Chuck Yates Got A Job

00;00;01;05 - 00;00;38;07
Unknown
Slow to do what he feels like. I will do this very fast for this work. Thank you. Pay in dreams and, take my name. Give me the Cordy story. Who's Cordy? So Cordy was founded about 40 years ago by some occupational health, the industrial hygienist, nurses and some technologists to help address, just occupational health in the workplace, taking care of employees and create software to help do that better.

00;00;38;09 - 00;01;08;11
Unknown
And since then, it has dramatically grown and expanded to cover all of environmental, health, safety, quality, sustainability. Just across the board, really focusing on responsible operations, helping organizations be more responsible, protect their workers, protect the communities that they work in with technology, and really by being the specialists and and so starting with nurses, knowing what that looks like to do their job and with the tools they needed.

00;01;08;13 - 00;01;36;19
Unknown
Kind of expanding to that, getting people from industry, getting people that have worked as safety professionals. What do you need? What what tools are you missing? What's the existing technology missing? And then building that in? So really kind of built for those, those specialists in these really key areas that are critical to keeping operations going. So protecting those employees, which in the end ends up protecting organizations and helping them be more performant as well.

00;01;36;20 - 00;02;07;15
Unknown
Right. Downtime because somebody got injured isn't just a human cost. But there's also, you know, performance costs and operational costs as well. So we've just found we have I think it's 1500 current customers, across many different industries, really focus a lot. And like the dirty and dangerous, is how we refer to it. Hopefully that's not too derogatory, because I think the folks in the oil patch would take that with pride.

00;02;07;17 - 00;02;29;10
Unknown
That's kind of what I thought. That's that's been my experience too. But, but that really though, so long as you said it, wearing square toed, boots. That's the key. Steel toed, right heel toe. Square toe. Not the round cowboy boots. I'm a finance pro. I like the round toes, but, they don't let me out in the field, so.

00;02;29;13 - 00;02;52;11
Unknown
Yeah. So we've just. You know, this this technology to really help organizations, be more responsible and improve performance around those, these key areas. Give me, like, an, an example of something your software might do for an energy company. Oil and gas company, a pipeline company, a service company. Sure. So let me give you like it is really wide and varied.

00;02;52;11 - 00;03;09;10
Unknown
We do a lot of things are specialty, but starting with things like fit for duty. So employee either they're getting hired or they're going to go out and they're going to be working, you know, on a rig or out in the oil field there. There's certain amounts of like testing that needs to be done to make sure you're physically able to go out there and do that.

00;03;09;10 - 00;03;37;03
Unknown
You're fit for duty. And so the nurses, the practitioners, the clinicians, they're doing those assessments, they'll do that in our software. They'll manage that. We like vaccines or other types of health care that's managed there. But then so that's health. If somebody does get injured, we're working with the employees. So we'll help to log the incident investigated, understand it, prevent it, but also support the employee in getting back to work if they're going to be out for a while.

00;03;37;06 - 00;03;59;09
Unknown
I, I manage that whole case, the insurance, all of those things. That's going to go into things like waste management as well. So maybe with, you know, an injury or some kind of incident, a lot of times it's not just a person, it's you're losing product, right? Something gets spilled that goes to the ground. You're going to need to report that, we're going to need to manage those kind of emissions and the hazards that come from that.

00;03;59;09 - 00;04;16;25
Unknown
And so our software's going to help do that as well. Understand it, quantify it, report it, tell the regulators what happened. And then also, you know, there's so when things go wrong our software is going to be tracking that and the impact of it. But also then of course the more important part of preventing things from going wrong.

00;04;16;25 - 00;04;41;07
Unknown
Right. So inspections, audits just corrective actions and tracking that you might do across the board. And this isn't oil and gas specific, but it's certainly managed. It's important. They're more than a lot of other places because keeping people safe, keeping operations going is so critical. And it's not an easy job. It's not just something, you know, that, happens easily.

00;04;41;14 - 00;05;04;25
Unknown
So let me let me ask you this. And I've never been out in the field. I was, as folks know, that. Watch this. So I always been a finance pro. I'll fess up to this. First time I went out to the field, I turned to my my business partner, Mike Hines, who is a man's man. I mean, he ran the Jay Field for Exxon at one point, which is a nasty hs2's field.

00;05;04;25 - 00;05;28;25
Unknown
And anyway, I turned to him and I go, wow, it's really dirty out here. And he goes, please don't tell the company man that you will get your butt kicked. So take this with a grain of salt. Where does your software stop? And like a JSA when we're going to go rig up a rig, where does that start?

00;05;28;25 - 00;05;52;05
Unknown
Or do you guys also provide jerseys for for oil field activities? Yeah, so do JSA. So it goes out. We're out into the field. You're doing your checklists. You're doing your risk assessments, your, checking the equipment. And so all of those like operational doing things operationally safe, all of those things, are in our software. Oh very cool.

00;05;52;09 - 00;06;17;18
Unknown
And then it's feedback to the people sitting in the office that are doing the calculations and figuring out what it means to write those experts heritage and the reporting. And so all of the above, that's interesting. Gotcha. The so my mind is racing with all this sort of stuff. The the big question though is how have you guys looked at what we'll call SAS apocalypse or whatever they're calling it.

00;06;17;18 - 00;06;41;23
Unknown
But basically you've been around for 40 years. You've been a software company. You're trying to adopt AI, bringing that in. How have you all kind of navigated that? Because me as the snooty upstart AI software guys going, oh, we're just going to eat all legacy software, and you actually have cash flow. And I don't. So yeah, know that that's funny.

00;06;42;00 - 00;07;04;21
Unknown
And I didn't expect that one. But I should have so fair point. Right. Are there, little there are bits and pieces of what we do in our software that could be done with AI, but our system is a system of record and it has built in best practices and the nuances. So you can't just read the regulation and say, based on this regulation, this is what I need to do.

00;07;04;27 - 00;07;46;17
Unknown
Every organization has best practices and approaches. They're using, human organizational performance, approach or safety to or different ways of interpreting how they'll comply with the regulation if we start with compliance. And that's built into the software already, not just not just AI, but like the understanding that this employee had this kind of exposure that ties into how often they've, you know, similar employees have been, had last time there's there's this huge amount of historical data and knowledge that isn't just available on the internet for AI to consume and set up, but I certainly can help with that.

00;07;46;17 - 00;08;12;15
Unknown
But it needs to be built on that foundation of the understanding and not just regulations, but the interpretation of it. They're keeping them up to date. The understanding of like different approaches and how that gets built in all of that and proprietary understanding and context. It's built into the software, and that's what I needs to be able to provide really great advice, insights, better information.

00;08;12;18 - 00;08;30;21
Unknown
But these are life and death decisions, right? So you're going to need to make sure it's built on a foundation you can trust. And that's that kind of I see you kind of going from like a system of record to a system, a context to a system of action. Once we get to the place where we trust AI more to be able to do things.

00;08;30;24 - 00;08;51;09
Unknown
But you have to have that system of record. So I think that there's a huge opportunity with AI that you need to build it. The thing, the foundation of trust that I just doesn't quite have that context and it's not publicly available. So I'm going to say this and hopefully no VC looking at investing at us is watching this, because I'm going to fess up.

00;08;51;09 - 00;09;14;22
Unknown
I actually do think, some of the SaaS companies are going to wind up as the source of record. I mean, they just have too much in the way of information, to not be permanently there. And at the end of the day, they're going to have to navigate the whole issue of, do we open up and talk to other software?

00;09;14;24 - 00;09;35;15
Unknown
Do we try to stay closed, loop and build AI within? And and they're going to have to navigate that. I think at the end of the day, technology always says if you're a source of record, you need to open up. But we'll see how that how that goes. And I am duly noting your your point on domain expertise.

00;09;35;15 - 00;09;56;24
Unknown
I mean, you do. You guys have just seen so much in the way of, of incidents and knowing the nuances of this and that, that that's really important because you're right. This is life or death. You, you, you pull up the wrong bit of information. People's lives are on the line. So I think that's a, that's fair point.

00;09;56;26 - 00;10;18;15
Unknown
I mean, that hits in is is personal for me. So my, my grandfather died when he was younger than I am from a health related issue, from working in the mines, from lung diseases, from exposure. Still working in the mine. My dad was six when he died. When he lost his dad, and he had five brothers and sisters.

00;10;18;16 - 00;10;36;18
Unknown
It was a huge family impact. It impacted him then. It impacts him today. Even my kids are impacted by it now. It it was generational impacts. So when stuff goes wrong at work, it has huge impacts. And it's our responsibility. Like, hey, at the same time, I want to be able to turn the lights on. I want to be able to drive where I need to go.

00;10;36;18 - 00;10;54;08
Unknown
I like we, we have a certain standard of living, but we want to know that the companies that are, that are providing those services to us, they're that energy that they're doing in a responsible way, and they're not doing in a way that's going to hurt their employees or the communities they operate in. So that's like my personal passion.

00;10;54;08 - 00;11;31;08
Unknown
And that works perfectly with Courtney, because that's what we do. Yeah. And Colin's the same way. My, my business partner, I mean, he is a young roughneck, saw things that people shouldn't have to see. And it's it's very personal for him as well. And the, so I totally get it. Well, what's been kind of I type challenges that you guys have faced, and I'm even happy to throw I challenges that we've faced, out there and kind of go first to give you a chance to, to think about some stuff.

00;11;31;10 - 00;12;00;04
Unknown
I will say this and I've got to give Colin credit on this. I really thought our biggest challenge was going to be, how in the hell do we get AI talent to move to Houston, Texas, and, yeah. No. And I love Houston. I mean, we have the best food scene in America. I will actually die on that hill as much as people say that they they hate the weather because it's always 100 degrees and 100% humidity, I don't feel like I have a shirt on unless it's sticking to me, so I.

00;12;00;08 - 00;12;27;25
Unknown
I love it here. But I also get, you know, going up to Seattle and recruiting folks out of Microsoft and the various places, going to the, going to Silicon Valley and recruiting folks around. I really thought that was going to be our biggest challenge, and it's been interesting. Colin's done a really good job of recruiting the team around here, and the way he did it was by selling that we're actually working on real world problems.

00;12;28;01 - 00;12;49;27
Unknown
I mean, if you look at the energy crisis out there in the world, it arguably can be our number one crisis. You know, the fact a billion people live in energy poverty is a big deal. I mean, that leads to wars and suffering and all that. And so he's done a really nice job of recruiting it. Recruiting talent here.

00;12;49;27 - 00;13;15;15
Unknown
We've got a got a great team, but that so that that's kind of one. Now you give me one of of kind of AI challenges. You guys have had, one of the AI challenges that we've had. And I think this resonates both with our customers and other software companies. Is that the pace of change is so fast, like AI and what is available and what it can do today is going to be totally different in six months from now.

00;13;15;16 - 00;13;34;10
Unknown
Oh, I check in with I check in with the tech team once a week. And I say, I'm saying this in a sales call. Is it even still true? You know, I well and we tested things, you know, a year ago I'm like, it's just not ready yet. We can't use it for that. It's not trustworthy enough that then six months after that.

00;13;34;10 - 00;13;56;08
Unknown
Yeah. No, it's ready now. We can do it. So it's shifting our own strategy to make sure that we're providing the best possible technology and responses to our customers, but it means just it does mean like shifting, changing more frequently than what? Than what we had in the past. Handwriting was one of those, I mean, six, nine months ago.

00;13;56;08 - 00;14;19;12
Unknown
Can it read handwriting? Nah. Can't read handwriting. It now reads handwriting better than we do. We put things into the system just so we can read what it says, which is, yeah, it's incredible. So the pace of changing and it's one of the things that the other thing that I think is interesting. So as like as a person who's leading strategy in a software company, lato, what do you see happening in five years?

00;14;19;19 - 00;14;38;25
Unknown
Five years? This is like a crystal ball predicting the future. Before I felt like I had a feeling like at least 3 to 5 years out. Here's what I think it looks like. And I have an idea. But honestly, it's going so fast. Like I couldn't have predicted where we are now five years ago. Like it's so many things have changed.

00;14;38;25 - 00;15;03;20
Unknown
So it just it, it really requires just staying on the pulse of it constantly. So my Sunday morning jam is I usually get up and go for a long walk. And I live in a small town about 25 miles southwest of Houston. And there's this whole creepy thing about these two bagpipe players that play the city park while I'm out walking, but that's a whole nother story.

00;15;03;22 - 00;15;23;10
Unknown
I finally came to terms. It used to annoy me because I want to listen to my Rogan podcast or whatever audio book or whatever, and these guys are playing the bagpipes and it's annoying. I don't know if you've ever heard bagpipes, but it's annoying. It's even worse in real life. I finally came to terms with that, though, because it's like, this is their jam.

00;15;23;15 - 00;15;44;11
Unknown
This is what they love. Their wives don't want them in the backyard, I get it. So now I just listen to the bagpipes. But where I was going with this is, on my three and four hour walk now, no more podcasts, no more audiobooks. I'm talking to I the whole time just trying to keep up. You know what happened this week?

00;15;44;11 - 00;16;07;26
Unknown
What is this be. I don't even know what this be means. Please explain it to me. What did carpaccio say this week? You know, it's crazy. So he isn't just here talking to I to get the information. I've been listening. I my go to right now is podcast, right. Like what's there's the daily podcast. The just lots of different people providing like this is what happened yesterday or in the last week getting a lot of different people's perspective on it.

00;16;07;26 - 00;16;34;05
Unknown
But you're just talking directly to your eye. Yeah. I've chosen grok mainly because I like her voice. So a little creepy there, I get, but no, and a lot of times, I'll see the blurb for the podcast and I'll be, hey, grok, what happened on this podcast? You know, can you summarize it for me? Yeah, I've gotten to I've gotten to that point.

00;16;34;08 - 00;17;13;03
Unknown
And it's crazy to try to keep up with just how how fast all the stuff's moving. And it's been the, the hardest thing, I think, for me has been because there's a new shiny object every week. Are we sitting here building the world's greatest software that nobody actually cares about? You know that that I wrote a blog about that about three weeks ago, because I feel like we spend a lot of time on R&D, and we have the shiny object, and we figure out how to embed it and make the software better.

00;17;13;06 - 00;17;32;07
Unknown
And then you're off to the next shiny object. Yeah. For us, I think, it's focusing on we have a problem. Right. So we have we want to help organizations operate more safely, like protect their employees. Let's just start there right away and protect the communities they operate in. What is what is required to do that. And that's for having that expertise.

00;17;32;07 - 00;17;50;02
Unknown
And like all of that understanding of what are the challenges that are out there in the world, and then looking at the tools, how can I help us solve that? Right. And then something new comes in. But really centering on the problem, we want to make sure that, you know, we're protecting the health of employees in the communities where organizations operate.

00;17;50;04 - 00;18;08;16
Unknown
That's our thing. And then we'll just add in the new technology. So it's not technology for technology's sake. It's not AI is hammer must be nail, right? We have the nail. We know what we need to focus on. And I think that does certainly help us. And this is like, well, here's the problems that we've historically had. Does AI help us solve that in a new way?

00;18;08;18 - 00;18;28;04
Unknown
Or in a better way? And then it's like some new technology comes in. So okay, does how does that help? How did that change things? And I think the hard thing is like, okay, is this one going to is this real? Is this going to be the thing that they're saying it is or is it not. Because there's a lot of is happening so fast, some of it gets debunked pretty quickly, right.

00;18;28;04 - 00;18;52;17
Unknown
So knowing being able to just know that the information is trusted or the technology is able to be trusted. One thing in, in in our world, everything needs to be auditable and explainable. So that is another thing. So you we have you know, we're dealing with regulators constantly. They want to see the paper trail or the, you know, the electron trail of how we got there and the decisions that were made.

00;18;52;17 - 00;19;14;08
Unknown
And that's another thing that can be tough for AI, because it's like, you know, by definition, also kind of a black box. So making sure everything we do is auditable. So that that may mean that some of there may be some really cool technology out there that we don't take advantage of because it's either not helping that's very specific mission, or it doesn't fit our level of like it's got to be governance.

00;19;14;08 - 00;19;49;18
Unknown
Got to be clear, it's got to be secure. We're also dealing with like HIPAA protected data, really sensitive data. So yeah, what tools we can use are certainly, limited or governed by the protections that they can offer to. Yeah. No, that's interesting. I finally the the blog I wrote was I can finally sleep. I think we finally figured out we had gone from I o allow you to search and engineers and oil and gas spend half their time looking for stuff to.

00;19;49;18 - 00;20;18;05
Unknown
Well, if you can extract the right data, you can start automating workflows, build agents to ultimately getting to the point where Clyde's going to be an operating system, if you will, and basically the tools and the platform we created for our PhDs to be able to spin up applications for our clients, we're just going to go ahead and give those tools to our clients and let them build their own applications.

00;20;18;05 - 00;20;39;06
Unknown
And we kind of see a world where we will have certain employees at certain clients that are building their own applications and are amazing and great. Others will get two thirds of the way there and call and need an FTE to come finish the application with them. And some folks will be. I just want the PhD to build.

00;20;39;06 - 00;21;05;09
Unknown
These are genic workflows for me. And so where we're going to earn our keep at collide is we are going to do a genic orchestration, data security, the audit trails like you talked about i.e. the guardrails so that the C-suite can actually sleep at night. And I pitch that to a client and they said, that's great. I don't want to mess with any of that stuff.

00;21;05;09 - 00;21;24;19
Unknown
And that was finally the first night of sleep I got in two years. So there you go. That makes I think that makes sense. I think, you know, if we go back to like some of the challenges, that we've been running into, and then there's two things that I, I'm sure that you run into as well.

00;21;24;21 - 00;21;48;10
Unknown
One of them, or if you haven't, you will I would expect one of them is just okay. So I needs to be built on top of a trusted data source and have all the it needs to have that context. We need to feed it that context. Right. So in in our world of environmental health, safety, sustainability, quality, it's most a lot of times companies started buying those solutions individually.

00;21;48;10 - 00;22;12;21
Unknown
You have a whole bunch of point solutions. They don't talk to each other. They don't have shared data, they don't have shared infrastructure. And the fact that, like when something goes wrong in environmental, it has impacts on safety, it has impacts on health and quality. You don't it's you don't see that. Or if you have warning signs that like, hey, something in your maintenance system is kind of it's it's within range, but kind of on the outside.

00;22;12;23 - 00;22;33;12
Unknown
Or it's late in the shift and people are starting to, you know, maybe get a little sloppier or maybe not follow protocol as much because they've been working for 11 hours and they're tired and like, understanding all those things together are really that's what you need to create the full picture to really understand and mitigate risk and put controls in place.

00;22;33;14 - 00;22;51;13
Unknown
If you have a whole bunch of systems where that's not all tied together, you can't see it, right? AI is not going to be able to see it. So there's part of like just having all of the infrastructure that you need for AI to be able to do these amazing things that we know that it will be able to do if everything's separate and dirty and not connected, can't do that.

00;22;51;13 - 00;23;10;23
Unknown
So that like on one side, organizations struggle because they don't have all the information in a clean way that they need for AI to do its job. But on the other side, you have the employees who don't trust AI and don't want to use it. And like, now it's going to take my job. I'm not I'm not interested.

00;23;10;23 - 00;23;42;01
Unknown
Or if they're like, yeah, seems great. And then they're using in ways they're totally create risk. And so the other side is like, let's start. It doesn't have to be doing the magical thing of the future, but let's just start getting people using it right now. So they're starting to like level like raise the water for all employees to get some understanding that this isn't magic or voodoo, although sometimes it feels like it, but like build up a level of experience and expertise.

00;23;42;03 - 00;24;03;18
Unknown
And you don't have to be an AI expert, but you do have to kind of understand what it's good at and what it's not, and, and get more comfortable with it. So that way they will use it by the time you get to this future state where you have all the data, you have all the information, it's going to start acting in some cases on your behalf for bringing up information for a human decision.

00;24;03;20 - 00;24;23;26
Unknown
They have to have some familiarity with AI and we have to educate our employees. We've got to get them going because there is definitely some resistance, especially in the field, in the frontline workers, like, no thank you, I've done it this way for this long. I'm going to keep doing it this way. Yeah. No, that's, that's a really good point.

00;24;23;26 - 00;24;44;29
Unknown
I was on a panel last night at the Petroleum Club, and we were talking about that, and they said, what's the key to all this? And I said, three years from now, it's ever started changing user behavior. Today I go, I honors I as much as I think Clyde has the best software out there and you should only use Clyde, blah, blah, blah, blah blah.

00;24;45;02 - 00;25;10;25
Unknown
I I do think at the end of the day, technology is pretty fungible to some degree. People have shown that they have a willingness to switch to grok from clod, you know, vice versa and everything. So the best technology or actually went out. But it's the organizations that start using it today driving user adoption. And I said last night, because I like to kind of say bombastic stuff, it's just what I do.

00;25;10;28 - 00;25;35;10
Unknown
I said in 18 months, it will show up in financial statements of oil and gas companies, who's using AI and who's not. And I think CEOs that aren't pushing adoption today are going to be out of a job. And I really mean that. And I would, it sounds like you kind of share the, the same thing. I, I've got a question now on, on user adoption.

00;25;35;10 - 00;26;08;03
Unknown
So if you had to give me 1 or 2 bits of advice on user adoption, how best to push that, how to start, what's your advice on that front? My advice would be start with the friction points somebody has. What do they hate about what they're doing? They don't want to do anymore? Because if you can bring AI in or any tool in to solve that problem, they're going to really appreciate it and they're going to be like, wait, I have these other things that are also really frustrating.

00;26;08;03 - 00;26;35;06
Unknown
And then you can build momentum and start getting, but start with the the pain points that they have, that are also, you know, of course, like within the risk profile and you know, understand that. But start with those frustration points. And a lot of times those are things that are administrative things, right? They're not value add or you don't feel like it's it fills your cup to be working on administrative typing things in like that's not why people get into the jobs are and unless of course are administrative and hate more power to them.

00;26;35;06 - 00;26;53;27
Unknown
But people want to be doing making the decisions, solving the problems, doing those things that feels good to solve problems, right? To fix things, to see the results and the the manual work of kind of administration a lot of times is a frustration point. Or maybe it's like they can't get access to the piece of information that they need.

00;26;53;27 - 00;27;14;16
Unknown
They always have to search for it. It takes forever. Those are the problems you start with, because then you get an advocate. You get somebody who's like, I love this thing. It made my life so much better. Even if it's not a huge business impact, it can be a huge impact for the for those employees. And a lot of times it ends up being a big impact because they can spend time doing more value added things.

00;27;14;19 - 00;27;43;25
Unknown
So start with those and get some quick wins. I love that because I talk about that. I'm usually a little more graphic and say words like socks. But yeah, things that really suck to you. But the the other thing I like to overlay on that on the Venn diagram is if you can really get a good handle on how much that thing that sucks is costing you, and you can get an ROI because not only is it like, oh my God, it made my world better.

00;27;44;02 - 00;28;04;00
Unknown
You can go tell the C-suite. And by the way, we're getting a five times ROI on this. I'm saving 1200 hours a year. I'm not paying that consultant anymore, or whatever the case may be. Yeah. No, they're they're almost always actually, I would say almost without exception. There are huge values to the business and those that the efficiency in not having people do that.

00;28;04;03 - 00;28;27;12
Unknown
So I can give a personal example. When I first started in, I was working for an energy company doing environmental permitting and consulting. And I was given a 600 page permit from there was for civic for one facility that I needed to understand and then translate into software. And it was a many months long job, many months long job.

00;28;27;17 - 00;28;49;16
Unknown
We now have an AI tool that's going to read that same permit and tell you, here's all the requirements and everything that you need to do now. Build that into your system, incorporate that into the way that you work. And it went from months to minutes and like, wow. Like I was literally I had an icon for the software of a person being their head on their computer because it was like the worst thing.

00;28;49;18 - 00;29;13;26
Unknown
And it was it was absolutely required, but not super value added. Right? Like spending all of that time. So now with AI, we could do 99% faster. In every organization, certainly every organization that operates in the United States, but every organization has those permits and all of that and just and has them for every site. So all of that time saved can be better used somewhere else.

00;29;13;29 - 00;29;35;02
Unknown
Yeah. We've got a client that we automated the filing. So there are tons and tons which the railroad commission in Texas wants. And they went from 1200 hours a year to seven minutes or whatever it is. And I think the client here in the next month or two is going to let it go fully a tech, literally no human in the loop.

00;29;35;02 - 00;29;56;26
Unknown
They'll get an email that says, hey, I got the tens, I filed them, we're all good, you know? So that's amazing. That's a huge amount of trust. So you guys must have done a really good job of building that in. And working through that to get to that level of accuracy and trust. That's great. Yeah, I think we've run 3000 tens and tens forms so far without a mistake.

00;29;56;26 - 00;30;23;02
Unknown
So knock on wood. Yeah. That's been that's been that's been great. Okay. I've got another question for you. So we have a source of record right now at an oil and gas company, and it's things like, you know, on stage 57 of the frack, the pressure was X, right? I'll kind of say that. And the beauty of AI is you brought up our layers.

00;30;23;05 - 00;30;42;16
Unknown
It's going to create one true source of record does in some way, shape or form. Either I'll clean up the data and get it into a good spot, or it'll talk to all the legacy like Clyde does, talk to all the legacy software and use that as creating that one source so everybody can sing off the same page of the hymnal.

00;30;42;18 - 00;31;23;04
Unknown
I'm going to say this is a statement, and feel free to beat it up as much as you want. I think that source of record is great, but I think creating the genic workflows and being able to have that as a source of record, how your organization actually operates and makes decisions is going to be ten x, the source of record that the data you already have is because I kind of look at it as the tribal knowledge and the know how and what you do every day you rent that, it walks out the door every day at 5:00, it gets in a car and it drives home the eugenic workflows.

00;31;23;04 - 00;31;57;08
Unknown
Following that and being able to mine that data for how to do things better, I think it's going to be ten x. Yeah. So I would agree that the AI that is actually acting, that is taking act or taking actions that it's working within a workflow that you're already doing or changing the way that you do the workflow is going to be even more valuable than what we have today, but there are going to be key places where we need to keep humans in the loop.

00;31;57;15 - 00;32;18;14
Unknown
Right? There's there are places where it is life or death decisions or like, look, as long as we have humans doing work in the field, you're going to need some humans to take care of them. I don't see a place where I can be providing first aid. Not in a way like this. Somebody just got injured. You're going to need a nurse, a clinician, an EMS person there to assess the situation.

00;32;18;18 - 00;32;40;07
Unknown
At least for the foreseeable future. And those people can use AI to do their job better. Right? But you are still going to need some humans and to make some decisions. There's going to be novel scenarios that I wouldn't know what to do with. There's nuanced ways of approach. So I think having all of this information in a system of record, there's there's a couple of things.

00;32;40;07 - 00;33;09;00
Unknown
One, if you have it in a data lake, right, or in, you know, some AI centralized level of like system of record that has the information that is all things that already happened. How does we want to interact? We want to intervene before the next bad thing does happen, not just looking backwards, but looking at what's current status right now and what's the next thing I'm going to do in is that next thing that I'm about to do as a human being here, safe, am I protected?

00;33;09;00 - 00;33;27;01
Unknown
Are the right controls in place? Am I going to cause a spill? What are those the next moment, looking at that next moment in. In order to look at the next moment, we need to know what those workflows are, what those activities are. And that is that's where we are focused on building AI into existing processes.

00;33;27;04 - 00;33;49;19
Unknown
It already understands the context of like, this is what I'm doing now, this is what I'm going to do next. And is that a safe situation? Is that risk it? What should I do to. And it will change. Right. We, building AI into the existing workflows helps with the adoption. It also helps with the context of the things that are going to come next, not just what's happened before.

00;33;49;22 - 00;34;18;26
Unknown
And then it is, it will change the way that we work. Right? It's going to change what those workflows look like. But there's still going to be places where I need a human decision at this point where I need to have this audit trail here, those things and understanding the full workflow is going to be important in having that context, that that background, the way that that works, the way all that that's I think you need some things that are kind of stable and then some things that are more moving around.

00;34;18;29 - 00;34;40;03
Unknown
And the way I would end up being a jetpack. So I think you need both. I really think you need both like that full system of record, the understanding of the workflows, and then you building AI in where it makes sense but in control, where I think I have found because with clients permission, I go in and play with their data.

00;34;40;09 - 00;35;09;07
Unknown
Just all the time. And where I think, AI is going to be very interesting is I think it does a really good job of finding correlation. But to your point, you still need a subject matter expert to say, is there causation? And, I think that's what's going to be interesting because, you know, in the oil and gas business, there is nobody more confident on the planet than an oil and gas engineer telling you how something works.

00;35;09;07 - 00;35;40;04
Unknown
And the shale revolution basically said those guys were idiots. They didn't know how it works. You know, I mean, that was at the beginning of my career. Oh, a source Rock will never produce. Well, then somebody said, man, let's throw some baby powder in a sauce rock and see what happens. And lo and behold, we triple oil production and so I think being able to, in effect, frack your data and look for those correlations, we're going to find so much stuff in there that on its surface is going to make no sense.

00;35;40;04 - 00;36;01;09
Unknown
But when you really dig in, it's like, lo and behold, look at that. Because at the end of the day, we're only getting 5 to 10% of the oil in place out right now. We got another 90% to go get out if we want, you know. Yeah. And so that next thing, how do you make sure that you're so you're absolutely right I is I mean that's one of its superpowers right.

00;36;01;09 - 00;36;15;27
Unknown
Is understanding the correlations and the information that we couldn't see. But now I want to turn it into a system of action is what does that mean for me, what I'm going to do next. Not like what should I do next. And is that thing that I'm going to do next, is it safe? Is it the right thing to do?

00;36;15;27 - 00;36;32;22
Unknown
What is that next action? And there's a lot of times there's going to be novel scenarios that I, if it doesn't have enough context, doesn't understand it, can't tell you. But I will also say the AI is never going to say John is going to fall from a ladder next Wednesday. Like, that's not the way risk works, right?

00;36;32;22 - 00;36;55;05
Unknown
It's like you can say, what's risky and where you have controls or you don't have controls, but it's not going to actually predict the future. Yeah. You know, my dad's a doctor and, folks, Will is small town doctor, right? So everybody calls dad when they get sick and says thing, you know, oh, I got this. And they always ask, what are my chances of living?

00;36;55;07 - 00;37;18;14
Unknown
And dad always comes back. Well, it's either 100 or 0. You either you either will or you won't. You know? And part of that joke is dad's trying to lighten the mood. But the other part is there's a serious element of you fight every day to stay alive because medical science changes. But to your point, is John going to fall off the ladder?

00;37;18;17 - 00;37;41;08
Unknown
There's not a 65% chance he is. He's either going to fall off or he's not. You know. And so life probabilities help guide us in life. But at the end of the day, they're not outcomes, you know. So absolutely not so. So one one other kind of weird question. While I, I gotcha the it blows silicon Valley's mind two things.

00;37;41;08 - 00;38;01;18
Unknown
One, we go out and we tell Silicon Valley when we're raising money, the energy business uses less than 2% of the data it has at its disposal. You know, heads explode, right? Facebook sells you toilet paper two hours after you go to Taco Bell. They use all the information, right? They use it all. We use less than 2%.

00;38;01;18 - 00;38;27;11
Unknown
The other thing, and I want to know, have you guys done anything to tackle this problem? 80% of the data we have in our business, in the energy business, which I think is, is technically challenging, is anything on the planet, including Elon Musk's sending spaceships up into the air, is captured in a PDF unstructured data. No PDF looks like another PDF.

00;38;27;11 - 00;38;52;15
Unknown
It's a mess. And so we we spend a lot of time throw a lot of energy and resources just at the PDF problem. Yeah, absolutely. There's a lot there's huge information that's that's not captured in a way that's usable. And so we definitely use AI for PDFs, handwritten forms. Right. Like capture that and then now let's digitize it.

00;38;52;17 - 00;39;16;15
Unknown
A lot of what I think I can do right now without having all of your data in perfect order, is help capture good quality information in a way that it's usable. So whether that's PDF scanning form handwritten form scanning, or even, you know, tying into, CCTVs and videos and being able to just collect the information that's out in the world and digitize it.

00;39;16;15 - 00;39;34;24
Unknown
So that way it can be understood. Right. And there's lots of ways we can do that, right? We do a lot of things like also with voice. So if something happens, you know, what we used to ask people to do is okay, now go log in, get your form, fill out this form while you know, while something is happening or remember everything so you can enter it later.

00;39;34;26 - 00;39;51;27
Unknown
But now just do a voice just like, hey, this is what happened, this is what's going on, and you can do it quickly. You can do it in your native language, because sometimes these are really stressful situations and you don't want to, you know, be working to the translation. Do that. And then it's going to log all of the relevant information that you just provided.

00;39;51;27 - 00;40;16;03
Unknown
So that way you know, we have those in electrons and we could do something about it or we understand what it looks like. So I think is really good at capturing information. And whether that's PDFs or like I said, like you got a CCTV sitting there right now and I'm not suggesting this is like, you know, your, you know, an overlord just watching everything, but just capturing the information, right?

00;40;16;08 - 00;40;40;10
Unknown
Understanding it so we know where the risks are and where things are happening. Where there aren't controls in place, where things are going out of out of whack, where you wouldn't expect them to. Is that information? Is there even if a person isn't, to be able to capture it? So there's like all of this information in the world, and I can help turn that into electronic data, that we can do something to better understand it.

00;40;40;12 - 00;41;08;15
Unknown
As the person singularly most pleased that there weren't cell phone cameras in college. Hey, I, I, I will say that is where this is going. I mean, drones are going to fly over fields. Robots are going to go out to Wells and, and, the data that keeps looking for leaks, like it's all happening and it's going to happen more and and you're absolutely right.

00;41;08;15 - 00;41;28;29
Unknown
That's one of the things we preach is, you know, your data is not in good shape. You don't want to do AI. That's like saying, I don't want to go to the gym because I'm not in shape. I mean, I, I was going to be part of the solution in that in terms of cleaning up data, parsing data out of unstructured formats, getting it into structured formats.

00;41;28;29 - 00;41;52;14
Unknown
And, and so it's, it's going to be, it's going to be kind of the wild, wild West in terms of getting that all done. But it's been fun. Yeah. I think of, the analogy that I think of around like, what's an organizational approach to AI? It's like learning to drive. So you weren't going to hand a teenager the keys to a sports car on a dirt road in the middle of a snowstorm.

00;41;52;14 - 00;42;11;22
Unknown
Like you don't just say, go right, you're going to get experience. You're going to like there's experience that you learn as doing. Like no one can just teach you. You can't read a book about how to drive and then just go out and drive, you know, an F1 race. So you need to get experience to get a feel for it to to build up that understanding.

00;42;11;22 - 00;42;30;21
Unknown
And that's what we need to get our organizations doing using AI in ways that are safe. Right. So it's like your, your partners, your, you know, the Clyde's the core. They're they're your instructors. We're going to help take you on the safe roads. We're going to build some guardrails for you. We're going to tell you for the intersections to look out for and go like get started.

00;42;30;23 - 00;42;53;27
Unknown
And get that experience at the same time, though, if there isn't already a highway, which most organizations don't have, you need to start building that highway. You need your IT teams to build those highways, to build the infrastructure. So that way, once you're ready, you can take off and drive. You can go fast. You can just go now, I know in Houston, like maybe you're not going fast on the highway because it's like 17 lanes of like maybe just cars not moving.

00;42;53;27 - 00;43;23;02
Unknown
But generally what I mean by highway is you can get farther, faster. And if you're not doing both, then you're going to get left behind. Yeah. No. Absolutely. So kind of closing question for you and I'm even happy to go first if you want time to think on this okay. What. And you kind of alluded to it earlier, but what are we talking about when we redo this podcast in five years that wasn't even on our radar screen today.

00;43;23;03 - 00;43;43;23
Unknown
No one's talking about today. Yeah. You go first. Let me think about that okay. So I, I got I got this question, last night on the AI panel that I was on, and it was I felt so bad because it was a, a sales guy from base and me, the podcaster and then a lawyer and and an accountant.

00;43;43;23 - 00;44;03;23
Unknown
And they were just looking down there going, we should not be on a panel with those two loud mouths. So we I wound up speaking way too much. But my my answer was, I say this, that I love America, I love our can-do spirit. I just spent a week over in Italy and Italy's great, but I will never be a European.

00;44;03;28 - 00;44;46;12
Unknown
God bless America. Red, white and blue. But I do think the thing we miss in our Go-Go entrepreneurial spirit over here is our mental health stuff. We are so bad about that. And I think one of the things in five years that we will have overlooked is just the mental health aspect of how addictive building applications can be when everybody has collide in the energy business and they're spinning up their own applications, the core Collide joint venture on safety, spinning up applications.

00;44;46;15 - 00;45;13;05
Unknown
God forbid it's all clogged code or codex or whatever. I mean, people can literally sit in front of a computer for 2440 eight hours without going to sleep. It gets so addictive that I don't think we appreciate the impact that's going to have. It can be as addictive as drugs, as alcohol, as anything else out there. And so I think it's going to be a bigger epidemic than, than we realize right now.

00;45;13;05 - 00;45;33;06
Unknown
We're starting to see little bitty signs of that with, with folks that are like, I mean, I think quad embedded in the in the latest, version. Hey, you need to go to sleep, walk away. So that that that's my story. In five years, that maybe we're not telling today. Okay, I like that. I can see that.

00;45;33;06 - 00;45;46;18
Unknown
And I'm going to say there's the other side of it as well, in that it is going to change the way that we work. So right now we're talking about AI to make things more efficient, to make things faster. So, you know, what can I do for us? I think in five years from now, the world looks very different.

00;45;46;18 - 00;46;20;24
Unknown
And the types of things we're doing. I think there's still going to be doctors and experts and just professionals that are. But what they do and how they spend their time will be very, very different. And it's going to require a whole a different skill set than what people have today. And if we don't train people on that information, then in how to do it, there is going to be the other side of the mental health crisis of people not knowing what to do with themselves, people in despair because they don't have a job, because they because the way they did their job before is no longer available.

00;46;20;27 - 00;46;44;07
Unknown
And so there's going to be a whole world of different types of jobs. And we need to have people trained and educated and to know how to take advantage of those things. Otherwise, we're not going to have enough of the people to do the things that we need, and we're going to have a whole bunch of people that that don't have, don't know where they fit in the world, don't know how to, you know, people want to work for the most part, right?

00;46;44;07 - 00;47;02;26
Unknown
Like, I'm looking forward to retirement, but like also like there's like a purpose, right to to going to work to doing things people need. You know, I think there's lots of, lots of people that are looking at the AI future talking about, you know, just a general income. And just like, what do we do, like the universal income?

00;47;02;26 - 00;47;17;00
Unknown
What do we do for all these people who aren't going to be working? And I do think there are jobs and there will be jobs for people, but they're going to look very different. People will need to be educated in how to use that and how to do those things. So that way we can kind of keep going.

00;47;17;00 - 00;47;47;23
Unknown
And there's mental health to that. There's just overall, I mean, that has so many downstream impacts of just income and society. And what what does it look like now? I really do think is going to fundamentally change, no one knows exactly what that looks like. Yeah. So it's kind of scary, but it's also really exciting because it means, I think that we're on the precipice of doing so many more things, doing them so well, doing this and giving people more time to spend the things, the problem, solving the things that they want to do.

00;47;47;25 - 00;48;09;04
Unknown
But it's not going to just happen. We've got to we have to look towards that and prepare, our employees ourselves for what it changed. Futures look like. I love that because I'm an optimist on all this. I, I truly believe it's going to be. I think every technology ever invented. It's made the world a better place.

00;48;09;06 - 00;48;32;27
Unknown
I could even make the argument nuclear bombs have. Because if you think about it, until Russia walked into Ukraine, at least we kept Europe for having ground wars, you know, for 75 years. So one thing that came from our report that I was supposed to mention, I do think is interesting. Oh, lay it on us. What's that? I said, lay it on us.

00;48;32;29 - 00;49;04;04
Unknown
So, you know, there's all this resistance to using AI. There's also people want to use AI. But organizationally, what we did the survey of 2000, different, leaders across the world around DHS. But one of the things we asked is, how much are you using, unsanctioned AI or shadow AI? And what we found is 95% admit to using AI in a way that their organizations don't condone, right?

00;49;04;06 - 00;49;21;21
Unknown
Using tools that are not provided by their organization. So what does that say? People actually want it. They want to use it. They're finding some value in it. But that's happening off book. You don't see it. You can't audit it. You don't know if it's safe. You don't know if they're sharing information. They shouldn't. You don't know how that's being used.

00;49;21;21 - 00;49;52;26
Unknown
That is incredibly scary, but also exciting. It means there really is the appetite where we went from before. People not really want to use it. They're using it, but not in ways that are necessarily with us as an enterprise, as an organization would want them to do. So give the people some tools that they can use. I think that they're using these of tools because they haven't been given the slides or the quantities, the AI tools, to help them give them a sanction tool, train them on how to use it, and then you'll have better control and they'll be happier.

00;49;52;28 - 00;50;14;13
Unknown
That's interesting because we started the panel last night with, the moderator said, okay, who here is using AI in their personal life? Raise your hand. And 95% of the hands went up. Okay. How many people are using it at work? And a lot of the hands went down and then I said, hey, Liz, let me ask a question.

00;50;14;16 - 00;50;31;17
Unknown
Who here is using it at work? Just not going to admit to it. And most of the hands went back up. And so actually that's exactly that. There's real use for it. But we just we want to we do want to make sure that it's being safe and that it's not, you know, hallucinating that we're not putting data out there, that we don't want.

00;50;31;17 - 00;50;58;04
Unknown
So organizations, employees are looking for the tools we need to give them, tools they can use in a trusted way. If they're taking company data and just dropping it into a personal ChatGPT or a Claude or Grok. I mean, your data just left your company as as well as AI is now training on your data. And, so you really do need the enterprise guardrails in place, etc..

00;50;58;04 - 00;51;21;13
Unknown
And, you know, the thing about the energy business, and I want to say this very carefully because I don't view this as reckless or negative, but to make any money, you have to be over your skis. I mean, if you bought an asset, you paid more than anyone else on the planet. When you drill a well, you putting a hole where no one else has ever put a hole before.

00;51;21;15 - 00;51;41;29
Unknown
And that's the only way to make any money. And I do think part of being over your skis today is using AI. But to your point, you do need some guardrails so that you don't fall down the mountain. Yeah, that's right. But the controls in place. So yeah. Awesome. Well again you were great to come on. This was fun.

00;51;42;07 - 00;52;14;29
Unknown
Yeah. It was fun. Yeah. And, anytime y'all want to nerd out and, talk tech stacks or anything like that. Love to share notes. Not that there's necessarily anything to. I mean, at some point, I'm sure we'll have an overlapping client. We'll need to figure out how to talk to each other. But, you know, like I said, any of the tech stack where we've done something that you guys maybe have struggled with, love to share because, yeah, at the end, at the end of the day, like I said, got fired because we didn't talk about spacing.

00;52;14;29 - 00;52;34;07
Unknown
Not going to repeat that again. Yeah. And the information sharing because it's all going so fast. I'm sure you've learned things that we haven't learned yet and vice versa. And vice. Yeah totally. Now we we we've got a couple of, couple of the oil and gas companies have been pretty forward thinking on AI and built teams and built a lot of stuff internally.

00;52;34;09 - 00;52;52;14
Unknown
And yeah, we just got to nerd out with those guys all day long. How'd you solve this? Oh, really? We solved it by doing this. Yeah. So, Amanda, this was so cool. I appreciate you coming on. Thanks for having me. It was. It was fun. It was a great kind of great conversation. How do people, get in touch with you?

00;52;52;16 - 00;53;02;07
Unknown
So contact cord econ. There's, you can go through that and there's, you know, contact me kind of thing. And if you want to get in touch with me, they can reach out through their.