WEBVTT 1 00:00:00.000 --> 00:00:03.359 Information economy as a rid. The world is teeming with 2 00:00:03.439 --> 00:00:08.039 innovation as new business models reinvent every industry industry. Inside 3 00:00:08.039 --> 00:00:12.039 Analysis is your source of information and insight about how 4 00:00:12.080 --> 00:00:14.960 to make the most of this exciting new era. Learn 5 00:00:15.000 --> 00:00:19.239 more at inside analysis dot Comsideanalysis dot com. And now 6 00:00:19.480 --> 00:00:21.800 here's your host, Eric Kavanaugh. 7 00:00:25.000 --> 00:00:28.239 Fare Well. All right, ladies and gentlemen, Hello and welcome 8 00:00:28.280 --> 00:00:30.879 back once again to the only coast to coast radio show. 9 00:00:30.879 --> 00:00:34.159 And that's all about the information economy. It's called Inside Analysis. 10 00:00:34.280 --> 00:00:36.560 You're true the Eric Kavanaugh is here, and folks, I'm 11 00:00:36.679 --> 00:00:39.759 very pleased to be talking about a very serious subject 12 00:00:39.799 --> 00:00:42.799 today that is hiring in the federal government. We have 13 00:00:42.880 --> 00:00:46.079 Chris Collegato today with us and he is from Fedstack 14 00:00:46.600 --> 00:00:50.439 and they're focused intently on this very challenge. And Chris, 15 00:00:50.479 --> 00:00:52.200 there are lots of things that need to get done 16 00:00:52.200 --> 00:00:54.679 in DC, as we all know, and you folks are 17 00:00:54.759 --> 00:00:57.759 out there helping to make these connections. Tell us quickly 18 00:00:57.799 --> 00:01:00.640 about Fedstack, what you guys were build for and what 19 00:01:00.679 --> 00:01:01.520 you're working on today. 20 00:01:02.320 --> 00:01:07.040 Sure, thanks, Eric, so very quick on. Fedstack is actually 21 00:01:07.079 --> 00:01:10.519 a new brand very focused on the federal. 22 00:01:12.200 --> 00:01:12.560 Market. 23 00:01:13.120 --> 00:01:16.200 In fact, we are basically a unit that was born 24 00:01:16.319 --> 00:01:20.920 out of a workforce development organization called smooth Stack. So 25 00:01:21.120 --> 00:01:24.359 this is actually a brand launch where we're actually expanding 26 00:01:24.359 --> 00:01:26.920 our offering from what we're pretty well known to. 27 00:01:26.879 --> 00:01:29.799 Have been doing in the market space until now. 28 00:01:30.359 --> 00:01:35.359 So our focus has been how do we basically close 29 00:01:35.400 --> 00:01:39.239 in on the skills gap specific to technology. Right, there's 30 00:01:39.280 --> 00:01:42.920 a lot of difficulty in hiring also in the federal space. 31 00:01:43.040 --> 00:01:47.040 There's also a lot of competition in the open market 32 00:01:47.079 --> 00:01:50.000 for pretty much the same pool of resources. So where 33 00:01:50.040 --> 00:01:53.120 we differentiate ourselves is we're actually what we were calling 34 00:01:53.159 --> 00:01:56.599 it creation of net new talent. Right. What that means 35 00:01:56.719 --> 00:02:03.120 is we actually develop the talent from sources where you 36 00:02:03.159 --> 00:02:05.319 would not usually find them, right, So a lot of 37 00:02:05.480 --> 00:02:08.800 new entrants into the technology market that have the high 38 00:02:08.800 --> 00:02:16.919 aptitude for grasping new technology, exiting military that would like 39 00:02:16.960 --> 00:02:20.560 to break into the technology field. Basically, we created an 40 00:02:20.599 --> 00:02:25.840 accelerated apprenticeship program where we are secret sauces being an 41 00:02:25.840 --> 00:02:30.719 immersive environment where we mirror the target environment for our clients, 42 00:02:31.240 --> 00:02:35.240 be that direct to the government or some of our 43 00:02:35.280 --> 00:02:39.919 system integrated partners where they're trying to meet a particular requirement. 44 00:02:40.599 --> 00:02:44.280 Yeah, So the new training where it is intensive training, 45 00:02:44.400 --> 00:02:46.840 and I'm presuming what you're doing is mimicking the work 46 00:02:46.919 --> 00:02:49.439 environment where they'll be so they work with the technologies 47 00:02:49.479 --> 00:02:52.039 that they'll need to be working with in the actual job. 48 00:02:52.080 --> 00:02:52.639 Is that right? 49 00:02:53.080 --> 00:02:53.560 That's correct. 50 00:02:53.599 --> 00:02:56.960 So we actually have a patent pending on this technology 51 00:02:57.000 --> 00:03:03.520 for called mirror environment, right. So beyond just training them 52 00:03:03.560 --> 00:03:08.560 on the content, right, we really tailored the curriculum specific. 53 00:03:08.039 --> 00:03:08.759 To that job. 54 00:03:09.039 --> 00:03:12.360 Right, So it's not just about training on one dimension, 55 00:03:12.919 --> 00:03:16.759 but really the full breadth of skill sets that's required 56 00:03:16.800 --> 00:03:19.840 to deliver the job for day one, right, So whether 57 00:03:19.919 --> 00:03:24.639 that's cloud, whether that's actual programming or even consulting skills 58 00:03:24.639 --> 00:03:27.319 and knowledge of the domain where they're going to be deployed. 59 00:03:27.800 --> 00:03:31.479 So we really tailored the environment specific to the requirement 60 00:03:32.159 --> 00:03:35.520 and then basically run them through anywhere from a ten 61 00:03:35.560 --> 00:03:40.360 to twelve week window against a full time, full time 62 00:03:41.080 --> 00:03:44.719 absorption of the material where we provide all the lab 63 00:03:45.199 --> 00:03:49.479 environments set up for that the trainers, the product owners 64 00:03:49.719 --> 00:03:53.520 mimicking and simulating what they would face when they actually 65 00:03:53.560 --> 00:03:54.680 work on day one. 66 00:03:55.360 --> 00:03:55.919 Yeah. 67 00:03:56.000 --> 00:03:59.319 Well, and there's lots of new technology to learn these days. Obviously, 68 00:03:59.439 --> 00:04:02.000 artificial intelligence is very much top of mind. 69 00:04:02.000 --> 00:04:04.000 For people. You have models that. 70 00:04:04.000 --> 00:04:06.719 Need to be designed, they need to be trained. You've 71 00:04:06.719 --> 00:04:10.039 got AI infrastructure to worry about. Do you cover that 72 00:04:10.120 --> 00:04:15.240 whole spectrum everything from the IT infrastructure to the model design, 73 00:04:15.360 --> 00:04:16.879 the training, all that kind of fun stuff. 74 00:04:17.199 --> 00:04:18.160 Oh, absolutely right. 75 00:04:18.240 --> 00:04:20.680 So we will focus on what is in need today 76 00:04:20.720 --> 00:04:25.639 and we actually continue to continue to scan the market 77 00:04:25.680 --> 00:04:27.959 of what's emerging. So we want to be able to 78 00:04:27.959 --> 00:04:31.240 stay ahead of what's coming. So we focus on. 79 00:04:31.120 --> 00:04:34.319 Five key areas, right, data and AI. 80 00:04:34.519 --> 00:04:36.720 Right, So a lot of the data engineering, big data, 81 00:04:36.800 --> 00:04:40.079 analytics and so on, a lot of the new AI 82 00:04:40.240 --> 00:04:45.240 models are coming out there, the traditional applications development, regardless 83 00:04:45.279 --> 00:04:46.920 of what stack that may be. 84 00:04:47.720 --> 00:04:49.120 And then digital platforms. 85 00:04:49.120 --> 00:04:52.480 There's a lot of COTS packages, ERP packages for example, 86 00:04:52.600 --> 00:04:57.759 lo code, no code, type of technologies uh, including infrastructure solutions, 87 00:04:57.759 --> 00:05:01.040 cloud hybrid, and so on, including the way we do 88 00:05:01.120 --> 00:05:06.040 DevOps for deployment and packaging all that into those target environment. 89 00:05:06.079 --> 00:05:08.600 And finally, of course across the board, you need to 90 00:05:08.639 --> 00:05:11.800 have cybersecurity for secure applications and platforms. 91 00:05:12.399 --> 00:05:15.160 Yeah, cybersecurity, I mean there's a space that will never 92 00:05:15.240 --> 00:05:18.439 ever ever go away. It's harder than ever, but you 93 00:05:18.480 --> 00:05:20.519 do have better tools than ever too, So how do 94 00:05:20.560 --> 00:05:24.079 you yourselves keep on top of the latest technologies? Do 95 00:05:24.160 --> 00:05:28.839 you hire consultants and practitioners from these environments. Let's just 96 00:05:28.879 --> 00:05:32.600 pick cybersecurity as one because it's its own entity. Do 97 00:05:32.680 --> 00:05:35.360 you go out and get folks from the big firms 98 00:05:35.439 --> 00:05:38.040 to come on and be your trainers and your consultants? 99 00:05:38.040 --> 00:05:38.720 How does that work? 100 00:05:39.319 --> 00:05:43.759 So we have a pretty large partner network, So we 101 00:05:43.800 --> 00:05:47.120 partner both from a strategic alliance with the vendor providers 102 00:05:47.120 --> 00:05:52.360 for example. So we create those partnerships where we are 103 00:05:52.399 --> 00:05:58.160 basically seen as workforce providers and then we basically look 104 00:05:58.240 --> 00:06:01.879 at those trainers or the ex experts from the various 105 00:06:01.920 --> 00:06:05.439 fields that we're trying to surface. Right So, in fact, Ashla, 106 00:06:05.519 --> 00:06:09.000 that's a good segue into the expansion of our offerings 107 00:06:09.040 --> 00:06:14.519 beyond creating this apprenticeship cohorts, where we're now actually extending 108 00:06:14.519 --> 00:06:18.480 our services to our partners where some of the folks 109 00:06:18.519 --> 00:06:20.600 that they have that may have been working on the 110 00:06:20.639 --> 00:06:24.800 same maybe legacy applications that now have to transition to 111 00:06:24.800 --> 00:06:28.680 the modern technology as new platforms get rolled out, they 112 00:06:28.720 --> 00:06:30.600 need to be able to keep pace with that, so 113 00:06:30.639 --> 00:06:33.839 we bring in the trainers that will help the transition 114 00:06:34.439 --> 00:06:38.399 from legacy to modern digital platforms. 115 00:06:38.600 --> 00:06:40.839 And there are lots and lots of new platforms. 116 00:06:40.839 --> 00:06:43.639 You mentioned low code, no code, that's been a very 117 00:06:43.639 --> 00:06:46.800 hot topic the last few years, where you just have 118 00:06:46.920 --> 00:06:51.480 a nice graphical user interface and it's typically a drag 119 00:06:51.519 --> 00:06:55.000 and drop where you pull together different components and under 120 00:06:55.040 --> 00:06:57.279 the covers they handle all the code development, all the 121 00:06:57.279 --> 00:06:58.000 code execution. 122 00:06:58.160 --> 00:06:58.399 Right. 123 00:06:59.120 --> 00:07:04.000 Absolutely, there's some exciting things that actually beyond the local 124 00:07:04.120 --> 00:07:08.040 no code now with AI, right, AI itself is actually 125 00:07:08.800 --> 00:07:11.399 needs to work together with the folks that were training 126 00:07:11.439 --> 00:07:14.839 because you're no longer just training them the basics of programming, 127 00:07:15.240 --> 00:07:17.360 but how to actually program with. 128 00:07:17.439 --> 00:07:18.759 AI as an assistant. 129 00:07:19.279 --> 00:07:21.319 So it's a little bit of a new game, right, 130 00:07:21.319 --> 00:07:24.680 It's almost a game changer where you know, one person 131 00:07:24.759 --> 00:07:29.199 needed to learn the very basic coding principles. Now you're 132 00:07:29.199 --> 00:07:32.399 doing local no code and reuse, dropping and dropping gugi 133 00:07:33.040 --> 00:07:35.079 on top of the thing, and now AI itself you 134 00:07:35.319 --> 00:07:37.279 give them a prompt and it's writing a lot of 135 00:07:37.279 --> 00:07:39.439 the code for you. So being able to live in 136 00:07:39.480 --> 00:07:44.000 that environment that the expectation is really accelerated outcomes. 137 00:07:44.879 --> 00:07:47.879 Yeah, and of course jen ai is very hot these days. 138 00:07:48.000 --> 00:07:50.639 But the problem with Jenais you probably know is that 139 00:07:50.759 --> 00:07:54.319 it is probabilistic, so it's not deterministic. I think that's 140 00:07:54.360 --> 00:07:57.160 one reason why you see so much emphasis on the copilots, 141 00:07:57.480 --> 00:08:00.480 on the helpers, the digital assistance, because the human can 142 00:08:00.519 --> 00:08:03.560 then still make a judgment about what to do. You're 143 00:08:03.560 --> 00:08:06.279 not just turning the genai and letting it do the job. 144 00:08:06.399 --> 00:08:07.639 Is that your impression as well? 145 00:08:07.720 --> 00:08:09.120 That absolutely? 146 00:08:10.600 --> 00:08:14.040 Oh absolutely, I think a lot of this hallucinations happen 147 00:08:14.160 --> 00:08:16.839 right with some of the It depends on what you 148 00:08:17.000 --> 00:08:20.279 use for training the models, So you know, part of 149 00:08:20.279 --> 00:08:23.959 the decision making would be when do you point Copilot 150 00:08:24.079 --> 00:08:26.800 or others into like external resources where it can be 151 00:08:26.839 --> 00:08:31.160 corrupted by a lot of the unvetted information that that's 152 00:08:31.160 --> 00:08:35.200 being formed to form your answers versus trusted sources for 153 00:08:35.279 --> 00:08:40.559 training in house. Potentially that would allow actually more reliable answers. 154 00:08:42.120 --> 00:08:44.279 And you know, one of the technologies that fascinates me 155 00:08:44.320 --> 00:08:45.840 the most, and I'm curious to know if you've heard 156 00:08:45.840 --> 00:08:50.000 about this process mining companies like Salonis Software a G. 157 00:08:50.120 --> 00:08:52.559 There's a few of them out there where you track 158 00:08:52.639 --> 00:08:57.279 typically the digital data footprints through various information systems to 159 00:08:57.360 --> 00:09:00.519 see what's actually happening to me, that is an incredibly 160 00:09:00.519 --> 00:09:05.519 powerful technology for rewriting, reinventing information systems to kind of 161 00:09:05.559 --> 00:09:07.279 catapult them into the modern age. 162 00:09:07.279 --> 00:09:09.639 What do you think, Well, absolutely, I think that that 163 00:09:09.799 --> 00:09:11.279 saves a lot of time. 164 00:09:11.399 --> 00:09:11.600 Right. 165 00:09:12.000 --> 00:09:15.000 You know, you've done a lot of methods in the past, 166 00:09:15.120 --> 00:09:18.600 the reverse engineering, and this really helps a lot, especially 167 00:09:18.639 --> 00:09:21.000 when you're doing modernization, right. It takes a lot of 168 00:09:21.000 --> 00:09:23.759 time to try and trace and ensure that you're able 169 00:09:23.840 --> 00:09:26.720 to keep the functions that you want to keep and 170 00:09:26.799 --> 00:09:29.320 how to design for the future, and something like this 171 00:09:29.399 --> 00:09:31.039 really accelerates that analysis. 172 00:09:31.519 --> 00:09:35.320 Yeah, and open source is a big deal too. Open source, 173 00:09:35.480 --> 00:09:39.879 I think has revolutionized the information technology landscape, certainly on 174 00:09:39.919 --> 00:09:41.840 the app development side, I mean all the way down 175 00:09:41.879 --> 00:09:44.240 to Linux and the Linux kernel and the work that's 176 00:09:44.279 --> 00:09:47.559 being done there, but the entire data stack now has 177 00:09:47.600 --> 00:09:50.720 been opening up to open source technology. Are there concerns 178 00:09:51.240 --> 00:09:55.559 in federal use cases for open source because the source 179 00:09:55.639 --> 00:09:56.039 is open? 180 00:09:56.279 --> 00:09:57.200 What do you think about all that? 181 00:09:57.879 --> 00:10:00.240 I think in the early days that been a lot 182 00:10:00.279 --> 00:10:03.039 of concern But there's like two thoughts on that, right, 183 00:10:03.039 --> 00:10:05.559 there's still a lot of folks that kind of want 184 00:10:05.559 --> 00:10:09.360 to look at closed systems but what we're finding out 185 00:10:09.519 --> 00:10:11.639 is a lot of folks say, hey, because it's an 186 00:10:11.639 --> 00:10:15.559 open system, it's been tested more thoroughly than any closed 187 00:10:15.559 --> 00:10:18.519 system that's out there, that they may actually renders them 188 00:10:18.519 --> 00:10:21.240 more secure. You know, I could go both ways on 189 00:10:21.320 --> 00:10:25.080 that one, but it really depends on how sensitive the 190 00:10:25.120 --> 00:10:29.320 systems you're developing and how you know whether you are 191 00:10:29.360 --> 00:10:33.279 exposing vulnerability in an open setting, or it's a mature 192 00:10:33.399 --> 00:10:39.159 enough platform that's been really thoroughly tested that makes it trustable. 193 00:10:39.200 --> 00:10:42.200 Like Linux, you know, was in the same boat at 194 00:10:42.200 --> 00:10:44.240 some point, and now it's all over the place. 195 00:10:44.080 --> 00:10:46.840 Right now, and now it's the enterprise standard for sure. 196 00:10:46.639 --> 00:10:51.039 Absolutely, and we all keep hearing about this it skills shortage, 197 00:10:51.320 --> 00:10:54.000 and you know, I don't really know what to make 198 00:10:54.000 --> 00:10:55.519 of it all. There are lots of people, I'm sure, 199 00:10:55.519 --> 00:10:58.159 who want to learn all those things, and you're filling 200 00:10:58.200 --> 00:11:01.440 that gap, right, I mean, you are training and retraining 201 00:11:01.480 --> 00:11:04.559 people to learn how to use all the new technologies. 202 00:11:04.600 --> 00:11:06.639 And you know, the fun part is that Jennai can 203 00:11:06.679 --> 00:11:08.919 be a big part of that, right. You can load 204 00:11:09.000 --> 00:11:12.720 instruction manuals into a GENEI solution and then just ask 205 00:11:12.759 --> 00:11:15.399 it all kinds of questions in that environment. It seems 206 00:11:15.399 --> 00:11:18.519 to me they're very, very powerful and very effective. They 207 00:11:18.559 --> 00:11:20.840 don't hallucinate as much because they're just pointed at a 208 00:11:20.879 --> 00:11:24.000 particular document. Is that what you found as well, that 209 00:11:24.240 --> 00:11:27.320 JENNI can be a very powerful copilot in helping to 210 00:11:27.360 --> 00:11:29.159 train people to use new technology. 211 00:11:29.399 --> 00:11:29.559 Well. 212 00:11:30.000 --> 00:11:33.320 Absolutely, And I think a lot of the younger generation 213 00:11:33.519 --> 00:11:37.840 factor growing up with GENAI access already, right, So we 214 00:11:37.879 --> 00:11:42.120 have to adopt our training mechanisms and methods in order 215 00:11:42.159 --> 00:11:45.679 to incorporate that in the learning management systems that we 216 00:11:46.159 --> 00:11:49.240 actually have ourselves in house, and so we need to 217 00:11:49.279 --> 00:11:53.240 constantly look for new ways of actually training. As you know, 218 00:11:53.279 --> 00:11:56.440 we're trying to train and rescale some of the folks 219 00:11:56.480 --> 00:11:59.159 that are more used to the older technologies, and then 220 00:11:59.200 --> 00:12:02.399 you have the the folks are new, younger generation are 221 00:12:02.480 --> 00:12:05.120 upcoming that expect that this is the way they want 222 00:12:05.159 --> 00:12:08.320 to learn in the future. So we're trying to have 223 00:12:08.440 --> 00:12:11.919 that happy medium. But the future really is everything is 224 00:12:11.960 --> 00:12:16.000 going to be gen AI or agenta AI assistant. 225 00:12:17.039 --> 00:12:18.759 Yeah, and that actually brings up a really good point. 226 00:12:18.840 --> 00:12:21.320 I'd be curious to get your thoughts as a trainer, 227 00:12:21.399 --> 00:12:24.320 as someone who is working for a company that trains people. 228 00:12:24.840 --> 00:12:29.240 We now have arguably five generations in the workforce with 229 00:12:29.519 --> 00:12:33.440 very different cultural norms, very different tendencies and more rays. 230 00:12:33.960 --> 00:12:35.000 How do you tackle that. 231 00:12:35.080 --> 00:12:39.360 Do you actually address that programmatically to treat people of 232 00:12:39.399 --> 00:12:40.960 a certain age one way and people of a certain 233 00:12:41.000 --> 00:12:43.919 age a little bit different just because of their cultural diversity, 234 00:12:44.000 --> 00:12:45.159 or how does that actually work? 235 00:12:45.399 --> 00:12:48.960 Yeah, we absolutely need to consider that, right, So when 236 00:12:49.000 --> 00:12:53.000 we're build out some cohorts in the screening process, as 237 00:12:53.120 --> 00:12:57.879 we are customizing the curriculum, that's part of the consideration. 238 00:12:58.080 --> 00:13:00.240 What is the makeup of that cohort for example, Well, 239 00:13:00.279 --> 00:13:03.000 if that's a mix of all five generations, you've got 240 00:13:03.039 --> 00:13:05.279 to be able to cater to what's the most effective 241 00:13:05.279 --> 00:13:09.240 technique and I just deliver the content material in a 242 00:13:09.279 --> 00:13:10.440 one size fits all manner. 243 00:13:11.679 --> 00:13:12.960 Yeah, that's interesting too. 244 00:13:13.120 --> 00:13:15.639 So you know, maybe you could share with our audience 245 00:13:15.639 --> 00:13:18.840 a bit how you track those kinds of things, the 246 00:13:18.919 --> 00:13:22.799 techniques that you use, which sessions you have people joined 247 00:13:22.799 --> 00:13:25.720 to train, and then the efficacy of that down the road. 248 00:13:25.799 --> 00:13:28.320 I mean, I know fed stack is new, but from 249 00:13:28.399 --> 00:13:31.600 your smooth Stack experience, for example, how much are you 250 00:13:31.679 --> 00:13:35.879 able to track, measure, and then ascertain the efficacy of 251 00:13:35.919 --> 00:13:39.159 certain programs to certain demographics and then monitor it and 252 00:13:39.200 --> 00:13:40.279 modify that over time. 253 00:13:40.919 --> 00:13:44.759 Yeah, so that's actually a really good question because that's 254 00:13:44.759 --> 00:13:46.919 the reason why we actually came up with our own 255 00:13:46.960 --> 00:13:49.399 learning management system to be able to track everything. 256 00:13:49.519 --> 00:13:49.759 Right. 257 00:13:50.080 --> 00:13:52.200 So when you look at a ten to twelve week 258 00:13:52.639 --> 00:13:57.840 process and cohort, every week is basically an evaluation where 259 00:13:58.080 --> 00:14:01.240 actually the progress of the entire class comes in, right, 260 00:14:01.279 --> 00:14:04.159 So we're trying to develop a cohort. In fact, it's 261 00:14:04.159 --> 00:14:06.919 no guarantee that they're actually going to graduate, right, So 262 00:14:07.039 --> 00:14:10.799 the efficacy of how we teach that is very important, 263 00:14:10.799 --> 00:14:16.039 but also the evaluation factors because we're very selective on 264 00:14:16.159 --> 00:14:18.799 the folks that we deploy out there for contracts, so 265 00:14:18.840 --> 00:14:21.320 we may start up with a very large number, but 266 00:14:21.440 --> 00:14:24.519 by the time we're finish and only the stream of 267 00:14:24.559 --> 00:14:27.559 the crop actually surfaces at the end. 268 00:14:27.679 --> 00:14:30.679 So we're a heavier aligned of metrics. 269 00:14:30.919 --> 00:14:33.919 And even after the courses are done, we do checkpoints, 270 00:14:34.000 --> 00:14:36.919 right the first thirty days, the first sixty days, what's 271 00:14:36.919 --> 00:14:41.759 your feedback of what would you rather us have done. 272 00:14:42.480 --> 00:14:45.320 Now that you actually have experience in working this and 273 00:14:45.360 --> 00:14:48.519 applying this on your current project, then we use that 274 00:14:48.559 --> 00:14:50.679 for the training of the next cohort in order to 275 00:14:50.720 --> 00:14:51.240 improve it. 276 00:14:52.840 --> 00:14:55.639 That's very impressive. You developed your own learning management system. 277 00:14:56.039 --> 00:14:58.360 If you sometimes you got to roll your own right. 278 00:14:58.399 --> 00:15:01.240 You have to figure out what you need done, what 279 00:15:01.320 --> 00:15:03.759 functionality you need baked into this system, and if you're 280 00:15:03.759 --> 00:15:06.399 a large enough organization, sometimes it makes sense to just 281 00:15:06.440 --> 00:15:08.120 build out your own system. 282 00:15:08.159 --> 00:15:09.399 That's that's pretty impressive. 283 00:15:09.399 --> 00:15:11.919 So I'm guessing you had some experience with learning management 284 00:15:11.960 --> 00:15:14.080 systems and you're like, you know what, we got to 285 00:15:14.159 --> 00:15:16.600 really roll up our sleeves and build this one out ourselves. 286 00:15:16.720 --> 00:15:18.279 How long did that take? Roughly? Do you know? 287 00:15:18.639 --> 00:15:21.879 Well, it's actually born out of necessity. So when we 288 00:15:22.200 --> 00:15:25.039 the organization started a smooth Stack, you know, five six 289 00:15:25.120 --> 00:15:28.879 years ago, it was an in person learning. We actually 290 00:15:29.240 --> 00:15:32.799 bring our students here, put them in apartments, and we 291 00:15:32.879 --> 00:15:36.519 have a whole training facility in house. When COVID hit, 292 00:15:37.279 --> 00:15:39.639 everything had to go to virtual and we had to 293 00:15:39.759 --> 00:15:41.759 rapidly come up with a way to be able to 294 00:15:41.799 --> 00:15:46.080 deliver those same, you know, quality programs in a virtual manner. 295 00:15:46.320 --> 00:15:47.879 And that's what actually. 296 00:15:47.480 --> 00:15:50.279 Prompted us to say, hey, we really need to create 297 00:15:50.279 --> 00:15:53.480 our own learning management system in order to deliver what 298 00:15:53.480 --> 00:15:56.759 we're able to deliver in an in person manner. 299 00:15:57.279 --> 00:15:57.759 Mm hmm. 300 00:15:58.360 --> 00:16:02.600 Yeah, COVID was quite the forcing function, right to use 301 00:16:03.240 --> 00:16:06.399 a technology term, It really forced us all to take 302 00:16:06.440 --> 00:16:11.080 a very hard look at processes, workflows, access to data, 303 00:16:11.120 --> 00:16:13.799 access to information systems, and security. 304 00:16:14.120 --> 00:16:15.000 For goodness sakes. 305 00:16:15.039 --> 00:16:18.600 I mean, with everybody working from home now, your threat 306 00:16:18.879 --> 00:16:22.480 scape is much larger because you have all these all 307 00:16:22.519 --> 00:16:25.759 these devices everywhere, computers that are outside of your data center, 308 00:16:25.879 --> 00:16:28.559 phones that are outside of your purview at least you know, 309 00:16:28.639 --> 00:16:31.039 in the in the corporate office, et cetera. So that 310 00:16:31.159 --> 00:16:33.080 was a real wake up call for you guys that 311 00:16:33.320 --> 00:16:36.440 you had to go and reevaluate and redesign how you 312 00:16:36.480 --> 00:16:37.279 do these things. 313 00:16:37.080 --> 00:16:39.559 Right, absolutely, absolutely. 314 00:16:39.440 --> 00:16:42.120 Yeah, that's that's pretty impressive. And let's get into in 315 00:16:42.120 --> 00:16:42.720 the next segment. 316 00:16:42.759 --> 00:16:46.200 We'll get a bit deeper into the cybersecurity side, just 317 00:16:46.240 --> 00:16:49.240 because that is so important and I happen to know 318 00:16:49.639 --> 00:16:54.200 from experience that cybersecurity is a constantly evolving, constantly changing 319 00:16:54.720 --> 00:16:57.440 environment and to stay on top of things you need 320 00:16:57.519 --> 00:17:00.720 to do. Of course, all the basics, password management things 321 00:17:00.759 --> 00:17:03.559 of this nature. Biometrics of course are really coming into 322 00:17:03.559 --> 00:17:07.079 play these days. But you need to be monitoring the network. 323 00:17:07.119 --> 00:17:08.960 You need to be monitoring the apps, you need to 324 00:17:08.960 --> 00:17:11.839 be monitoring the behaviors of all these people. And there 325 00:17:11.880 --> 00:17:15.559 are hundreds and hundreds of security solutions you can use. 326 00:17:15.960 --> 00:17:18.319 Some like I suggest that focus on the network, some 327 00:17:18.359 --> 00:17:20.839 focus on the apps, some focus on the users and 328 00:17:20.920 --> 00:17:23.599 kind of watching, and some take a more holistic approach. 329 00:17:24.000 --> 00:17:26.640 And of course, with machine learning you can track these 330 00:17:26.680 --> 00:17:30.480 things more and more assiduously over time. So when we 331 00:17:30.519 --> 00:17:32.200 come back from the break, we'll be talking again to 332 00:17:32.319 --> 00:17:35.880 Chris Coligado. He is with fed Stack. This is a 333 00:17:35.920 --> 00:17:39.359 new brand that's coming out of the smooth Stack organization 334 00:17:39.440 --> 00:17:42.400 that's been around for a while. They do it services, consulting, training, 335 00:17:42.680 --> 00:17:45.599 helping people learn how to do the jobs of the future, 336 00:17:45.599 --> 00:17:48.240 which are you know, it's the jobs of today, right 337 00:17:48.559 --> 00:17:51.799 staying on top of these systems and keeping them safe. 338 00:17:51.839 --> 00:17:55.119 Because if the government isn't safe, who is safe? Well, folks, 339 00:17:55.160 --> 00:17:58.720 don't touch that. Delby right back. You're listening to Inside Analysis. 340 00:18:04.759 --> 00:18:11.000 Welcome back to Inside Analysis. Here's your host, Eric Tabanac. 341 00:18:12.319 --> 00:18:14.880 All right, folks back here on Inside Analysis talking to 342 00:18:15.000 --> 00:18:18.400 Chris Coligato of fed Stack. This is a new brand 343 00:18:18.400 --> 00:18:21.160 that's coming out of smooth Stack and Chris in the 344 00:18:21.200 --> 00:18:23.839 last segment you were talking about how COVID was a 345 00:18:23.880 --> 00:18:26.160 forcing function. COVID kind of woke all of us up 346 00:18:26.200 --> 00:18:28.799 in lots of different ways, and we had to pay 347 00:18:28.880 --> 00:18:32.440 close attention to what we're doing. You have to create 348 00:18:32.480 --> 00:18:35.359 these immersive experiences for people. So I guess one question 349 00:18:35.400 --> 00:18:38.599 I'll ask you is VR. Are you using virtual reality 350 00:18:38.599 --> 00:18:39.640 for any of this training. 351 00:18:41.279 --> 00:18:44.359 We're starting to use VR in certain segments, especially in 352 00:18:44.400 --> 00:18:47.599 the enterprise side of things, because some of the clients 353 00:18:47.640 --> 00:18:51.920 are actually in the virtual reality environment. So we're experimenting 354 00:18:51.960 --> 00:18:55.000 a little bit of that, right, But again it goes 355 00:18:55.039 --> 00:18:57.599 back to learning learning preferences. 356 00:18:57.839 --> 00:18:59.079 So you know, if. 357 00:18:58.960 --> 00:19:03.000 We are looking at a cohort where they're really receptive 358 00:19:03.079 --> 00:19:07.720 to virtual reality, augmented reality type of learning process, we'll 359 00:19:07.759 --> 00:19:12.039 shore you'll surely explore that. Uh so far, it hasn't 360 00:19:12.039 --> 00:19:16.400 been much demand for that type of immersion levels, but 361 00:19:16.519 --> 00:19:18.079 something that they were definitely open to. 362 00:19:18.759 --> 00:19:19.359 Yeah. 363 00:19:19.440 --> 00:19:22.119 Well, let's let's dig back into the cybersecurity. I mean, 364 00:19:22.160 --> 00:19:24.839 how how do you stay on top of all the 365 00:19:24.920 --> 00:19:30.200 latest do you interface with companies like splunk or uh 366 00:19:30.400 --> 00:19:34.200 Solar Winds. Of course, they had their experience with being 367 00:19:34.240 --> 00:19:37.640 hacked themselves, which I thought was one of the craziest hacks. 368 00:19:37.640 --> 00:19:41.200 I mean, we've seen some really some bad hacks lately. 369 00:19:41.279 --> 00:19:43.880 Snowflake was hacked, a lot of customer data was stolen. 370 00:19:44.119 --> 00:19:45.960 How do you guys stay on top of the security 371 00:19:46.000 --> 00:19:48.359 space to make sure that you are training people for 372 00:19:48.440 --> 00:19:50.200 this new generation of technologies? 373 00:19:51.000 --> 00:19:53.640 So yeah, it goes you know, I actually just brought 374 00:19:53.640 --> 00:19:57.279 in one of our cybersecurity UH experts is going to 375 00:19:57.359 --> 00:20:00.599 be leading that US for our Tier one to consult arena. 376 00:20:01.200 --> 00:20:05.880 But you know, so far, we've been basically working our network, 377 00:20:07.160 --> 00:20:09.960 whether it's a product based you know, as you mentioned 378 00:20:10.200 --> 00:20:12.680 all all those things that you mentioned earlier, some of 379 00:20:12.720 --> 00:20:15.799 the product vendors but also even some of the training 380 00:20:16.240 --> 00:20:20.279 vendors that are out there, they're already delivering these types 381 00:20:20.319 --> 00:20:24.839 of methodologies in the defense and intel spaces. We keep 382 00:20:24.880 --> 00:20:27.119 track of that and we create a partnerships on how 383 00:20:27.119 --> 00:20:31.839 to actually develop the curriculum together. You know, they usually 384 00:20:31.880 --> 00:20:34.880 deliver a lot of these things either in a just 385 00:20:35.119 --> 00:20:39.400 urst of content more of a boot camp style content push, 386 00:20:39.480 --> 00:20:41.160 and some of them are very focused just on the 387 00:20:41.160 --> 00:20:44.480 certification side of it. That's when we're actually enriching a 388 00:20:44.559 --> 00:20:47.279 lot of the existing programs that are out there through 389 00:20:47.279 --> 00:20:51.480 our mirrored environment immersion that's kind of new. So we're 390 00:20:51.519 --> 00:20:54.240 partnering with a lot of the players out there, both 391 00:20:54.279 --> 00:20:59.640 product and trainers themselves, in order to deliver a differentiated offering. 392 00:21:00.279 --> 00:21:01.079 Yeah, that's interesting. 393 00:21:01.319 --> 00:21:03.440 And now do you also when you do this training 394 00:21:03.720 --> 00:21:06.119 and you follow all the way through, so you're helping 395 00:21:06.200 --> 00:21:09.480 folks get jobs at these organizations. 396 00:21:09.000 --> 00:21:11.880 And your clients. Is it any number of agencies? 397 00:21:11.920 --> 00:21:14.559 Are there specific agencies that you represent or is there 398 00:21:14.599 --> 00:21:19.279 a particular focus or one of the agencies that works 399 00:21:19.319 --> 00:21:20.960 with you the most, or tell me about that for 400 00:21:20.960 --> 00:21:21.519 a minute. 401 00:21:21.759 --> 00:21:26.240