1 00:00:06,080 --> 00:00:07,920 Speaker 1: Welcome to Fear and Greed Q and A where we 2 00:00:07,960 --> 00:00:11,719 Speaker 1: ask and answer questions about business, investing, economics, politics and more. 3 00:00:11,800 --> 00:00:15,560 Speaker 1: I'm Sean Aylmer. Software companies have been hit very hard 4 00:00:15,560 --> 00:00:19,400 Speaker 1: this year after AI tools raised questions about whether barriers 5 00:00:19,440 --> 00:00:22,720 Speaker 1: to entry in the sector were starting to disappear. The 6 00:00:22,800 --> 00:00:26,200 Speaker 1: sell off was sharp and in many cases indiscriminate, with 7 00:00:26,320 --> 00:00:29,319 Speaker 1: investors questioning whether the software businesses still have the same 8 00:00:29,320 --> 00:00:34,400 Speaker 1: long term advantage they once did so is software broken? 9 00:00:35,240 --> 00:00:38,440 Speaker 1: Is this the SaaS apocalypse or is this the major opportunity. 10 00:00:38,600 --> 00:00:41,600 Speaker 1: Remember this is general information only and you should seek 11 00:00:41,640 --> 00:00:45,880 Speaker 1: advice tailor to your circumstances before making investment decisions. Damon 12 00:00:45,960 --> 00:00:50,880 Speaker 1: Callahan is a partner investment at ECP Asset Management. Damon, 13 00:00:50,920 --> 00:00:52,080 Speaker 1: welcome back to Fear and Greed. 14 00:00:52,560 --> 00:00:53,360 Speaker 2: Thank you for having me. 15 00:00:54,280 --> 00:00:57,840 Speaker 1: The sell off in software has it been justified? Why 16 00:00:57,880 --> 00:00:58,560 Speaker 1: has it happened? 17 00:01:00,040 --> 00:01:02,280 Speaker 2: So if we just go back to you know, the 18 00:01:02,280 --> 00:01:04,960 Speaker 2: big sell off happened in the latter part of Genuarine. 19 00:01:04,959 --> 00:01:10,000 Speaker 2: It's early feb and it happened because coding tools, the 20 00:01:10,120 --> 00:01:13,119 Speaker 2: likes of claud Code most people have heard of, hit 21 00:01:13,160 --> 00:01:16,920 Speaker 2: a point of productivity where it was becoming clear that 22 00:01:17,000 --> 00:01:20,160 Speaker 2: the way software written was changing. Many of the best 23 00:01:20,160 --> 00:01:23,360 Speaker 2: engineers don't write code anymore, at least there's the anecdotes 24 00:01:23,440 --> 00:01:27,440 Speaker 2: we're hearing. You know, they're really focusing on architecture, stepping 25 00:01:27,520 --> 00:01:30,600 Speaker 2: back and letting the models work, but obviously going through 26 00:01:30,600 --> 00:01:33,120 Speaker 2: a process of working with the models to tease out 27 00:01:33,959 --> 00:01:36,720 Speaker 2: big chunks of code at a time. And the consequence 28 00:01:36,760 --> 00:01:39,759 Speaker 2: of that was a lot of people stepping back hearing 29 00:01:39,800 --> 00:01:44,520 Speaker 2: this and saying, well, software is going to be commoditized. 30 00:01:44,560 --> 00:01:48,160 Speaker 2: There's going to be infinite coding resource available to everyone, 31 00:01:48,280 --> 00:01:52,000 Speaker 2: and therefore all businesses in the world of software are 32 00:01:52,040 --> 00:01:56,160 Speaker 2: going to become increasingly competitive and it's not an investable 33 00:01:56,200 --> 00:02:00,880 Speaker 2: space anymore. And that was reflected in how the cohort 34 00:02:01,520 --> 00:02:06,440 Speaker 2: of equities in software traded broadly. And my response to 35 00:02:06,600 --> 00:02:07,920 Speaker 2: you know, is it dead or is there a big 36 00:02:07,920 --> 00:02:10,919 Speaker 2: opportunity is that it should be looked at very selectively, 37 00:02:11,160 --> 00:02:13,160 Speaker 2: and that's the way software alwayshould have been looked at. 38 00:02:13,360 --> 00:02:15,840 Speaker 2: No business is a great business just because it's software. 39 00:02:16,080 --> 00:02:20,800 Speaker 2: Software is just a digital delivery mechanism for solving someone's problem, 40 00:02:20,880 --> 00:02:24,240 Speaker 2: much the same way as bricks and mortar is via 41 00:02:24,400 --> 00:02:27,480 Speaker 2: a non digital channel and so you know, the basis 42 00:02:27,480 --> 00:02:31,600 Speaker 2: of owning a software company needs to be looked at 43 00:02:31,720 --> 00:02:35,120 Speaker 2: from you know, what is special about this business? You 44 00:02:35,120 --> 00:02:37,920 Speaker 2: know what we think about that as is the competitive 45 00:02:37,960 --> 00:02:41,720 Speaker 2: advantage that a software business has. And that's something I 46 00:02:41,720 --> 00:02:43,720 Speaker 2: think an investor really needs to understand if they want 47 00:02:43,760 --> 00:02:47,160 Speaker 2: to dive in. If they can find businesses with very 48 00:02:47,200 --> 00:02:50,280 Speaker 2: strong competitive advantages, this is the environment where you're going 49 00:02:50,320 --> 00:02:54,480 Speaker 2: to find exceptional opportunities. But I would tread carefully because 50 00:02:54,720 --> 00:02:58,320 Speaker 2: increasingly there are other businesses that aren't that great in 51 00:02:58,360 --> 00:03:02,800 Speaker 2: the software world that will be increasingly commoditized. So you know, 52 00:03:02,919 --> 00:03:03,640 Speaker 2: it's not what you're doing. 53 00:03:04,280 --> 00:03:06,320 Speaker 1: Yeah, I mean that all makes sense. I suppose the 54 00:03:06,639 --> 00:03:09,680 Speaker 1: trick is, how do you know which ones will be 55 00:03:09,760 --> 00:03:15,720 Speaker 1: okay and which ones won't? Because the speed of adoption 56 00:03:15,919 --> 00:03:20,560 Speaker 1: of AI and the latest versions of AI, be at 57 00:03:20,639 --> 00:03:27,040 Speaker 1: Claude or Gemini or Anthropic, how do you know which 58 00:03:27,080 --> 00:03:30,080 Speaker 1: ones again, which ones are going to actually survive, Which 59 00:03:30,560 --> 00:03:32,919 Speaker 1: software as a service provider companies are going to survive 60 00:03:32,960 --> 00:03:33,560 Speaker 1: and which won't. 61 00:03:34,440 --> 00:03:38,760 Speaker 2: So good question, Sean. So the starting point for owning 62 00:03:38,760 --> 00:03:40,720 Speaker 2: a business should never have been because it was software, 63 00:03:41,080 --> 00:03:43,880 Speaker 2: and so then you know the way to think about 64 00:03:43,960 --> 00:03:47,360 Speaker 2: this via analogy is if we were looking at a 65 00:03:47,360 --> 00:03:50,560 Speaker 2: software business at Ecpuset Management, we would have thought about, 66 00:03:51,400 --> 00:03:55,480 Speaker 2: you know, pre twenty twenty five, say, if venture capital 67 00:03:56,000 --> 00:03:58,680 Speaker 2: with very deep pockets decided they wanted to compete in 68 00:03:58,680 --> 00:04:02,920 Speaker 2: this industry and could throw immense amount of develop a 69 00:04:03,000 --> 00:04:06,960 Speaker 2: resource at competing with a particular business, how a threat 70 00:04:07,000 --> 00:04:09,480 Speaker 2: are they? And that then forces you to do away 71 00:04:09,520 --> 00:04:11,440 Speaker 2: with whether or not the software is any good, because 72 00:04:11,480 --> 00:04:13,800 Speaker 2: anyone can build good software with enough time and money. 73 00:04:14,240 --> 00:04:15,880 Speaker 2: You've got to think about what are the assets they 74 00:04:15,960 --> 00:04:21,719 Speaker 2: have that prevent competition? And so, to answer your question explicitly, 75 00:04:22,160 --> 00:04:24,440 Speaker 2: what are the competitive advantages that you can have are 76 00:04:24,480 --> 00:04:28,480 Speaker 2: really strong in software? There's a few ones that I'd 77 00:04:28,520 --> 00:04:31,039 Speaker 2: call out, namely that we see a lot of patterns 78 00:04:31,080 --> 00:04:35,680 Speaker 2: of in our investment experience. Two that I'll name so firstly, 79 00:04:35,720 --> 00:04:38,880 Speaker 2: one is enterprise grade data. What that can look like 80 00:04:39,120 --> 00:04:45,040 Speaker 2: is decades of customer contributed data to your business that 81 00:04:45,160 --> 00:04:48,360 Speaker 2: is proprietary to you, which means that you have, say, 82 00:04:49,200 --> 00:04:52,200 Speaker 2: exceptional risk models that no one with infinite coding can 83 00:04:52,240 --> 00:04:55,200 Speaker 2: replicate because they haven't been in your market and experienced 84 00:04:55,720 --> 00:04:58,200 Speaker 2: what you've experienced with the customer base. And developed around 85 00:04:58,200 --> 00:05:03,799 Speaker 2: over time. An example could be deep understanding of industry 86 00:05:03,839 --> 00:05:07,840 Speaker 2: workflow configurations that you can only get from being in 87 00:05:07,880 --> 00:05:10,800 Speaker 2: an industry vertical for a long period of time, developing 88 00:05:10,920 --> 00:05:14,799 Speaker 2: software to solve all the edge cases of customer problems. 89 00:05:15,520 --> 00:05:19,440 Speaker 2: That is, software is just the delivery mechanism. You're solving 90 00:05:19,440 --> 00:05:23,000 Speaker 2: a problem, and you've developed a reputation around doing that, 91 00:05:23,200 --> 00:05:25,359 Speaker 2: which is why you have the ability to charge the 92 00:05:25,400 --> 00:05:28,240 Speaker 2: fees you charge. The last one I'd mentioned is that 93 00:05:28,760 --> 00:05:31,360 Speaker 2: the reputation of a software company. So we don't think 94 00:05:31,400 --> 00:05:34,520 Speaker 2: about brand the same way we would in consumer In software, 95 00:05:34,520 --> 00:05:38,320 Speaker 2: think about reputational advantage, and it's particularly important in enterprise software. 96 00:05:38,520 --> 00:05:41,120 Speaker 2: So give a simple example. There is a reason the 97 00:05:41,520 --> 00:05:45,080 Speaker 2: saying no one gets fired for hiring IBM. And we're 98 00:05:45,120 --> 00:05:48,000 Speaker 2: all aware of the concept of the institutional imperative where 99 00:05:48,040 --> 00:05:51,880 Speaker 2: a lot of major enterprise customers look around at their 100 00:05:51,880 --> 00:05:54,120 Speaker 2: peers and say, well, what are they using? Because if 101 00:05:54,160 --> 00:05:56,960 Speaker 2: you're the CIO and you're going to make a major 102 00:05:57,000 --> 00:06:01,080 Speaker 2: digital modernization in your workforce, you're not going to take 103 00:06:01,120 --> 00:06:03,120 Speaker 2: a risk on a startup. And the reason you're not 104 00:06:03,160 --> 00:06:04,520 Speaker 2: going to do that is because you don't want to 105 00:06:04,560 --> 00:06:06,880 Speaker 2: have to go to the board and explain why taking 106 00:06:06,920 --> 00:06:09,960 Speaker 2: that risk failed and there was cost overruns and delays, 107 00:06:10,000 --> 00:06:12,760 Speaker 2: and now you're behind track and the competitors who made 108 00:06:12,760 --> 00:06:14,920 Speaker 2: the safe choice or ahead of you because you're putting 109 00:06:14,920 --> 00:06:17,440 Speaker 2: your job on the line. And so we think about 110 00:06:17,760 --> 00:06:22,239 Speaker 2: if this particular software company has demonstrated over a decade 111 00:06:22,279 --> 00:06:26,400 Speaker 2: that they've implemented their software and they've done that successfully 112 00:06:26,440 --> 00:06:29,920 Speaker 2: with the majority of the major potential customers in an industry, 113 00:06:30,160 --> 00:06:33,520 Speaker 2: and players number two and three are nowhere as far 114 00:06:33,640 --> 00:06:36,360 Speaker 2: as progressed. That's really interesting to us because it says 115 00:06:36,400 --> 00:06:40,560 Speaker 2: there's a reputational advantage that is effectively a very very 116 00:06:40,640 --> 00:06:44,240 Speaker 2: valuable resource that's very hard to replicate again cannot be 117 00:06:44,279 --> 00:06:48,400 Speaker 2: replicated with infinite coding resource. So that's the way you 118 00:06:48,480 --> 00:06:50,720 Speaker 2: find the good companies. The way we think about the 119 00:06:50,720 --> 00:06:53,400 Speaker 2: bad ones is, you know, if they don't have any 120 00:06:53,440 --> 00:06:56,920 Speaker 2: special data assets, they don't have any particular reputational advantage. 121 00:06:57,120 --> 00:07:01,480 Speaker 2: They're just another software, simple software application with many look 122 00:07:01,520 --> 00:07:04,240 Speaker 2: alike competitors. That is a place I'd want to avoid 123 00:07:04,360 --> 00:07:05,880 Speaker 2: because that is a place is going to be at 124 00:07:05,920 --> 00:07:09,279 Speaker 2: more and more competitive this everybody is racing ahead with 125 00:07:09,360 --> 00:07:10,840 Speaker 2: better solutions. 126 00:07:11,000 --> 00:07:16,320 Speaker 1: Okay, you mentioned wise tech can just park personnel issues 127 00:07:16,360 --> 00:07:18,440 Speaker 1: at wis Tech because there's fairly going on at that 128 00:07:18,600 --> 00:07:22,040 Speaker 1: very senior level. But in terms of the technology it 129 00:07:22,160 --> 00:07:26,920 Speaker 1: has and the brand it has, is that a good example? 130 00:07:27,400 --> 00:07:29,000 Speaker 1: I mean, it's a bit difficult one to talk about 131 00:07:29,080 --> 00:07:32,559 Speaker 1: right now, but you know, just parking the controversy there 132 00:07:32,760 --> 00:07:35,840 Speaker 1: is that a good one In terms of the threat 133 00:07:35,960 --> 00:07:39,680 Speaker 1: of AI are you're saying that product is good enough 134 00:07:39,720 --> 00:07:40,280 Speaker 1: to get through. 135 00:07:41,360 --> 00:07:44,640 Speaker 2: Yeah, So, I mean, let's just focus on the business. 136 00:07:44,880 --> 00:07:50,440 Speaker 2: The problems that wise techs solve for the world's largest 137 00:07:50,520 --> 00:07:55,160 Speaker 2: third party logistics service providers are immense. It's not just 138 00:07:55,200 --> 00:07:59,240 Speaker 2: a simple case of moving cargo across an ocean or 139 00:07:59,280 --> 00:08:02,600 Speaker 2: airliner country A to country B. We're talking about the 140 00:08:02,600 --> 00:08:08,080 Speaker 2: complexity of dealing with customs integrations at the borders of 141 00:08:08,240 --> 00:08:13,400 Speaker 2: eighty five percent of manufacturing trade flows globally. So what 142 00:08:13,440 --> 00:08:16,960 Speaker 2: that looks like is a company, a software company that 143 00:08:17,080 --> 00:08:22,720 Speaker 2: has to maintain over one hundred and seventy customs regulator 144 00:08:23,160 --> 00:08:26,560 Speaker 2: integrations at every border that needs to be government certified. 145 00:08:26,920 --> 00:08:29,800 Speaker 2: And what that means is that is not something you 146 00:08:29,800 --> 00:08:32,920 Speaker 2: can just replicate with with infinite coding resource that takes 147 00:08:33,040 --> 00:08:35,640 Speaker 2: genuine time, and you need to demonstrate to the regulator 148 00:08:35,640 --> 00:08:38,920 Speaker 2: that you should have a license to operate. And then 149 00:08:38,960 --> 00:08:40,880 Speaker 2: after you have that license to operate, you have to 150 00:08:40,880 --> 00:08:45,320 Speaker 2: deal with tens of millions of customs classifications changes annually 151 00:08:45,840 --> 00:08:48,959 Speaker 2: and your customers that the logistics companies that use your 152 00:08:49,000 --> 00:08:52,880 Speaker 2: software rely on wise tech to get to get that 153 00:08:53,080 --> 00:08:56,040 Speaker 2: right because if they don't, they misclassify goods in moving 154 00:08:56,040 --> 00:08:59,880 Speaker 2: them around the world the significant fine implications. So you know, 155 00:09:00,080 --> 00:09:02,120 Speaker 2: the complexity, that's just one part of their business. The 156 00:09:02,160 --> 00:09:06,320 Speaker 2: complexity doesn't come just from the software, and that is 157 00:09:06,360 --> 00:09:08,920 Speaker 2: complex like you need to have been in that industry 158 00:09:09,000 --> 00:09:13,320 Speaker 2: for decades to understand the workflow to build up, to 159 00:09:13,360 --> 00:09:15,800 Speaker 2: build that workflow up and demonstrate to the regulators and 160 00:09:15,840 --> 00:09:18,960 Speaker 2: demonstrate to the customers you know, and earn revenue along 161 00:09:18,960 --> 00:09:21,440 Speaker 2: the way to fund that. R and D. Being a 162 00:09:21,480 --> 00:09:24,439 Speaker 2: startup or a sub tier operator and just having more 163 00:09:24,480 --> 00:09:27,240 Speaker 2: coding and infinite coding if we want to be extreme 164 00:09:27,320 --> 00:09:30,960 Speaker 2: capability doesn't give you that right to play. And the 165 00:09:31,000 --> 00:09:32,800 Speaker 2: other thing that needs to be mentioned is you think 166 00:09:32,800 --> 00:09:35,400 Speaker 2: about the complexity of their problems that they're solving, and 167 00:09:35,440 --> 00:09:37,640 Speaker 2: you spend five minutes listening to their investigator think about 168 00:09:37,640 --> 00:09:40,280 Speaker 2: the problems they yet want to solve. They also have 169 00:09:40,400 --> 00:09:44,440 Speaker 2: access to these tools, and they have genuine engineering competency 170 00:09:44,600 --> 00:09:47,520 Speaker 2: at the C suite in their business, so their ability 171 00:09:47,880 --> 00:09:51,199 Speaker 2: to develop at a faster rate and move the goalposts 172 00:09:51,720 --> 00:09:56,280 Speaker 2: faster than anyone startup or as I said, sub tier 173 00:09:57,160 --> 00:10:00,240 Speaker 2: second tier operator could catch up. I mean that that's 174 00:10:00,280 --> 00:10:02,760 Speaker 2: what would make them a prime example of a business 175 00:10:02,760 --> 00:10:05,240 Speaker 2: that is better in this environment, not worse. 176 00:10:06,000 --> 00:10:07,600 Speaker 1: I mean, we're out of time, but it's kind of 177 00:10:07,600 --> 00:10:10,600 Speaker 1: like the fundamentals still matter, and I mean it's sort 178 00:10:10,600 --> 00:10:14,240 Speaker 1: of self evident, I know, but even in an AI world, 179 00:10:14,360 --> 00:10:16,040 Speaker 1: business fundamentals matter. 180 00:10:16,480 --> 00:10:18,599 Speaker 2: Yeah. This is a long conversation, Sean, so happy to 181 00:10:18,600 --> 00:10:19,880 Speaker 2: pick it up with you again anytime. 182 00:10:20,080 --> 00:10:22,400 Speaker 1: Fantastic Damon, thanks for talking to Fear and Greed. 183 00:10:22,600 --> 00:10:23,280 Speaker 2: Appreciate it. 184 00:10:23,480 --> 00:10:27,480 Speaker 1: That was Damon Callahan from ECP Asset Management. Remember to 185 00:10:27,480 --> 00:10:31,000 Speaker 1: seek advice from Taylor to your circumstances for making investment decisions. 186 00:10:31,120 --> 00:10:33,160 Speaker 1: I'm Sean Almer and this is Fearing Greed Q and 187 00:10:33,240 --> 00:10:33,280 Speaker 1: a