Tim (00:00:00) - Usually I think solving a pain point is the number one way to get people to adopt something. But getting them over that threshold of, hey, once that pain point is gone, what is my job? It takes a little bit more of that inspirational piece. So yeah, I think they're both very entangled there.

Ariana (00:00:22) - Welcome to Secret Ops, the podcast uncovering the world of operations. One episode at a time. I'm your host, Ariana Cofone, and today's guest is Tim Tutt, CEO and co-founder at Night Shift Development, a company which focuses on helping organizations make sense of their data primarily through their core product, Clear Query. This episode dives into all the technical questions that I know you're curious about but aren't quite sure what it is. We're talking about artificial intelligence, augmented intelligence, augmented reality, cybersecurity, and many, many more pieces of how that fits into the world of operations. Tim is a true joy to speak to, so let's dive in. Tim, welcome to Secret Ops. I was really looking forward to this episode because cybersecurity, technology, data analytics, I mean, your experience really runs the gamut here.

Ariana (00:01:21) - So we're going to dive into all these super yummy topics and how they relate to operations. But I guess first and foremost, welcome before I nerd out.

Tim (00:01:30) - I appreciate it. Happy to be here.

Ariana (00:01:31) - Now, before we jump into my millions of questions, let's start out with your journey and how you got to where you are today. So do you mind taking us through that?

Tim (00:01:40) - Yeah, absolutely. So, you know, my background is very, very weird. I've done a whole lot over my career, so I started off getting into technology when I was very, very young. I remember way back in the day, I used to have my mom take me to bookstores so I could go and read about how to write code, how to figure out how to do this on my own. Then I'd go home and try to test things out. I ended up building my middle school's website when I was in middle school. It was a very weird career, so I've always been very hyper interested in technology and how things work and how we can build those out.

Tim (00:02:15) - As I kind of grew up, I did a handful of things in high school. I worked for a group that was in my local area, my local county, where we were designing a center to help students get jobs, help teens 14 to 21 is really kind of what we focus on, help them get jobs. And at the time, I was 14 years old. They wanted a youth advisory board to build this thing out. So we did everything from interviewing to helping to go and collect all of the office supplies, all the computers going to get donations to kind of get the center up and running, eventually kind of dovetailed that into actually building out a little mini monster.com where people come in and provide their resumes. And we would do job matching type things for them, you know, back in the day. Then I went to school for computer science at Virginia Tech, worked at the college newspaper there, then had an internship with a company called BAE Systems. That's an interesting start of my career because at that point during that internship, I wound up getting a government clearance, started doing work for the government through my internship there which turned into a part-time job during the school year, full-time on my breaks type of thing.

Tim (00:03:38) - So it was nice because it paid for all my fun college parties. Kept rolling through there, once I left, I worked for a company called Indica Search and Discovery Company. Product company was doing product development there for government.

Ariana (00:03:55) - Actually Tim, quick second, because I think search and discovery might be new for some of the listeners here. Can you just describe what that is exactly?

Tim (00:04:01) - Yep, absolutely. So helping to sift through data to figure out how I find what I need, how do I discover the information that's important for me, whether that falls into the category of HR data or financial data, just really searching the data. So anytime you go to Google.com, think about that for your internal business, right? I love to use the example of Amazon.com when I talk about Endeca in particular, because it's probably one of the favorite examples. Whenever you're on Amazon.com, you're looking for, you know, some new TV. Well, I want to go and I want to find a TV that's this brand and, you know, this screen size.

Tim (00:04:39) - So you have this faceted navigation type thing that helps you drill down into exactly what it is that you're trying to find. So I want a Samsung TV that's between 57 and 60in. And, you know, I also want the highest quality. So you have all these filters that you can drill into. But we start that off with an initial search of I'm looking for TVs now I drill into those things Endeca did the same thing, but for your business data. So whatever you're looking for there, that's what we were helping people to kind of help surface in general. So search and discovery is really just helping people find and discover their data.

Ariana (00:05:14) - What made you get into that? Because that immediately I'm like, oh, yummy, Like systematizing things, finding things. But I don't know if people…I mean, probably now people have more of a consciousness of thinking about that. But I don't know if it was when you were doing it, if it was in the societal consciousness of finding your data and using your data.

Ariana (00:05:33) - So what drew you to it?

Tim (00:05:34) - Sure. You know, so it was interesting that actually happened completely by accident. You know, I had always been in the technology space and an interesting, you know, hey, how do we build systems to help make things more efficient? That's one thing that you will find about me and will probably discuss this multiple times today is, I'm all about efficiency. How do we automate, how do we make things simpler? So, you know, through my development background, while I was actually looking for jobs, I actually had a headhunter follow up and find me, you know, said, Hey, let me introduce you to this company Endeca. You know, here's what they do. And search and discovery really wasn't on my mind, but, you know, helping make sense of and organizing data had been something I had done before. And I understood kind of the core concepts and understood how to build systems for that. And this was something where I was looking at, hey, how do we make this easier on non-technical humans? And that's where I've always kind of kept my mindset.

Tim (00:06:31) - So this was an interesting space where, hey, got to find a thing where we can make this easier for people that don't necessarily have the deep technical skill sets. But it was also a new area for me, so I happened to fall into that one at the time and actually fell in love with it there, fell in love with the whole concept of search and discovery and data in general. I think it brought out something that was there underlying before, but I didn't really know it was there because I was always thinking about how to use data, how to collect data. But I never really thought about data as a product or a software career path total.

Ariana (00:07:07) - I mean, when I'm speaking to people in college or in high school and we're talking about what their future career could look like, I'm like, your job doesn't exist yet. In like three years is going to exist. I can't tell you what it is, but like it just it's going to happen. I think that's kind of what you're talking about is like the technology sort of caught up with the problems and the things that you were trying to solve, and then it gave a terminology to it and you're like, Yes, this is the thing that I want to do.

Ariana (00:07:31) - And sort of all came together.

Tim (00:07:33) - That's absolutely right. So yeah, moving forward from there, you know, and Endeca wound up getting bought by Oracle years ago and then moved on, did some other things and wound up at a company called Bogart Associates doing government contracting. Still focused in that large scale search and discovery area. So and when I say large scale, I'm talking about massive, massive amounts of data just flowing in. How do we sift through it? How do we find the needles in the haystack, if you will? And it's building systems using a handful of open source technologies at that time. So I had kind of shifted away from, you know, hey, I have a proprietary product that, you know, is supporting to build and do those things to using open source technologies to kind of build a solution. One of those was a product called ElasticSearch got very, very deep into leveraging that and deploying it across. A lot of my government clients became an Elastic Certified engineer so that I could kind of do that very effectively.

Tim (00:08:33) - And while at Bogart, you know, one of the roles that I had supporting government customers was me playing the middleman between my end users and their data. So we had a bunch of analysts that we supported and those analysts would come to me and a handful of other people and say, Hey, we've got this question we're looking for where a particular individual is or how do we get access to a particular location? How do we drill in and find those things? I then had access to our massive supercomputer. We'd go run queries, write queries against that, come back with some data and say, okay, great, here's the answer to that question. There was always a follow up question. Okay, well great. Now how do we get to…and it was just constant back and forth, and that was actually where I kind of ran into this mode of I hated doing the back and forth of, hey, question…Okay now we have a follow up. And I'm always a middleman between my end users and their data.

Tim (00:09:31) - If you talk to any developer, most will tell you we're all lazy, if we have to do anything more than once. We're just going to automate it and then never do it again. I started building out scripts for the general questions that people would ask me, so I would go and write these scripts so I can run this and plug in data and great, here's your answer. But it still felt like I was playing this middleman role, and I hated that whole concept and wanted to get to a place where we could help people get access to their data on their own, get those answers on their own, and then come to me for the more complex problems. Let me do something a little bit more interesting, a little bit more fun from my perspective, but also enables them to get to their answers faster because most of those things they should be able to do on their own. And that's actually when I kind of took a big step back, and myself and my co-founder went and had lunch and over drinks, decided we were going to start a company and we were going to build a product to help solve this problem.

Tim (00:10:32) - And that's how Nightshift started about six years ago. And we're coming up on our six year anniversary this year.

Ariana (00:10:41) - I got to ask because I'm just curious, where did the name come from? Because I think it's such a cool name, but give us the background around the name?

Tim (00:10:49) - Yeah, absolutely. So when we decided to start this company, we were both still working our full time jobs, had bills to pay. And we said we're going to work our full time jobs, come home and work on product at night and wait until we could actually start the company and had revenue enough to get going on our own. So the company name was Nightshift development because of that, because that's what we were doing.

Ariana (00:11:13) - Cool. Love that history. Oh my God, that's so fun. You have lived during such an interesting time and how technology and just our knowledge around data has changed and also policies and you know, I mean, it's constantly…I feel like in operations, my job is constantly changing every day, which is fun.

Ariana (00:11:34) - It's also exhausting. So when we talk about operations, like I said in previous episodes, the commonality I found is people process and tech. So obviously you've got the technology component real on lock. So I'd love to sort of start with the people aspect because it's clear from your history in your career you're driven to solve problems for people, you're driven to help people create efficiencies in their life from when you were 14 all the way to today. So why do you believe in democratizing technology and data access for people? Like where do you think that drive comes from?

Tim (00:12:12) - You know, it's a super interesting question. I think a lot of it comes from I'm always looking for what's the easiest path for me to do something. And while, you know, I have these interesting tech skill sets, not everybody has those things. Not everybody has the time to go and learn everything. Things are getting a lot easier these days, but I think before there was this magic gate between users being able to do the things that they wanted to do and to drive things more efficiently.

Tim (00:12:44) - And I wanted to kind of help bridge that gap. Technology isn't just meant for the super deep tech people. It's actually meant to make things more efficient. So that's just…it's always been the mentality I've had is making things more efficient, always, you know, driving things to be simpler. You're right, I did grow up in an interesting time. We think about and maybe I've had influences. I don't think I've realized before, but if you think about it, I grew up in the time right before the iPhone became a thing, so I used to have old sidekicks and, you know, flip phones and those types of things. And then all of a sudden the iPhone comes and transforms the entire world and it's just simple. You know, most Apple products, they just work in general and there's that ease of use where all of a sudden it's like, hey, as a human, I don't really have to think about it. And you've even seen that evolve since the iPhone came out.

Tim (00:13:36) - Like, I know now when I get a new iPhone, I literally just take the new one out, start the setup, and I set them next to each other and it just transfers everything for me. And I'm like, well, that feels like magic. And that's exactly what I think technology should be for most people. This should feel like magic. It should just work and be easy because that just makes your life easier and then you get more time to work on the more interesting problems that require a little bit more brain power.

Ariana (00:14:03) - Definitely. So in a previous role that I had, I was teaching emerging technology to audiences of varying technical levels, and I found that there are people who are excited for this change and who are amped and they want to know and they want to learn and they want. And then you get the other side of the coin where people are like, nope, don't want this is too…how do you navigate that human element in what you're doing? I mean, I can assume that there's probably a massive educational component to the work that you have to do just to explain to people why they should be doing something.

Ariana (00:14:39) - But how do you navigate that through your day-to-day?

Tim (00:14:41) - Yeah, you know, it's a conversation that comes up every, almost every day, especially when doing sales. You know, for us, we actually fight that battle on two fronts now because we fight it with the more technical individuals because they're like, well, you're going to be taking away my job because this is my job to go and do these things for these people. And then you're fighting me on the other side because people are saying, well, I'm used to doing it this way and I know how to do it this way. Or, hey, if this becomes more efficient, then they need less of me. The way we always kind of frame that is what we are doing is helping to augment your job, to make you a whole lot more efficient so that you can then move and start focusing on other things. So it's not about taking your job away. It's about augmenting your job so that we can now start doing more interesting things and start driving things in a different way.

Tim (00:15:31) - This might sound a little pie in the sky, but you know, this is one of my biggest things is…I think the more efficient we become as humans, the more we can get away from doing these mundane tasks and we can automate these things. The faster we're going to evolve as a human species and we can get to those cooler things, those sci-fi things that we all grew up on. I mean, we're in 2023 now, I think what was it, The Jetsons? We were supposed to have, like flying jetpacks, right? So we're still missing some of those things that, you know, hey, how do we accelerate that? I think it's interesting now because we've now hit this interesting point in just the last nine months or so with generative AI chatGPT, everyone getting super excited about that. My sister just yesterday posted a post about how she couldn't believe that her brother has spent his life writing code because now she's letting ChatGPT go and write code for her. And she's like, oh my God, this makes my job so much easier.

Tim (00:16:29) - And I'm like, I'm glad you're looking at that. And she's like, I'm so much more efficient now. And I love to hear that people look at it that way because it should be a driving factor for you. It should be something that helps make your life more efficient. So now you have more time to go do the other things that you want to do. And she's looking at it and saying, great, I can automate my real estate business by, you know, automating some of these processes in a way that I hadn't been able to before. So now I can do more and then I can go out and do other things that I'm interested in doing.

Ariana (00:16:59) - Well, this gets into what we talked about before we jumped on recording, which is augmented reality. So augmented intelligence, all of these sort of like…it's like a half step to what we're doing today. So can you explain what is augmented intelligence in relation to artificial intelligence and sort of what that manifests like in processes and in technology?

Tim (00:17:23) - Yeah, absolutely.

Tim (00:17:25) - So augmented intelligence is really more about taking the data that we do have, everything that is available to us and providing that, providing that in context to what we're doing. And it's interesting because, you know, we didn't talk about this before, but you mentioned augmented reality. And I think there is a really interesting element to this, right? Because there are companies that I know of that do this right now where they are looking at, hey, how do we take augmented reality and we've all seen those movies where I'm walking down the street and it's showing me, oh, hey, there's this store, and here's exactly what it is. Here's the price of something that you're looking for. This is taking data that we have access to and providing that in a way where I don't have to go look for it. I don't have to go discover it. It's now being pushed to me. So augmented intelligence is really about providing that extra context for you as you do the normal day to day of your job as you're asking questions. Here's some other insights that may be interesting and may drive you down a path that you weren't thinking about before. So that's really what the whole augmented intelligence space is about. But, you know, there's an interesting blend with augmented reality, too. I mean, Google Glass tried to do this years ago where you're walking down the street and hey, it's going to do some automatic object detection and maybe provide you some other insights. There's a product that I've seen that will actually, as you're having a conversation, it will do the speech to text translation and then go and search for things for you automatically. So if I mention a restaurant, a store, and it'll just pop up and show, oh, here's where that store is and whatnot for the other users. So you're getting that extra context without having to go back and ask that user or you can drill into that type of thing. It's hyper interesting stuff and I am loving to see how that starts to blend into the rest of the world. It is a little bit different there because all you're starting to look at how do we mimic human brain patterns? How do we mimic how we think about things and do the things that a human would normally do? Which is slightly different because AI leverages this additional context and all this data but it's not just that it's a lot more. It's trying to mimic how we would process things, which is where generative AI space starts to get really interesting because now we're seeing, hey, I can very closely mimic how we would write or how we would communicate, how we would respond to things.

Ariana (00:19:56) - Do you think when we say artificial intelligence that most of the time we're actually referring to augmented intelligence at this moment in time?

Tim (00:20:04) - It's interesting because I think we…I have multiple thoughts on this.

Ariana (00:20:09) - Go for it, I can't wait!

Tim (00:20:12) - Thing one, I think we are still very, very far off from true artificial intelligence. You know, we are getting much closer. But even in the generative AI space. We're still light years away from it being able to do these things on its own. You know, there's a whole field now that’s popped up in the last nine months…prompt engineering. How do we prompt the computer to know, and provide all the context that it needs to be able to respond in the right way type thing.

Tim (00:20:44) - And that's it's basically we're telling the computer what to do. That's where we are. We're still telling the computer what to do. We're providing the instructions. That's what machine learning is. But it's much more efficient at putting those things together because now I can say, hey, write me a sonnet in the form of a J.K. Rowling, you know, chapter from Harry Potter or whatever it is, and it's going to come back and do that because it has all the data and context that it needs to do that. But I have to tell it to do that. I have to tell it exactly what I want it to do in this generative space. So I think sometimes it can be mixed up for most people because most people don't understand the difference. Right? Augmented intelligence can also seem like magic. It's like, oh wow, you just told me I had a 47% spike in sales and I didn't even know to ask that question. But that's a great Intel for me and now I want to go and drill in.

Tim (00:21:37) - That can seem like magic to people and that can seem like AI, but really it's just providing that data. And if you don't know the difference between the two, sure. And this is the other big thought I wanted to kind of throw out there, sometimes I get a little irritated because you see a lot of companies almost abuse and leverage that and they say, oh, we're powered by AI. And it's not really AI, it's just, it's great marketing material. It's a thing that helps them sell and people are fascinated or interested in drawn to those things. And if you don't know any better, great, I'm going to run and go with that.

Ariana (00:22:12) - Totally. I think we saw that especially within the crypto blockchain space. I was teaching blockchain at the time that everything was like going bananas a couple of years ago and it was like fueled by blockchain technology. And I'm like, get out, get out of here. You know, like like it was, it became this sort of marketing buzz term because you could get investment and users and all these different things on it.

Ariana (00:22:32) - So it is hard, especially as we start to get more nuanced with our technology being able to untangle those things, because unfortunately how it's being marketed is confusing the general public.

Tim (00:22:44) - Absolutely. It's one of the conversations that I have with my marketing team because they were very heavy on me. Like we need to be saying something about ChatGPT and generative AI, and I'm like, I don't know that we do. Maybe we can say something about it, but let's be realistic about how we actually leverage it, how we view these things, and let's maybe provide some educational content on it. So that's the way we've been kind of operating. Sure, we'll talk about it because yeah, you have to ride the train if you want to stay relevant these days. But let's do it in the right context and not be abusive in a way.

Ariana (00:23:17) - Yeah, it's got to be hard to cut through the noise. And also because of what you do…it is literally entangled in all of that. So it's like yes and no.

Ariana (00:23:26) - But maybe and let me explain. And it's sort of that educational stuff that we're just starting to understand. Like, I remember my parents, we did the AI generated photos. I mean, I think my mom's brain just exploded, you know, like just seeing her young self with flowers and like a renaissance lady, you know? And it's interesting explaining what those things are to someone that grew up with like a black and white color television and radio and it's like, what is even happening? You know, we're there. There's so many different varying degrees of where we're at from an educational standpoint because it's just going so fast, like it's just happening incredibly quickly. So I would love to touch on operations because I think what got me excited was that you are efficiency focused and you've got that sort of DNA in what you do. So can you explain how operations and technology fit together within your world and what you do?

Tim (00:24:22) - Yeah, absolutely. I think it fits together in A) the product we provide, but also B) in our own internal business.

Tim (00:24:29) - So you know, the product we provide, it's designed around helping to simplify the whole data analytics process. How do you take your data, find the answers that you need, how do you ask questions? And that's really what we've been focusing on the last six years, is how do we enable people to ask questions and natural language and get back answers to what they need on their data. So that applies in every area of operations from finance to HR. You know, hey, what's the average age of employees that, you know, leave our company within three years? You know, is this something that we need to look into? Okay, great. Now what's the average score of their performance ratings for these employees? You know, are they high performers? Are we losing lots of high performers? Is that something we need to go and look at? What are the trends of those things over time? So our product is really designed to help you ask those questions simply.

[00:24:22]- I tend to blend it. I used to say, it's Siri meets Tableau, but Tableau is actually a big competitor of ours now. So we now say, hey, it's Siri meets your data. You know, it's how do we help enable you to ask these questions, simply get back these beautiful visualization charts so that's how our product and our technology blends into the operations space. It's how do you do that internally from an operations standpoint? We are always looking for things to make everything we do more efficient. That's everything from our sales operations, how do we track our leads? How do we track where they are? We use HubSpot for kind of moving that through the thing. We also use HubSpot for our marketing funnels. How do we make sure that we're sending out marketing emails to all of the right people at the right times? We're segmenting things appropriately. On the finance side, we use a combination of tools for A) how do we make sure we have a tech budget that our employees can use? So how do we make sure we're able to track that in an efficient way? And I'm looking for the most efficient technology.

Tim (00:26:30) - So we actually use a company called Brex that gives you a corporate card for those employees so we can track every expense they're doing and they have an easy way to take a picture and upload their expenses. And now we don't have to do that manual process of…or at least we've minimized the amount of expense reporting you have to do. So the way I look at tech and operations is it's designed to make it easier for our internal team having to do those things– easier. They spend less time on doing the mundane manual tasks and can focus more on the more interesting things that we need to do on a day-to-day basis.

Ariana (00:27:04) - So I want to talk about ClearQuery because…so in my head as an operations person, I do exactly what you just said. I'm targeting all the different departments, understanding where the data is starting into my pipeline of operations, how it threads through, where it needs to be used and automated. So when it comes to ClearQuery, which is the main product that you all have developed, where does that fit in? Because man, it would be awesome if I could just say something that I want and instead of having to do all of that manual labor, just be able to have answers that are a lot faster, especially because when you're in operations or COO, there's so many things you need to have an attention on. So talk to me about how that product works within the ecosystem.

Tim (00:27:47) - Yeah, absolutely. So it fits in each and almost every area, right? So one of the things that we try to do was be very generic with the product so that we're not targeting one specific type. We're not just targeting sales, we're not just targeting HR, we're not just targeting, targeting marketing, we're targeting all of those things. It's really about how do we help you get the answers from your data. So wherever that lives, whatever that data is. We have a lot of government use cases as well, a lot of cyber security use cases. So, I can dive into each one of those, but we actually use it internally anytime we're about to go to a conference, we'll usually get a list of, Hey, here are the other companies that are going to be there, people that are registered, and we can go and augment that with other data to say, okay, great, based on the company and the job title, this is probably the person, but we can augment with, Hey, here's the revenue size, the size of that company.

Tim (00:28:43) - And now our sales team has a bit of a target that we can throw in a clear query and say, Hey, how many executives in the finance sector are going to be at this be attending this conference, or what are the top sectors that have senior decision makers so that we know who we want to go and target once we go to this conference? So that's one of the ways that we use it internally. And again, you know, this applies, you know, if you're thinking about sales or you're thinking about marketing, how do I even segment and break down my user base? We have a capability that we call Automated Insights, which will automatically drill into your data and highlight and surface for you the breakdown of how things are kind of spread across the board. Maybe it's by job title, maybe it's by industry. You know, just using that same example again, if I move into an HR context, maybe I'm looking at, Hey, let's look at our top performers.

Tim (00:29:40) - How many of them have college degrees versus not? How many of them have worked other jobs? How many of them have 10 to 12 years of experience versus 1 to 2 years of experience? And how do we use that to determine how to best impact our business? How do we identify those people and maybe replicate what they're doing. One of the really interesting use cases that we found is, if you're looking for people that are searching for data on a day to day basis and that's their core job is being good data analysts and good stewards of data. If you actually look at the analytics of how people are searching that data. So if I look at the analytics of how my top performers are actually running through it, yeah, it's a little bit meta, but now I can start to identify, okay, here's how people are doing this. Now I can go and retrain everyone else on how to best become someone that can drill into their data in a really interesting way.

Ariana (00:30:42) - My brain exploded! I think when I talk about operations, if you are an operations or technology, it looks incredibly boring. But I think what it's very hard to explain is how incredibly creative it is. Like that is an incredibly creative way to use technology and data to understand human behavior, to help other people and to become more effective. And then they can do other things. Like that's where technology becomes your canvas to be able to paint on and you can have all these different paints to use data analytics, natural language processing, all these different things that you can use to try new things and reinvent the way that you're doing what you're doing today. Whoa! Oh, my gosh. So when we're talking about operations through the lens of technology, through the lens of these products, what do you think that people just get wrong about this? Because obviously I'm like a super fan of these types of things and this type of thinking. But for people who aren't, what do you think they just get wrong about it?

Tim (00:31:45) - Yeah, I think we touched on it a little bit earlier, but this is the one thing that I run into so often is people are always concerned that, hey, this is going to remove your job.

Tim (00:31:54) - It's replacing you, and actually it's not meant to replace you. It's really meant to help augment what you do. You move away from those mundane day to day tasks, but you also just…it helps you get to that more creative part of your job, right? Because there are creative aspects to all of these operations tasks. There are other things that you should and could be doing if you have the room in space to actually do those things and you've removed all of the manual, Hey, I have to do this day in, day out type things. So that's really one of the big things that I think people tend to miss about operations and tech is it's really an augment, not a replacement by any stretch.

Ariana (00:32:38) - Do you think that the only way for people to really understand is to kind of go through the emotional roller coaster of feeling what is possible? Like I remember specifically working with certain teams and me sort of telling them, Oh, we can automate this and this can trigger this.

Ariana (00:32:53) - And then when we do this. It's kind of like going a little bit down the rabbit hole of the dominoes that you can do in operations when you have these kinds of tools at your disposal. And there was such resistance because I don't even know if I made sense. I probably wasn't even speaking English, you know, like I wasn't even communicating in a way that they could understand it. But then once they saw it, then it was like everything sort of came into focus. But I had to kind of go through a lot of teeth pulling to get there. Do you find that too? Like people have to experience it, to understand it, or are you seeing that adapt more?

Tim (00:33:28) - I'm seeing a little bit more adaptation these days. Generationally in truth, right? It's very different, right? You know, people that grew up with technology can tend to see it a lot faster, right? Whereas people that hate technology started coming in and seeking out other things.

Tim (00:33:46) - It's a very different kind of mindset. What I have found to be probably the most beneficial way for us to kind of go in and pitch and sell these concepts is really putting myself in the mind of what does that person do on a day-to-day job? So understanding, Hey, what is your role? What are you doing? Which means that I have to learn a lot more about what their jobs are so that I can actually speak their language. Okay, you're probably doing X, Y, and Z day-to-day. You know, Hey, here's some random thoughts and ideas that I had just thinking about this, you know, in the five minutes that I had. And that usually triggers something in them or like, okay, yeah, that's cute and cool Tim but I've been doing this for 50 years. I've actually got another idea based off of what you said, but thanks for getting my brain going on this type of thing. So sometimes it's a little bit of that education and being able to speak the same language.

Tim (00:34:34) - And that's really one of the things that we try to do as efficiently as we can when we're going in and talking about, you know, how technology can make things more efficient.

Ariana (00:34:43) - That's a great approach. I also think I'm trying to think of ways that I've been able to get there faster is like when you talk about a pain point that really hurts, and then they're like, Yeah, let's fix that. I really hate that thing. And then that seems to kind of lead and kind of l allows you to move faster through the process of adopting it because they just want to get that pain point done. So that's like on the other side of, you know, you're going the more inspirational route. And I'm sort of like, let's solve that thing that's a pain in the butt for you. But both things are entangled, I'm guessing.

Tim (00:35:11) - Yeah and I think both things are entangled, right? So usually it's the, hey, if we can get that thing out of the way, here's some of the other interesting things that you could do.

But they're very entangled. Yes. Solving that pain point is usually, I think solving a pain point is the number one way to get people to adopt something. But getting them over that threshold of, hey, once that pain point is gone, what is my job? It takes a little bit more of that inspirational piece. So yeah, I think they're both very entangled there.

Ariana (00:35:43) - So I want to dip into a question for the more technical folks that are listening out of pure curiosity on my part, which is, what is the technical stack that you have worked with over the years and how has that adapted as technology has adapted?

Tim (00:35:56) - My tech stack has evolved over the years quite drastically. I used to be a backend Java developer, pure Java, building spring applications and those types of things eventually moved into web application development using JavaScript. And, not until recently Node.js, React.js types of things, my data stack has varied. It's always been a little bit different for me.

Tim (00:36:24) - Endeca was one of those, I've used the Oracle MySQL databases, relational data stores back in the day, and I moved to using Elasticsearch almost exclusively for way too many things. Abused technologies and ways that they were not designed. And then I make them work in the way I want them to work. But Elasticsearch is definitely one of those in terms of end data storage, but, you know, run the gamut of the full MySQL end to Node.js front end. I tend to stay in this web application stack, but I've also done the mobile application. So that's a very interesting shift in mindset and how you kind of develop when you're looking at iPhones. It's Objective-C. When you're looking at Android, you're talking about Java, and it's a whole different game.

Ariana (00:37:12) - I had a mental block with that. I tried to do mobile app developing and I was like, Nope, back to web development land for me.

Tim (00:37:20) - Yeah, I did it for a little while and had some personal things that I did.

Tim (00:37:22) - But yeah, web development felt so much better for me. It's just easier. And that's kind of where we've stayed as a company in general.

Ariana (00:37:31) - That’s so interesting. So that's just if you're listening to that and you're like, all of those words make no sense. Essentially, they're just different languages that from a technology standpoint, you can write technology in different languages and different types of applications, whether you're creating a website, a mobile application for your phone or something else, requires different knowledge. So especially, I think what's evolved in the last couple of years is again democratizing, making those languages more approachable, more easy to understand from a language standpoint. Like a lot of the older languages were very technical, like a lot of syntax. JavaScript has a lot of semicolons that are the bane of your existence. So like iterating it so that more people can adopt it into their own needs.

Tim (00:38:16) - All right, so serious question tabs or spaces?

Ariana (00:38:17) - Drama. Okay. I'm a tab girl, okay?

Tim (00:38:20) - I'm also a tab guy, so we're good.

Tim (00:38:22) - We can–

Ariana (00:38:23) - I started sweating. No joke, really intensely. If people are listening to us and they're like, wow, these are these people, they've got something, I want to do this thing that they're doing, I guess where would you start today? Because, you know, you've evolved with technology and if you're starting today, I got to admit, that might be overwhelming to like, look at this whole thing. Where do you pick your niche? But how would you…I don't know. How would you guide people into that journey from a technology standpoint, but also for talking about augmented intelligence. If we're talking about SearchQuery, like where would you guide people?

Tim (00:38:59) - There's a couple of answers to that question. One, I wish the resources that are available today were available when I was growing up learning most of these things. I kid you not. I was literally in bookstores like I will never forget. My mom would like let me go and sit there for hours and just flip through books and go home.

Tim (00:39:16) - I actually do need to go back and thank her for that. But you know, now everything's available on YouTube. You've got free courses galore. There's a whole bunch, there's a slew of resources on the Internet where you can just get started. There are a lot of languages that you can start with too. I talk about JavaScript and JavaScript is a pain of a language in general. And it does take a little bit of background, but a lot of people, especially when you're getting into data, they start with Python and Python is a relatively simple language for you to kind of get started with. The syntax is usually easier for the brain to kind of comprehend and start diving through. So it makes it easier for people to just get started. So Python I think is definitely a good start especially if you're talking about getting into data and data analytics or AI machine learning any of those things, because Python is really the core of a lot of those things. Even when we started, our core platform was built in Python, you know, we had the core engine for doing the intent, understanding and natural language processing and entity attraction type things. All that was done in Python and over the years and very short time span, there started to become a whole lot of libraries and things that were implemented in JavaScript, in Node.js that we were able to take advantage of that allowed to move our stack to something that all of our team could use instead of us having to have a set of just core Python developers working on those things. So that's kind of how some of our things have evolved along the way. But again, you've got Coursera online, you've got I've got a long email that I normally send to a lot of my friends that will ask me this very question of how do I get an attack? And I say, well, it depends on what area. And it goes into, Hey, if you're interested in development, if you're interested in cybersecurity, I've got links to various free courses and some paid courses. But it really just depends on how much investment you want to put into that. That said, I think the number one thing that I always tell everyone is before you get into it, have a project or an idea in mind, what is the thing that you want to solve? Because that's going to make it more interesting and bring it home for you.

Tim (00:41:31) - So as you're learning these techniques and skills, you can go and apply those to your project, the thing that you're hyper interested in. And now it's going to become it's going to it's going to sink in a whole lot more. And you're going to be able to think about things in a very different way.

Ariana (00:41:45) - Yeah, that's a really good point. I also, from my own experience, I think knowing the best way that you learn also is super helpful. Like I'm a doer. I got to be cornered into doing something and I got to prove somebody wrong. That's how I know I learned. So for other people, it might be like the fact that you learn coding by reading. I'm like, Wow, that is amazing because you have to translate that into the interface. But some people, that's where they learn audio/visual, right? I think that's also another layer that can be paired with that thing that you want to build. And there's so many tools, right? And a lot of them are free. I think that's the thing is like you just have to have the want to learn and you've got to know how you learn best, merge those two things and you're in the right direction.

Tim (00:42:32) - Absolutely. Couldn't agree more.

Ariana (00:42:33) - I mean, there's just too much you need. We need at least two hours because I do want to wrap up with some of that human level part of you and get to know you as a human being. So. So we've got some rapid fire questions. You can go with your gut on these just to get to know him as a human. So the first one is what is the favorite part of your day?

Tim (00:42:53) - Honestly, when I do wake up because my brain is kind of on rapid fire on the 10 million things I need to be doing. It's also probably the most stressful part of my day because I'm thinking about all of those different things and trying to figure out how I'm going to fit everything in. But it's exciting because my brain does get going in a fun way. Anytime I have a meeting with a client or even internally with employees, it's definitely an excitement because now I'm having to exercise muscles that I don't normally exercise because sometimes it's you're on autopilot.

Tim (00:43:29) - So when I get a chance to do something or talk about something that I wasn't thinking of before, it just starts to really flex those muscles and gets my creative juices flowing a little bit.

Ariana (00:43:38) - What is something that makes you little-kid happy?

Tim (00:43:41) - Ooh, dark chocolate. Like I'm obsessed with dark chocolate. So I have a client and the office admin on the front of her desk as soon as you walk in the office, she has this little bowl of candy. And like, I always go and look and she knows I'm obsessed with dark chocolate. So she always fills it with dark chocolate when she knows I'm coming. So like, that does get me a little hacky. So I do. I do love some dark chocolate there.

Ariana (00:44:07) - A follow up question to that important question, which is, is there a percentage of dark chocolate that you aim for?

Tim (00:44:13) - Typically that's 72% to 78% range. Anything above that is way too sweet, That 72% range is like right on the cusp of perfection.

Ariana (00:44:23) - Totally, totally anything above gets to get in that dirt range, which like, sometimes I'm down, but other times, no.

Ariana (00:44:31) - What book are you currently reading or listening to?

Tim (00:44:34) - There's a poker strategy book by Daniel Negreanu that I actually just purchased. Just hit my door yesterday, as a matter of fact. So I'm getting ready to do a deep dive into that one. I'm a big poker player, so I'm always looking for interesting strategies and angles and things like that.

Ariana (00:44:52) - Very cool. What is the best purchase you've made under $50?

Tim (00:44:58) - This is going to sound a little weird, but all right, so I've carried a pen with me in my pocket every day since I was like a young child, like, just always. So I carry G2 pens with me all the time. And I just keep them on. Those are cheap, they cost absolutely nothing. But it's like the most used thing that I keep on me because I am constantly writing things down. There's something about writing for me that helps commit things and even typing doesn't have the same effect as actually writing something down.

Tim (00:45:33) - So there are some times where if I have a coding idea, I will literally write the code down on paper to help keep that committed to memory, even if I throw it away, the the act of writing it down helps. So I'm going to go with the pens.

Ariana (00:45:48) - Very cool. I do think it's hard to find your soulmate pen and then once you find it, you have it for life. This is true. What is your favorite quote?

Tim (00:45:57) - Favorite quote? One of my favorite books ever is The Hard Thing About Hard Things. It's a fantastic business book. If you're ever just getting started in the business, it goes into a bunch of founder, you know, stories and hey, here's the things that you run through at different stages and those types of things. But we do a company newsletter and every month I started off with a quote and I actually use this when maybe just a couple of months ago. So “take care of the people, the products and the and the profits” in that order.

Tim (00:46:28) - That is like the key crux of that quote. It's much longer than that. But that's the crux of it, is the people, the product and the profits. And that's exactly how we try to run our business, take care of our people, have, you know, the best benefits we can possibly have, make sure people have the best lifestyle that they can possibly have. The product is secondary. Make sure the product…because if you take care of the people, the people are going to take care of the product. Once you take care of the product, the product is going to help drive those profits. And that's how we look at things from a business perspective.

Ariana (00:46:57) - Wow. I got to read that. That sounds amazing.

Tim (00:47:00) - It’s a fantastic book. I pull quotes from it all day long. So, one of my favorite books. I've read it probably more times than anything else. It's definitely a fantastic book.

Ariana (00:47:11) - So at this point in your life, what do you think is the most important lesson you've learned?

Tim (00:47:16) - This goes back to childhood, how my parents raised me, etcetera.

Tim (00:47:19) - Take care of the people around you. You take care of the people around you…A) The world's going to be a better place in general because people are just generally happy. B) It helps to make things a lot more fun. I mean, if you look at the way we've built our company, our culture was designed around, hey, we're going to throw people into positions that they've never done before. We're all starting this off. When I started the business, I had never run a business before. I'd never done ops before. I had to figure a lot of these things out on the fly. You know, how do we do finance? How do we do contracts? All the different things that you have to do. So when we hire, I look for people that have hustle and are really willing to, hey, I can grit in and figure out how to do the thing even if they've never done it before. So as long as you're taking care of those people and giving them the opportunities, you're going to see that, you know returned in spades.

Tim (00:48:14) - I think that applies in every aspect of your life, right? Making sure you take care of the people around you no matter where they are. That's going to return to you in spades. But also it just feels good to do it.

Ariana (00:48:27) - Last rapid fire question, which is what do you want to be when you grow up?

Tim (00:48:32) - Yeah, I asked myself this question like every other day. I have no idea. It's funny, I actually joke with a lot of my team. I don't know what I want to be when I grow up. I had designs on being a lawyer. I had designs on being a doctor. I had designs on being an astronaut. You know, I run the gamut now. All I know is I think I will always be running a business after we have whatever exit we have with this business. I will be starting another one. I don't know what that is yet, but I've got a million and one ideas and we're going to throw darts at them until we figure out which one makes the most sense.

Tim (00:49:09) - So I think that that entrepreneurial lifestyle is definitely the right fit for me. You know what exactly that looks like? It could change. Who knows? Next time I may be in a completely different field. It may not be tech, but I'm definitely always going to be kind of driving on building something and creating.

Ariana (00:49:26) - Tim I'm so sad that our time is up because I just have so many more questions for you. I just got to thank you very much for taking complex concepts and bringing them to life in a really approachable way. If people are also as jazzed as I am, where can they find you and the work that you're doing?

Tim (00:49:43) - Yeah, absolutely. So you can definitely find me on LinkedIn. On LinkedIn I’m /TimTutt. I'm on Twitter as TimfTutt. There's someone else that had my old handle or the handle I try to use everywhere. But I am Tim Tutt on Twitter. And then if you're interested in data analytics and want to give us a shot, ClearQuery.IO is our website.

Tim (00:50:07) - Check us out there. We've got a free tier for you to check out as well.

Ariana (00:50:10) - Tim Thank you again, we will have to do another part. Listeners, thank you so much for listening to Secret Ops. You have no idea how much it means. Please make sure to follow us wherever you find your podcast and check us out at secret-ops.com. We'll see you next time.