accountable. If that model does something wrong, or a prompt injection technique works, or the result that comes back looks right, but it isn't right, and that that wisdom isn't there to know the difference, that's gonna create problems. And depending on the level of sensitivity of the space, maybe it's illegal. Maybe it has to be something that is exactly correct. You're gonna want somebody to review that. I think they're got uh go ahead.

SPEAKER_03 4:47

Well, I use perplexity, I use claude, whatever. Do you ever argue with your AI?

SPEAKER_00 4:53

I have I have said no, that's not right. Try again before you.

SPEAKER_03 4:57

I think you should because it's learning, right? Because the more I use it in the context of like I use perplexity for the podcast here, and it has learned what I'm looking for. It's learned your name, it's learned my name, it's learned just different things that we can provide along the way. So if it's wrong, you need to say that is incorrect. I need blah, blah, blah, blah, blah. It's it'll take that into consideration and learn it for the next answer. That's how it grew is by sifting the internet for information wrong or right. Like Wikipedia. Wikipedia always got laughed at because halftime. It can be wrong too, right? Because the way it's contributed to. So, but I think you should argue with AI. That's a good point. We shouldn't be afraid of it. Don't worry about it. It ain't gonna take your life over right away.

SPEAKER_01 5:42

You can argue with it. Well, okay, so there, this this gets to the heart of the Schumer article. And you started this talking about fear. Maybe we should dive a little deeper on this thing, right? I think the point he's trying to make is that in his opinion, this is already here. A, it's advancing quicker than the general population has realized. B, C, there's no turning back to clock. And D, it's coming for you. And and the U is kind of, and and how soon it's coming for you really kind of, I think depends on what line of work you're in. But sooner or later it's coming for you. And if you don't learn about it and figure out how to leverage it in the ways that Brian you just described and Steele you just described in terms of augmenting how you do things and helping you, then you know, you are going to lose, would be the unfriendly way of putting it. And I'll just ask you, do you think he's right?

SPEAKER_03 6:43

Oh, yeah, I I I think some of the things he's looking at is right. I don't get no, I I get I get worrisome about it. But I think some of these have I guess I've I'm old enough, I've seen the evolution of tooling. Uh all these tools that have hit us have exponentially had more effect. Like in a machinist world, the CNC machine, yeah, that was a world, you know, when everybody was doing bins and everything, calculating it by hand, and now all of a sudden you can program it and do a hundred of them exactly the same way. Now, before you always had a little bit of a quirk because the the the machinists didn't do it the exact same way every for a hundred of them. So that was happening. Then you got the internet, you've got all these different things. You got VM, we've got virtualization of servers, you got SaaS that's grown, just all these things. But AI, it's they've all been had an exponential, the cell phone, all an exponential effect on society. That's what kind of worries me. It's it's no, it's more changes are coming. I'm okay with change. I'm a change agent. I'm good with that. It's exponentially more change than I'm used to. I think is what I kind of worry about.

SPEAKER_01 7:47

So do you think it's gonna happen at a pace that's gonna outstrip the majority of the population's ability to keep pace with it? I think governments for sure.

SPEAKER_03 8:00

That's what scares me now, also is like we're having this. I'm reading about Claude is arguing redlining contract, you know, EULA contracts with the government over whether AI their AI can be used for unmanned attacks, you know? And then oh Chat GPT just signed a contract, so then everybody's wondering, okay, did you give into that? I mean, you everybody's just you know wondering. I think government's always been slow, but it's been a thing that it hasn't I mean, besides the missile crisis, I don't think it's really affected us a lot by government being slow. Yeah, our privacy's gone. These are big things, but these are things uh we we deal with. I think AI can vastly change things with smaller countries, smaller groups of people have a bigger say, I guess. I don't know. In a positive way, you're saying though, in those smaller positive positive or negative. I mean, you give it to North Korea or Venezuela, and they have a little bit more effect, you know, with doing things to our our systems, whether it be water systems, power systems, just things like that. I mean, we thought the viruses were bad, you know, when AI can outthink things, you know, and learn along the way and dodge and weave, you know, through these A V things. Um I don't know.

SPEAKER_00 9:16

Yeah, that that's I mean, the examples of of trying to shut it down and it blackmailing all experimental, but blackmailing the uh person who was shutting it down. Uh, I think there's a defined space where these tools should be used, where they should play in. We should also understand the limitations and and really make sure that those limitations are clear. I I talked about reasoning at one point and it right, it it is prediction. It might adjust, it might predict differently based on if you said no, that's wrong. Okay, well, it's gonna go back to its sources and find the next best answer. Kind of like we would. You know what? Something has told me, or my wisdom has told me something has showed me that this is not right. Strawberry uh only has it doesn't have one R, it's got two R's. No, no, that's still wrong. And I do worry about the security. I I think the the scale is the most impressive part. How fast it can crunch data specifically using GPUs. This is gonna be a really niche example back in uh probably the early 2000s. Um, there was this forensic suite called Backtrack. It's called Kali Linux now. And you could take a hash and bring it in there and crack that hash with tools that were available. One of those techniques was called rainbow tables, and it used your GPU back then to actually accelerate the cracking of that hash and that brute forcing versus just CPU cycles. It feels like AI is like rainbow tables, but for data, for knowledge, for information. It's using your GPU to crunch all that in a way we had never done it before or even thought about doing it. And we are seeing the results of that in a much more sophisticated way than if we just have the same old tech stack in the early 2000s. We we've already pre-optimized, it feels like. And it feels like there's still so much further we can go because essentially it feels like we're in the tape era. You have memory when memory context windows that you have to deal with. You're basically filling up a piece of tape and then gotta wipe it, start over with what your your latest goal is, and then keep going. I predict that goes away with within like a year or two. Everyone's talking about memory context windows now. No one will be talking about that. At some point in the future, that will go away. It will automatically be handled if it's still necessary. That will go away. That is unneeded complexity in AI that will go away just to keep things running. So I do fear scale. I do think that there we should always be aware of the limitation. We should, I do agree, you you should upskill, you should understand how to use the tool, you should understand when you should use the tool, understand limitations. I think they're Brian, to your point on the CNC, which was awesome. I don't want to kick it over you, Toby, to comment on this. You have these different points in time where you have innovation that allows us to be productive in different ways. Is it going to replace folks? If you were one of those folks doing the CNC and then the CNC machine comes in, maybe in that perspective, but what is that person doing now? They're programming the CNC machine, they're learning how to print a hundred at a time instead of doing one by one manually. That person who had to do that job built empathy. Maybe they're now an enterprise architect. I think there's a lot of variables, a lot of nuance. Fear can definitely be in the driver's seat, but we should also, I think there is opportunity out there that if we focus too much on the fear, we we won't see it, or at least it won't be as clear. But that is not to say we should ignore the risks because those risks are out there.

SPEAKER_01 13:12

Yeah, I think that's right. I think it's fear is, of course, first a very personal thing, right? You're thinking, uh-huh, is AI coming for my job, right? Not is this going to be a positive or negative net thing for society. I mean, maybe you're thinking about those things too, but primarily, right, I think people's fears are centered around whether or not this is gonna replace me or whether or not the thing I'm studying in college, if I come out in two or three years, is gonna be a thing that is even gonna be a job anymore, right? So you're having these personal fears. But you know, getting back to Schumer's article, one of the ways to at least mitigate that fear is to do something about it. You can't sit around and moan and complain and, you know, hope that the world doesn't change. That's never gonna happen, right? What are you gonna do to be the guy that comes out on the other side knowing how to program the CNC machine if you were the, you know, non-CNC machinist before or whatever that role was before? You've got to teach yourself, you've got to spend time practicing, you've got to find uses for it now and, you know, spend an hour a day, stop treating it like a smarter Google and start thinking about it differently, spend some time with it. That's uh, you know, I I don't think that's bad advice at all, right? Whether or not you're an entry-level coder whose job is probably very close to being, you know, uh eliminated or at least changed so drastically that, you know, it it's not what it was two or three years ago, right? Or somebody that thinks you've got more time on your hands, right? Maybe there's maybe you're in a field or you're thinking about going into a field where you think AI's not gonna touch that for a few years and you've got some sort of buffer. I'll give you uh a personal example here. I was talking to my son who's getting ready to go to college in the fall. And I said, How are you, if at all, thinking about what AI is gonna do to the job market that you're gonna come out into in four years? And his answer to me was, Well, the things I'm thinking about studying, I don't think AI is going to replace. And I just kind of smiled inwardly and I'm thinking, maybe you better think a little bit more about that sort of uh the other people are probably thinking that as well.

SPEAKER_00 15:27

And so there's probably gonna be an uptick in folks that are going into whatever field that is. I mean, you have even if it's not technology related, other folks are gonna think AI can't replace a plumber or an electrician, but now you have more plumbers and more electricians.

SPEAKER_02 15:44

Yeah.

SPEAKER_03 15:45

So my worry isn't so much that AI is here, it's that people re who are looking to cut corners, things like that are reliant on it. So there was a in the article he mentions a year ago AI could barely write a few lines of code, and now it can write hundreds of lines of code correctly. Well, that's because it's a development tool, programming tool. They fed it, right, all that information to build up its intelligence. Other areas like financial analysis, journalism, and medical analysis, those areas don't have that history boat up yet. And on the pit, they even had a charting program that was written by AI and then charted it wrong. And uh, doctor said you need to go look at it. You can't just say everything it's doing is accurate. You've got to go give it a second look and approve it before you send it on because it could chart your analysis as incorrect and give you the wrong medicine or or ignore signs. Same thing with financials. I saw an article or a commercial, and I don't know if they're using AI about it, but the whole idea is it was an EFT, and they said, Oh, we're not taking all the historic reports and all that. That's old news. We're doing this a different way. I'm thinking, oh my God, are you using AI to determine where this is going? You know, yeah. I'm thinking there's no freaking way. And I just think in writing content and journalism, is it going to take all the talking heads, the commentaries with real news and make some commentaries now real news? I mean, that's what it's doing today, right? I mean, everybody's believing this is happening, but it's just someone made a comment just to get things started. Next thing you know, everyone believes that's what happened. I think that's what scares me. It's those little segments that we depend on daily. Well, I'm not going to mention who I think it is, but someone put out a recipe that had like rat poison or gasoline in it or something, some kind of drink, right? And they just didn't over and it got and it got published because someone looked at it to see, hey, is this really a recipe that we want to put out? AI didn't know any better. They learned, you know, it's just things like that that I think that's what worries me. It's that people want to sit back autonomously have drive a car. I don't want to touch the steering wheel, right? I want to do more with less. That's what worries me about AI.

SPEAKER_00 18:02

Not I've seen examples where it's used as a crutch, and I think that's where it falls flat and disappoints. When it is used to augment your ability and assist to help you do more, or as another source to think through things that might be able to provide you perspective, that's when I've seen it shine and in coding. It's awesome to get something up quickly.

SPEAKER_03 18:27

Yeah. So we're 20 minutes into steel. Did we miss anything before we go to opportunity? I don't want to miss anything. I know we just kind of ran with this a little bit. Is there any points that we didn't hit on fear?

SPEAKER_00 18:38

I think we talked about the key points or at least the major points using it as a crutch, security, government, um, replacement of jobs. All things that are valid fears. I don't know that there's a specific point that was missed on the fear side. I I think that was all about.

SPEAKER_03 18:59

Yeah, it got into like white-collar jobs gone and one to five years. I think everyone's been looking for that anyway. There's always been a risk of middle management, you know, losing positions because things are, you know, isn't needed. I don't know.

SPEAKER_00 19:13

I mean, that happens with or without AI.

SPEAKER_03 19:16

Yeah. That's been the long term. And I think that's just about the middle management not having empathy, not getting involved, you know what I mean, and just trying to rule from on high, even though they're not on high, they're in the middle. So, okay, that's the honest fear. Let's talk about the upside. I believe it or not, I've got just as much upside for AI as I had in all my negativity.

SPEAKER_00 19:37

All right, I'm I'm curious to hear that.

SPEAKER_03 19:40

Let's talk about the upside he lays out because I think it's just as extreme. So he says this might be the most important year of our career. If you're an IT pro listening to this, what does working accordingly actually look like between now and December?

SPEAKER_00 19:57

I think that's upscaling. That that's training, that's learning, that's augmenting your your skills, and that's growing that muscle, applying it. I'm in the process of doing that now.

SPEAKER_03 20:08

With Service Now, with Azure, with AWS, all those things, didn't you feel like when A first came out, you were behind the eight ball or be, you know, and you didn't know enough, and you just had to jump back in again, learn more aggressively, you know?

SPEAKER_00 20:22

Same behavior with containers, absolutely. With with that next level of virtualization, yes. I think even when VMs first came out, it was what is this? Wow, that's really cool. I can do this with I would have, and then you hear all these other use cases that you never even would have thought of. And so I think yes, it's changing so fast. Definitely feel behind the eight ball.

SPEAKER_02 20:46

You have to evolve.

SPEAKER_00 20:47

Was the latest and greatest. I think two weeks ago or a week ago, they just released 5.4. It's today, I think it's so fast. Now with Azure, there were like six options to manage your Azure instance when that first came out. So that not as much.

SPEAKER_03 21:04

Well, there was things like egress. What was it?

SPEAKER_00 21:08

Yeah, ingress and egress.

SPEAKER_03 21:10

Yeah, ingress and egress where charging was dramatically different. You can put data on it, but if you want to retrieve data from it, the cost was dramatically more expensive. I think the learning curve was the general is a general expense, but how how much of expense is it? And I think AI is going to be the same thing with tokens and GPUs and use of things like that too, right? I mean, to some extent.

SPEAKER_00 21:33

I don't know where that is necessarily headed. I know everybody is looking for efficiency, and the coolest things I've seen have been in the small model space. You have these foundational models where if you need the the one page or the the one shot, and you have a incredible, fantastical outcome, that seems to be the direction. And for a lot of platforms, there's folks that are feel really passionate. It's very strong in that space. And then on the opposite side, I've seen some really, really good small models across use cases, whether it's uh a chat bot, image generation, video generation, whatever, that have just had amazing results because of the technology underpinning all of this is improving. I have a vibe code example, uh, and I was using Codecs, and I could see the token count go up over time, and that's that memory context window. And I think I was on a free plan. It was 250,000 tokens or something for this memory context. I did the entire POC before I even hit that window. And this was with 5.3. A couple weeks ago, months ago. I don't recall what the context windows were. Now you have some offerings like pro offerings, etc. There are million, million tokens in context. Now, how do you what do you do when you hit that limit? Save your current state, pull the next goal in, and continue on, move forward. It's like a it's a memory card for a PlayStation. That's all it is. And I I think at some point that goes away. You'll probably have a container that just has your uh your AI goal or where you currently are.

SPEAKER_03 23:20

Well, I I I don't think I've made the flip yet. I kept saying we're going to talk about opportunity, but I you're looking at half full, I'm looking at half empty. So there was a statement that Brian Feid made a couple weeks ago that we just released today. It said, like, when things are free, you're no longer the customer, you're the product, right? That's a that's something to be considered. But here's the other thing I've been watching lately commercials, and I see them today. And it's it's a cloud commercial and it says ads are coming to AI, but not to Claude. That's where free.

SPEAKER_00 23:51

Is that not an ad?

SPEAKER_03 23:53

Well, yeah, no, I mean ads, you know how you go to Google, I think it's different. When you go to Google, you do a first few pages are people who paid money. And if it's that's what's next, is if it's gonna be free, you're gonna have to sift through all those ads to get that. Why I value it now is because I don't have all those ads to deal with. Yeah. So I just think that's I'm I'm gonna try to get off the half-empty side and start looking at opportunity here. There is an opportunity. I love the opportunity of automation. I love the thing where, and we dealt with it when we were working together at Taft. You know, it's like I had smart people on my team, but they were filled with time of doing dumb things, repetitive, easy tasks. If I if I had AI, I wouldn't be doing extraordinary things and making a move. I'd make more moves by saying, I'm gonna get rid of these redundant things and have someone monitor, but you know, get some things done that way, and let my people think and do things to grow and expand. There's the value of AI to me. Is those sort of things.

SPEAKER_01 24:58

Yeah, agreed. I think I'll say something around opportunity and and riff off of that. I think right now you can build some really cool things. You can automate some really cool things, but you've got to kind of cobble everything together yourself, right? You have to be a pretty good technologist to spin up, you know, something that can do all these amazing things. You, you know, build a language model or rather run a language model on your local machine, bring some agents in-house, have it do all these cool things where you can just, you know, text it and have it summarize something back to you and produce PDFs and images and PowerPoints and all that. All possible today. But it isn't easy to do necessarily, certainly not for the average Joe, right? I mean, I think the opportunity is that, you know, you're gonna have something like this black rectangle and it's gonna be an edge device, right? And all that, all the all the the plumbing and the complexity of all of that, you know, there's the opportunity for whoever figures out how to build that because my mom isn't gonna wanna uh or or wouldn't be capable of doing that. I love you, mom, but you can't uh you're you're not gonna put open quad on your your Mac mini by yourself.

SPEAKER_03 26:10

So one of the things we're looking at doing, ServiceNow has a cool tool that they're building. I don't know if it's perfect yet. We haven't used it yet. I've got later this week and next week, we're talking to them about how do I introduce this to a handful of people where I call citizen development, right? But it's not really citizen development. I have a lot of controls in there, so it's not really open. But they have a product called Build Agent and it uses natural language for them just to type in, I want to do this type of application to do these things in this way and report it in this way to me, you know, write the paragraph story of what you want, and it will build the application. And you, I would say developers have to finish it, probably insert it into a service cow, you know, just those areas to make it useful for them to get to and use in a finite, but it'll take to me, I have a small development team, it takes all of those back and like right now. I go back and forth on just small edits on a workflow. Oh, this field, this field, this field. I think two things happen. One, they can take me halfway there, and I haven't to get involved yet. And I could see what they're thinking by reading that paragraph. I know their mindset, I know what they were trying to accomplish, and this is what I delivered to them, things like that. And they'll also understand hey, every time I have a little tiny change, it caused more work for me. Maybe I don't want to have that change. And I think the way changes more. Is it a value return or is it just some small thing that's not going to bring anything? And I think to me, it teaches those people those sort of things. But I like that idea. If it works, and the demo worked fabulously and impressed our team tremendously. But I'm looking forward to seeing how that comes out because we have a lot of workflows. We're we're changing from everything's an incident to everything is like an interaction. And then make a decision at that point, is this a request, a change, or an incident? And if it's a request, it goes to a series like a catalog series of flows. They choose the right flow and it flows the right way and hits the right people. No more volleyball tickets, no more. Do you send it to me? Yeah, I didn't want it. I sent it back to you, all those sort of things.

SPEAKER_01 28:11

Well, and and the opportunity there, if I'm understanding your your story correctly, is that this tool will allow your developers to iterate more quickly, right? I mean, you can you can have idea A and then, you know, it'll it'll give you output A and then now let's tweak that a little bit. Now you've got a A.1, and it doesn't take any more time than it took to ask the question and you know, wait a yeah.

SPEAKER_03 28:40

I opened Pandora's box by saying this is how we're doing it interaction to incident change or request, but we don't have enough request workflows to handle all the different requests that are coming in, they have to be written. And I don't have a team to write it. So I'm thinking, I can't like a thousand request workflows I probably have to write in like 30 days. And there's no way it's not gonna happen. But for every department that's affected by this category, this product, if they got involved and said, this is how I'll give you a paragraph of how I want it to work, and I take that paragraph for them and put it in there, and it builds it halfway for me without me having to go in and do a lot of manipulation and templates, that'll save me a lot of time. So I think this natural language, even if they don't get involved, they just send me the paragraph, will help a lot. I think I I'm I'm hoping. I don't want to be negative. This is the opportunity segment. Certainly. But that's an opportunity for me is how do I save time? How do I save energy on redundant things where I want to expand and grow and jump into new areas?

SPEAKER_00 29:38

I think saving energy, saving time. Critical things, we we all want to do that.

SPEAKER_02 29:44

Think bigger.

SPEAKER_00 29:44

Going back to how that example started, it's that manual maintenance. I call it the M-word. It's manual, it's that zombie work. It's not contributing to innovation. Uh, it's not something where you need a surgeon looking at it. It's the stuff that really nobody wants to do. It's the stuff that even on the desk, help desk, you don't want to do. Let's see what we can shift of that work, at least over to AI. Is there some of that boilerplate work that we don't really have time for, which is how we end up in messy environments or we end up with tech debt? Is there any of that that contributes, anything contributing to that that we can shift over? That maintenance work, that zombie work that we really don't find value in, but we have to do anyways? Can we identify what those things are? Can we prioritize them and then move that work over? I think that would be what I'd be most excited about because you have time, you have energy, those are your resources. That's it. It's finite. When it's done, it's done. When your brain is burnt, it's burnt. I would love to be able to protect those two things and give those two things back to people, back to both the folks who have to manage the platforms, work in the company, and then hopefully some of that translates outwards and has a ripple effect to our customers getting a better end product.

SPEAKER_03 31:05

So you're with ServiceNow a lot, Steele. So they have also we're looking at the the it's Gen AI, but it's also predictive intelligence. So it's at actually entry level of for of help desk before our people help desk gets involved. So when a phone call comes in right now, it's gonna be people, them using it. Even though the ticket will have, okay, I've seen this, but it'll have pop-ups. I've seen this before. Do you want to use this as a closing? Do you want to use this as a KB article? It'll bring them help. It'll nurture them along the way. The other thing, though, is the emails. I want help, I want the virtual agent to hit it first and get the ticket almost to the point of this is solved, or maybe after over time that can be solved. Some of the easier things can just route right in, go right out because predictive intelligence told them 99% of the time this is what you do. And I think that's going to be a benefit too. Using Teams as a front face, you know, they type into Teams. I'm having a problem with this. Having virtual agent taking that first stab at it before a person, an individual has to see it. It'll allow them to spread out and do different things or do more things that are probably time consuming with a user. It needs more nurturing, hand-to-hand stuff, and more tickets can get done instead of waiting in a queue because I have a deep thing I'm working on here. I can't get to those things. I think that is a value, what you're speaking of value. That's to me is a value.

SPEAKER_00 32:28

And to kind of expand that example, that's using machine learning to look at data, historical data, see what the solution was, see who it was assigned to, see what the fix was, and provide that solution. And that's why it's critical to have good knowledge. It's why it's critical to have good data in tickets and to have good data in general. Yep. And even those capabilities are a good first step towards protecting energy, towards protecting time. I mean, hopefully Bon Jovi likes performing living on a prayer for the 100 billionth time or a thousandth time. I mean, I'm sure they could snore it and play it perfectly uh in their sleep. It's moving forward. What can I do now? If I don't have to worry about resetting passwords, if an email comes in, the intent is understood, the ticket is created, populated, the agent is looking at knowledge articles, and the agenda is looking at catalog items or the your service catalog to provide some kind of solution. That is real value. There's real ROI there, there's protection of energy, there's protection of time. And then I think you can have those conversations of how do we innovate? How do we make this better? How are we measuring this? How are we tracking the value for this? Because now I believe you are getting value. That value that was promised, that AI is going, whether Gen AI or machine learning in it in this example, Brian, it's both of them working in tandem. And I think this is a sweet spot because it's real data, it's not hallucinated data. And then it's Gen AI capability bringing that data in and then leveraging it in the way that solves the ticket or makes the problem more, I'm not necessarily trivial, but prevent it from having to go back to human hands. It's not something I've solved a hundred times. I get it, I know how to do it, I can teach folks, but I want to go solve different problems. And I think that's the value, that tier zero value that everyone who has IT, has systems, will get immediate benefit from. That's where you got to bring people on board, have them relate to that story and be able to articulate it with that empathy. Uh, and then measure it and show that value. That is the thing that I'm most excited about, is just all of those different use cases to protect time and energy.

SPEAKER_03 34:54

So Matt mentions, and this is in our opportunity segment, but he mentions leaning in to the hardest to replace parts relationships, trust, accountability, physical presence. How do I te leaders and platform owners double down there? And I'm I'm interested in it. Do you have a thought on that?

SPEAKER_00 35:13

I'll let Toby start.

SPEAKER_01 35:16

Talking about leaning into those as like from the human element, like if AI is gonna do those mundane zombie tasks, then my value as a human is to lean into that the relationship and those other aspects you talk about, Brian?

SPEAKER_03 35:29

Yeah, I think so, because then the follow-up was like where I AIs can build the workflows, what is trusted human look like, you know, inside of an IT department? So I don't know. I don't know if it's saying can AI can't it replace relationships and trust and accountability and it can't be physical presence, but can it replace human aspects for that? Is that what we say our value is? But yet it's not a good idea.

SPEAKER_00 35:54

Did did calculators replace mathematicians?

SPEAKER_01 35:57

Right. Fair point there, Steele. Yeah, um, I'd like to think not, but I think it shifts the value and the importance over to those things, right? Right.

SPEAKER_03 36:07

At least that.

SPEAKER_04 36:08

Yeah.

SPEAKER_03 36:09

We we've seen that churn. I mean, what, 20, 30 years ago, your IT geek is someone you probably would not ever, ever put in front of a user because they couldn't communicate, right? They had, you know, the Doritos and chips and Mountain Dews and cigarettes and whatever else going on, and in some back room, it's dimly lit, and that was that was your IT geek. And it was a geek. Nowadays, that's not your prof your successful IT professional. It's someone who has to be like we talked about empathy, you know, has builds trust, builds relationships, is accountable for what they're doing, or takes their product or solutions into account, you know, are accountable for it. I think, I think it's a totally different type of person nowadays.

SPEAKER_01 36:52

I think that's true. I I I wanted to respond to something, Steele, you were talking about that the zombie work. And I think one of the things I've been trying to do more with AI lately is beyond just those zombie tasks, and I think that was, you know, a lot of people's haha moments when, you know, something AI did it for you, you know, whether it coded this app for you or add disk space.

SPEAKER_02 37:14

This space airs. You know, automatically add disk space. Easy then, right?

SPEAKER_01 37:20

Well, whatever. There's you know, all sorts of those examples, but then using it to do that higher level work, which it's capable of now helping you with, right? You know, okay, uh fine, summarize an email, right? I mean, think about like I put this in in human terms, right? You know, I was an executive, I could have an assistant or an intern do that for me, right? I don't need that anymore.

SPEAKER_00 37:42

I have it feels like we we have one now, which is really cool.

SPEAKER_01 37:46

We have one, right? Which is cool because you know, our parents probably had secretaries that do that, a human thing, and then now we've got this AI that does that. But, you know, you gotta you gotta take it further than that. And I think this is, you know, back to Matt's point about you know, practicing and working with it and pushing it and learning new learning new things about it and upskilling to your point, Steele. Like it can help you be that, uh help you be that trusted advisor by helping you strategize, right? Don't think of it as uh an executive assistant or an eager, you know, all uh a never tiresome uh intern. Think about it as a round table full of experts. Okay, we've solved the problem of you know, auto-adjudicating tickets that come in first pass to service now, right? We've offloaded that to an agent, it gets it right 99% of the time. Now, AI genius, help me figure out how to run a better service desk. How do I, you know, how do I build this great thing that I've always wanted to build and never had time? Challenge me on that. Let's talk about that for a while, let's strategize around that, right?

SPEAKER_03 38:53

I like your term a chat a challenge, though, because you gotta tell it no every once in a while.

SPEAKER_01 38:57

You do, you do. I I've I've had more great results of the past month or two by saying no and saying, challenge me on that, push back on this, right? Argue with me about it, right? Question my thinking. I I'm thinking about this, poke holes in this, right? Use phrases like that. Because you can't take yourself, you're in it.

SPEAKER_03 39:17

Imagine if you went to a project meeting, a delivery, and you sat there and you was in a conference room and you represented your area, and there were 10 other nine other people, make 10, nine other people who are experts in each of their areas, right? So to me, that's what AI can do. It can sit those seats for you, but you still have to sit in that seat. You still have to represent your spot. And that's where the challenge comes in. You bring something to that table. That's right.

SPEAKER_01 39:45

And do you want a round table full of nine yes men just saying, yes, Brian, what a fantastic idea that was. Let's go with that, right? No, you want you want honest opinions. You want people that are gonna challenge your thinking, people that are gonna bring their expertise, right? So, you know, once you start treating it like a round table full of very knowledgeable people in X, Y, and Z that, you know, can give you honest opinion, you're gonna get some.

SPEAKER_03 40:10

But they're only gonna give you nine tenths at the most of the answer, right? Because you're that tenth person. I think that's an important thing we can't forget. Yeah. It won't always give you a perfect. It takes you as a part of it to do so. And I think if everyone thinks of it that way, is I'm a part of this. I'm just gonna trust what they say and just take it and run with it. I think you do that blindly. Would you do that in a conference room with nine other people? No.

SPEAKER_00 40:35

No, I would rather set a round table of nine X-Men myself instead of yes men. I I think to that point, even X-Men as the example, you have different domains of knowledge that you can pull from.

SPEAKER_03 40:49

Right.

SPEAKER_00 40:50

Different skills. And so it there's a different scope. And you are there to synthesize that information and then leverage it. And you can have your head in the ground like the ostrich and hide from that possibility. There are folks who are not doing that, they are tackling it headfirst, and they're they're reaping the benefits of that. They're learning where it's valuable, where you can trust it, where you should review. And it's not a one-trick pony anymore. It's not just a chat bot. It has a wide range of capabilities from generating dashboards, metrics, all the other use cases, generating applications. It has brought things that would have been out of reach or real difficult to get to into the realm of possibility in a much shorter time. And that is the most exciting thing about it is what you might have had as a dream, it's closer now. It's something that you can bring into fruition using your partners at that round table.

SPEAKER_03 41:51

But I think you've got to make sure you just like any conference room of people, you have to invite the right people. So if you only invited six of the people who are needed to be in that meeting or three of them didn't attend, you're gonna be missing part of your answer. So your prompt, you know, in AI, you know, when you start building those tools and whatever you build, you have to make sure you include all the different schematic things that you wanted to look at or consider so we'll bring you back a better answer, right? I mean, lots of times I'll do a search and I I I did one on TOGAF. You brought the, you know, the T O G A up the that um I I I said bring me some some topics about that. And it gave me some things about the testing, the certification. I don't want to go down that rabbit hole. So I said, remove that now, what are the questions now? You know, we you have to give it some guidance. I think you still have to think about what you're looking at, you know, to do things. And I think you have to consider the areas across the IT spectrum that you're wanting to involve in that I in that AI output.

SPEAKER_00 42:52

But Toby, uh I I I want you to comment on this, but I I see two trends. And I'm gonna knock on wood on when I say this, because I I'm sure you both will counterexample me immediately. I think with how you interact with AI, knowing how much information you have to provide up front, how much critical information you have to provide, you could start small, you don't have to provide it all. But I I I think there is an increase in critical thinking that is needed when you can see that the more you provide and the better quality of thought that you start with, the better the outcome. I think critical thinking, there's gonna be an emphasis on it more so than there already is, and it's gonna be much more common. Uh, and folks are gonna get in aggregate better at critical thinking. It's one trend. Great. Second is that to Matt's point earlier about relationships, technology is going to get better at managing technology, and I think people are gonna get better at managing and relating with people. That's where I see that headed. You take that critical thinking that is improving. We are talking more with our customers. We're growing empathy. We're understanding our products and better understanding what solutions are needed in the market. And then translating that over into the product side, over into the solution side. And then technology, AI helps fill in that gap. Models improve, critical thinking improves, outcomes improve, instructions improve. Folks become more focused on the data and the outcomes that we're trying to drive, providing that, and then letting technology do what technology does. I think those two trends or those two themes are going to are I agree with you on critical thinking.

SPEAKER_03 44:36

Become more visible.

SPEAKER_00 44:37

Yeah.

SPEAKER_03 44:38

I got a t-shirt. It says critical thinking in big words, then it says the other national deficit. It's true though, because it's something that, I don't know, critical thinking was uh, I think was at a high level, Thomas Edison, Ben Franklin, you know, all the all those entrepreneurs and inventors. And then we went through this plate this plateauing or dips where we just kind of rogue things for a while. And I think now we're back on the uplift again. And I think that's what's shaking people up. You can't just write anymore. You have to really critically think some of these things through. You have to think about security, where you put your name, where you put your phone numbers, where you give your ad, you know, your password, your credit cards. It's critical thinking. It involves that. And I think that's where people are stumbling. We haven't had to critically think probably since Reagan, you know, 80s. You know, it's just, I think that's something that I think that's my opinion. It's something that we're hurting in, and what uh this will teach us to do so.

SPEAKER_01 45:34

I I like the the the second point you were trying to make, Castile, about a point you did make about human relationships becoming more important. It's isn't it ironic though, like if that that were to be the case, right? We've brought more of these whatever AI robots into our lives and we interact with them in cases where we formally would have interacted with actual people, whether it's a chatbot or a research assistant or an intern or you know, a colleague, right? We're we're leveraging AI to do those things. But in some senses, right, by offloading those tasks, you've now swung things back over in the other direction and you can focus on what it makes you well, you know, what makes you truly unique as a as a as a human and differentiation to AI. Interesting.

SPEAKER_03 46:20

Yeah, I think tech technology itself has made us not so social in a way, but I think it's opened up other things like parents or siblings across the country for you, Toby in Montana. Right. If it was back in the 70s, you would get a Christmas card and a couple of letters a year. You know, a long distance telephone call was probably very expensive, you know, to have a long conversation. But now between Zoom, Zoom calls, watching their their their Facebook pictures of their kids, you are able to keep in touch a lot easier if you use it the social media for that reason. Not for chasing likes. Nice. I don't know why I say that because we chase likes a lot on this podcast. But um make sure you like, like, subscribe, like, subscribe. But I mean, just to give yourself credibility as a person or something, as an individual, I think that's tough. I go, but I think it has opened up or you know, shortened the distance in our world between people. My daughter went to South Korea, and now she talks with there's people she met all over the world on a regular basis. That wouldn't have happened so much in the 70s because the letters were taking too long in between and so many people forget each other, and you know, it's just not as easy. Truly said. Well, have we solved uh have we solved everything here, gents? I think it was a good article. I think you've got to take it with how you know, read into it what you read, you know. I think some of the negative is probably too negative, some of the opportunities too much opportunity. That's with anything. I think you should read I think it's a good thought-provoking article. I think a lot of people should read it and just to get an idea of the effects of AI and what's coming and what what to think about it and what to consider. So be the giraffe.

SPEAKER_01 48:01

Yeah, be the giraffe. Exactly. Be the giraffe, not the ostrich. Whether or not you think it's happening tomorrow or five years from now, you know, educate yourself, be the be the giraffe. All right, bring it home, Steele.

SPEAKER_00 48:13

If Matt Schummer's article, Something Big Happening, resonated with you, hit the link in the show notes and give it a full read. He deserves the eyeballs. And if this conversation helped you, follow the Wired Garage, leave a review, and pass this episode to one person on your team who needs to hear it. Until next time, keep your hands on the tools, your eyes on the humans, and we'll see you back in the wired garage.

SPEAKER_03 48:35

Thanks, everybody.

SPEAKER_00 48:36

Thanks.