1 00:00:07,778 --> 00:00:09,919 Welcome back to Adventures in DevOps. 2 00:00:09,919 --> 00:00:13,340 I've never heard anyone say we need viewer tests. 3 00:00:13,340 --> 00:00:22,673 And that's why we've grabbed almost 20-year veteran in building reliable software, executive consultant, and is currently the CEO and founder at Itacama, where they're 4 00:00:22,673 --> 00:00:29,955 guiding businesses to success or forcing them when necessary to adopt the best practices that the industry has already known about for decades. 5 00:00:29,955 --> 00:00:32,556 Pia Viedemeyer, welcome to the show. 6 00:00:32,588 --> 00:00:33,335 Hi, Warren. 7 00:00:33,335 --> 00:00:34,562 Thanks for having me. 8 00:00:34,562 --> 00:00:36,924 I think we just have to get this out of the way first. 9 00:00:36,924 --> 00:00:41,407 I see almost two modes in every company I've ever interviewed or interacted with. 10 00:00:41,407 --> 00:00:46,150 That's the no quality whatsoever, uh, because it's no one's responsibility. 11 00:00:46,150 --> 00:00:56,637 Or no quality whatsoever because there's a single person, team, or organization with quality in their name, effectively isolating from the whole system, having quality built 12 00:00:56,637 --> 00:00:57,197 into it. 13 00:00:57,197 --> 00:00:58,728 How does this even happen? 14 00:00:59,070 --> 00:01:00,071 my god. 15 00:01:00,071 --> 00:01:05,503 If I if I would know how that happens, dear, I think I'll be a billionaire already. 16 00:01:07,415 --> 00:01:12,658 Honestly, I feel there is so much history behind that. 17 00:01:12,658 --> 00:01:18,161 Well, I used to work for quite a long time in in so called quality roles. 18 00:01:18,161 --> 00:01:24,784 So I had the quality or the testing thing in my in my job title and only just recently got into a company. 19 00:01:24,784 --> 00:01:27,810 But I can tell you a bit more on that later where 20 00:01:27,810 --> 00:01:36,943 there was like this, okay, no quality, we don't not we don't need it, but there is no like person or or department responsible for that. 21 00:01:36,943 --> 00:01:46,296 I feel like it for me it it's a lot about okay how we used to work in uh in a waterfall way. 22 00:01:46,296 --> 00:01:51,348 When like right, so this one after the other and it seemed to be clear that okay 23 00:01:51,348 --> 00:02:02,317 My as a as a business analyst, for example, my responsibility is to write all the requirements, pixel perfect, a hundred percent, and then I'll hand it over to developers 24 00:02:02,317 --> 00:02:06,831 and then they take care of it and they do the developing, writing, coding stuff. 25 00:02:06,831 --> 00:02:15,819 And then when they are done and and that used to to be um defined by okay, the code is there, but testing is not part of my job. 26 00:02:15,819 --> 00:02:17,180 I've experienced that a lot. 27 00:02:17,180 --> 00:02:18,752 Not so much anymore these days. 28 00:02:18,752 --> 00:02:19,722 That's good. 29 00:02:19,824 --> 00:02:31,445 but then, you know, it got handed over to this, there is the quality person, department, team, whoever, and they will magically, you know, build that quality in or test it in or 30 00:02:31,445 --> 00:02:34,408 and I never understood how that should happen. 31 00:02:34,408 --> 00:02:36,911 How how this should work. 32 00:02:36,911 --> 00:02:40,584 It it just seemed stupid to me from the very beginning. 33 00:02:40,584 --> 00:02:49,490 Do you do you think that it's heavily related to the fact that people are trying to well identify what their core responsibilities are in in their job or in the organization that 34 00:02:49,490 --> 00:02:50,441 they're in? 35 00:02:50,441 --> 00:02:56,245 And for them that means identifying like my job starts here at this point and ends over here. 36 00:02:56,245 --> 00:03:02,509 And for the parts that they feel like they understand and have the capability to actually do, they put that within scope. 37 00:03:02,509 --> 00:03:09,154 And for everything that they feel not comfortable doing, they try to just find someone else to be responsible for that. 38 00:03:09,154 --> 00:03:11,635 And it may not even be you know, totally conscious. 39 00:03:11,635 --> 00:03:13,896 It may just be like, okay, I can do this. 40 00:03:13,896 --> 00:03:19,298 I was pr hired as this because my title is, as you said, you know, business analyst or software engineer. 41 00:03:19,438 --> 00:03:24,360 And if you're the analyst and you say, Well, okay, that there's software engineers or developers at my company. 42 00:03:24,360 --> 00:03:26,501 I don't do the code, I just do this part. 43 00:03:26,501 --> 00:03:30,363 And then someone else magically takes over a responsibility for that. 44 00:03:30,363 --> 00:03:32,474 I can imagine the same thing happening elsewhere. 45 00:03:32,474 --> 00:03:38,688 I don't remember going through my own academic career and being taught how to 46 00:03:38,688 --> 00:03:40,728 make tests or make reliable software. 47 00:03:40,728 --> 00:03:44,503 Like that was never a core uh aspect to what we were building. 48 00:03:44,503 --> 00:03:53,251 So I can totally understand where if you get to the professional arena and you get into a job which says you are a software engineer, you still don't think you need to do testing. 49 00:03:53,251 --> 00:04:01,204 And especially not if you had a an organization present in your company that says, you know, we are responsible for, you know, QA. 50 00:04:01,204 --> 00:04:01,815 Mm-hmm. 51 00:04:01,815 --> 00:04:02,395 Yeah. 52 00:04:02,395 --> 00:04:03,996 Yeah, absolutely. 53 00:04:04,017 --> 00:04:07,169 And I think it's it's very human, right? 54 00:04:07,169 --> 00:04:14,616 So it it helps us to have these clear definitions or guardrails like this is your job from here to there. 55 00:04:14,616 --> 00:04:16,568 It gives us security. 56 00:04:16,568 --> 00:04:22,123 And and as human beings we we like that kind of, but also we we like to have freedom. 57 00:04:22,123 --> 00:04:27,906 So I think it it's all in the mix, but I feel it helps people to have this, I don't know. 58 00:04:27,906 --> 00:04:37,193 job role definition and then whatever is written in there helps you to orient yourself in the organization, in the company. 59 00:04:37,193 --> 00:04:40,194 It gives you a feeling of belonging to this or that group. 60 00:04:40,194 --> 00:04:52,243 Of course, there are always different types of people and characters and people that are more open or or curious to to learn and to, you know, look over the fence and see what 61 00:04:52,243 --> 00:04:55,325 what the other roles are doing, what their job is. 62 00:04:55,325 --> 00:04:56,930 And then there are other people that 63 00:04:56,930 --> 00:05:04,596 don't feel like that or they they feel good where they are and they like to to work like stay in their garden and be the masters there. 64 00:05:04,596 --> 00:05:07,358 And I think both is okay. 65 00:05:07,358 --> 00:05:18,567 But what I don't like is just, you know, giving away responsibility for or ownership for a product that we are all together working on. 66 00:05:18,567 --> 00:05:18,857 Right. 67 00:05:18,857 --> 00:05:23,234 Because like if you work on a software product, I I don't care if you are like 68 00:05:23,234 --> 00:05:35,283 a scrum team or an agile whatever team or if you're organized um in in in silos or tradition more traditional ways or any any kind of way I don't care it's like you build 69 00:05:35,283 --> 00:05:37,545 that one product together. 70 00:05:37,545 --> 00:05:44,991 So it's you all have to take your your the ownership for for that product and so forth quality. 71 00:05:44,991 --> 00:05:47,554 No, I I totally I I I absolutely agree. 72 00:05:47,554 --> 00:05:57,499 I I think one of the challenges there is on the flip side uh of the other extreme is you have these giant meetings with 150 people in them where everyone's responsible for getting 73 00:05:57,499 --> 00:05:58,734 the product out. 74 00:05:58,734 --> 00:06:08,379 And then those meetings no are also not effective in in some regard because I don't know how you can ever do something useful in a meeting with 150 people in it where it's not 75 00:06:08,379 --> 00:06:14,214 like a broadcast meeting or a meeting where uh you know you're you're going over maybe the the current status of the company or something. 76 00:06:14,214 --> 00:06:16,744 Like it's not it's not the level where everyone can participate. 77 00:06:16,744 --> 00:06:25,679 So how do you find the sweet spot here between uh having the individual teams or team members completely isolated and only working on the parts that they think they should be 78 00:06:25,679 --> 00:06:28,152 working on and having too many people 79 00:06:28,152 --> 00:06:29,025 present in the meeting. 80 00:06:29,025 --> 00:06:30,796 Like how do you know who should actually be there? 81 00:06:30,796 --> 00:06:33,107 So first I would always start small, right? 82 00:06:33,107 --> 00:06:35,098 Um because I I totally agree. 83 00:06:35,098 --> 00:06:48,144 Like it there is no point of like having like this many people uh in one room and I would f start with people who are interested in okay, how how do we make sure that our product 84 00:06:48,144 --> 00:06:53,936 is the right product and and does what it should and and makes the users happy in the end. 85 00:06:53,936 --> 00:06:58,280 I like the word build in quality and I don't care about any framework. 86 00:06:58,280 --> 00:07:00,281 Um just to say that right in the beginning. 87 00:07:00,281 --> 00:07:09,495 But for me really it it's all about building quality into the product from the very beginning until until production and and maintenance and all that stuff. 88 00:07:09,495 --> 00:07:22,820 When I used to work in like separate testing teams, I always tried to find some way to go to connect to to the developers, whether this is at the coffee machine and you know, just 89 00:07:22,820 --> 00:07:26,586 having a chat and and asking them, okay, what what feature are you working on today? 90 00:07:26,586 --> 00:07:27,444 And then 91 00:07:27,444 --> 00:07:32,046 most of the people are super open to just tell you because it's their baby, right? 92 00:07:32,046 --> 00:07:35,117 They they built it, they are proud of it. 93 00:07:35,117 --> 00:07:38,859 And then you just, you know, you have already your conversation started. 94 00:07:38,859 --> 00:07:43,120 And I I was always curious to to see how that works. 95 00:07:43,120 --> 00:07:44,471 Like all in the background. 96 00:07:44,471 --> 00:07:52,594 I mean I have a very basic knowledge about um well like one semester at university or so in coding and nobody wants me to code. 97 00:07:52,594 --> 00:07:57,366 But I'm actually able to follow when somebody shows me something, I can follow. 98 00:07:57,510 --> 00:08:07,459 And uh and yeah, it and I'm always curious about how how they build up things and how all the things connect together with all the you know interfaces and all that stuff. 99 00:08:07,459 --> 00:08:15,206 And from my experience, just show interest in the people you work with and just just ask them, Hey, what are you doing? 100 00:08:15,206 --> 00:08:16,347 Can you show me? 101 00:08:16,347 --> 00:08:19,210 And then you're there, right next to them at your desk. 102 00:08:19,210 --> 00:08:23,733 And then uh for example, you could ask or I ask them, okay, cool. 103 00:08:23,733 --> 00:08:24,428 So 104 00:08:24,428 --> 00:08:34,085 How how do you make sure that this won't crash when we, you know, connect it with all the other parts of the of the application or of with the surrounding systems? 105 00:08:34,085 --> 00:08:36,546 And then I go, Oh yeah, well, good point. 106 00:08:36,546 --> 00:08:42,310 Well, I have my unit test, but actually I did not think too much about integration tests yet. 107 00:08:42,310 --> 00:08:45,652 Then I what about this and that? 108 00:08:45,652 --> 00:08:48,386 Have you thought about or maybe why? 109 00:08:48,386 --> 00:08:51,188 haven't you thought about connecting this or that system? 110 00:08:51,188 --> 00:09:00,496 And then you have uh I never got like stopped in a way that like people didn't tell me like I why are you asking me those things? 111 00:09:00,496 --> 00:09:07,981 You will see you will see the the feature when it gets shipped to your QA environment and then you can take a look. 112 00:09:07,981 --> 00:09:08,322 Right. 113 00:09:08,322 --> 00:09:09,102 So 114 00:09:09,718 --> 00:09:17,981 I I'm surprised you never ran into I mean, 'cause you mentioned that uh engineers may or who it's not necessarily an engineer, but anyone who's built a a uh product or a project 115 00:09:17,981 --> 00:09:22,860 themselves and consider it their their their baby, to go up to them and ask them questions. 116 00:09:22,860 --> 00:09:29,174 I I feel like there is this historical challenge of i professionally even 117 00:09:29,174 --> 00:09:38,971 to not crush the f the fragile fragile developer ego that comes with owning a thing and to come up to them and, you know, suggest that maybe part of it is broken or isn't working 118 00:09:38,971 --> 00:09:39,492 right. 119 00:09:39,492 --> 00:09:43,378 I I'm you must have run into uh issues like that. 120 00:09:43,418 --> 00:09:43,838 yes. 121 00:09:43,838 --> 00:09:44,428 Yeah, yeah, yeah. 122 00:09:44,428 --> 00:09:45,139 I did. 123 00:09:45,139 --> 00:09:45,509 I did. 124 00:09:45,509 --> 00:09:57,606 But for me, like the the the the big difference or what made the big difference for me was when I actually proactively approached them in a very positive way, showing them respect 125 00:09:57,606 --> 00:09:58,767 for their work. 126 00:09:58,767 --> 00:10:01,278 Because I think it's I had a hard job, right? 127 00:10:01,278 --> 00:10:12,248 I mean I don't I also I didn't like to, you know, always be the one at the end of the process having to tell other people who put a lot of effort into their work. 128 00:10:12,248 --> 00:10:17,022 To tell them this is not good, this is not working, or this is shitty, or whatever. 129 00:10:17,022 --> 00:10:20,525 Of course they they didn't like to hear that. 130 00:10:20,525 --> 00:10:22,346 Um nobody likes to hear that. 131 00:10:22,346 --> 00:10:34,487 Yeah, for me, I very soon in my career found out that I want to do it differently, to to find a different approach that works for myself and to connect to the human and not only 132 00:10:34,487 --> 00:10:40,990 talk about like this the the technical product and that makes a big difference um for me. 133 00:10:40,990 --> 00:10:43,421 And and also for for the people I worked with. 134 00:10:43,421 --> 00:10:50,182 Of course, nobody, not everybody was open to my suggestions, no matter which way I tried. 135 00:10:50,182 --> 00:10:51,616 Um, but that's okay. 136 00:10:51,616 --> 00:11:00,040 But most of them, when I really, you know, I came out of my testing room, I crossed the hallway, I went to the other office, and there I was. 137 00:11:00,040 --> 00:11:04,082 And then like, you know, the first time is the tester, right? 138 00:11:04,363 --> 00:11:07,294 She made probably she found the park or more than one. 139 00:11:07,294 --> 00:11:08,045 Right. 140 00:11:08,045 --> 00:11:10,424 And then I was like, So I was like, Hey, how are you doing? 141 00:11:10,424 --> 00:11:11,455 What are you working on? 142 00:11:11,455 --> 00:11:12,977 Yeah, but yeah. 143 00:11:12,977 --> 00:11:17,042 Most of them opened up and they just thought, okay, she's a human too. 144 00:11:17,042 --> 00:11:18,925 Okay, she's interested in what we're doing. 145 00:11:18,925 --> 00:11:20,366 And then also I got it back. 146 00:11:20,366 --> 00:11:23,991 I really believe in what you send out comes back to you. 147 00:11:23,991 --> 00:11:29,824 And when you send out like, you know, positivity and respect to other people, then then this comes back. 148 00:11:29,824 --> 00:11:40,753 And so I I feel like it's natural then that you graduated from uh working with just software engineers and and I I feel like testing is such a dirty word sometimes, uh 149 00:11:40,753 --> 00:11:49,641 validating, you know, what was actually being built and that it was being built correctly, uh, not necessarily just from a technical side, to uh consulting for for companies and 150 00:11:49,641 --> 00:11:58,698 running your own to do executive consulting or helping companies, organizations transition from building software in their current modes to something more. 151 00:11:58,832 --> 00:12:00,463 reliable or sustainable in that way. 152 00:12:00,463 --> 00:12:07,809 And I I feel like uh from what I saw on your on your profiles, they're usually about changing organizational structures. 153 00:12:07,809 --> 00:12:17,527 And something that you actually mentioned earlier was that uh you see less of a challenge now with testing than you had seen historically. 154 00:12:17,527 --> 00:12:24,460 And I don't know if you were alluding to something specific that's happened recently uh for that transition or or something else. 155 00:12:24,460 --> 00:12:29,825 Well, let's see if it if it goes into the other direction again now with with our AI helpers. 156 00:12:29,825 --> 00:12:40,453 But yeah, so so recently what I mean, um I've met more and more people, not only developers, um, like basically like everybody you have working on a on a software product, 157 00:12:40,453 --> 00:12:42,996 uh all the different roles, whatever they are called. 158 00:12:42,996 --> 00:12:52,920 I feel like that more and more people are interested in, you know, the other disciplines and learning a bit more here and there, just to 159 00:12:52,920 --> 00:13:00,416 to be more effective, productive as a team and and to also be able to support each other better. 160 00:13:00,462 --> 00:13:04,097 I was gonna say, I want your career experiences because you seem like such the optimist. 161 00:13:04,097 --> 00:13:08,491 Like everything's been great, you know, people are working and want to collaborate together. 162 00:13:08,491 --> 00:13:10,070 And here I am thinking like 163 00:13:10,070 --> 00:13:11,532 Is my experience unique? 164 00:13:11,532 --> 00:13:13,164 You know, am I am I the one? 165 00:13:13,164 --> 00:13:17,839 Or maybe I'm the problem where I've seen uh I remember some of my early jobs. 166 00:13:17,839 --> 00:13:27,590 Like if if I met someone in QA, they were they were on some sort of social media for 90% of the time until right after code freeze, where they would review stuff. 167 00:13:27,590 --> 00:13:31,494 And then you'd get the most ridiculous questions ever, like 168 00:13:31,532 --> 00:13:34,194 Why doesn't this work according to our testing documents? 169 00:13:34,194 --> 00:13:36,505 And I'm like, I don't know what is in your testing documents. 170 00:13:36,505 --> 00:13:38,447 Maybe your testing documents are wrong. 171 00:13:38,447 --> 00:13:50,255 And so it it's great to see this other perspective that even if organizations aren't set up optimally, that there are there have been companies and uh engineering orgs that have 172 00:13:50,255 --> 00:13:55,436 been able to figure out their way through it and still evaluate and build software correctly. 173 00:13:55,436 --> 00:14:00,518 Yeah, but I mean not not everything is is perfect, also in my experience. 174 00:14:00,518 --> 00:14:06,730 So I have been working with those teams and those organizations where I felt like I am the problem. 175 00:14:06,730 --> 00:14:09,851 Like it's it's like like okay, they don't get it. 176 00:14:09,851 --> 00:14:12,352 I have no idea what else to do. 177 00:14:12,352 --> 00:14:20,256 And there were points in my career where I decided to leave a project because there was th they didn't get it. 178 00:14:20,256 --> 00:14:31,394 I was like really I was the unicorn and they they gave me the feeling that I'm totally crazy and what I ask or what I want to do is just bullshit. 179 00:14:31,394 --> 00:14:41,070 So I said, Okay guys, then if you wanna tell me how quality assurance or or building quality works, I'm the wrong person. 180 00:14:41,070 --> 00:14:43,808 Because I wanna make sure that we all together 181 00:14:43,808 --> 00:14:48,261 like a line and make sure we build a cool and and high quality product. 182 00:14:48,261 --> 00:14:48,721 Of course. 183 00:14:48,721 --> 00:14:52,483 There are those those folks and it's okay. 184 00:14:52,903 --> 00:14:56,365 yeah, but I just hate it when okay, now you got me. 185 00:14:56,365 --> 00:15:05,671 So I had once a job, I didn't stay for long, um where and I and I put it in a um how do you call it in English? 186 00:15:05,671 --> 00:15:07,332 In the quote in quotes, yeah. 187 00:15:07,332 --> 00:15:11,226 So a so called uh enterprise architect. 188 00:15:11,226 --> 00:15:16,728 I I don't know what what this guy was doing, but definitely not architecture in any sense. 189 00:15:17,029 --> 00:15:29,454 And and uh and that guy I was quite new in in that uh in that team and I it was as a financial t institution here in Zurich and I've been hired as a test manager. 190 00:15:29,454 --> 00:15:37,097 And I took it over from from from a junior colleague and um I should, you know, organize, plan all the test management. 191 00:15:37,097 --> 00:15:39,628 I've been doing this for quite some time before. 192 00:15:39,670 --> 00:15:54,894 I went there and then this uh this this uh whatever architect um came into our office and didn't even look at me and and only at my my colleague and and telling like basically 193 00:15:54,894 --> 00:16:07,594 talking over my head but talking to me at the same time and telling us how to yeah this listen girls this is how you you should plan the testing and this is how blah blah blah. 194 00:16:07,594 --> 00:16:20,558 And and this is how my developers um built it because I painted it in PowerPoint and and I stood up and and you know um walked in front of my colleagues so that that guy actually 195 00:16:20,558 --> 00:16:29,971 had to look at me, which he still didn't do, you know, and somebody just basically looks through you and I went there and I said and I, you know, uh offered my hand and said, Hi, 196 00:16:29,971 --> 00:16:30,927 we don't know each other. 197 00:16:30,927 --> 00:16:34,582 I'm Pia and I'm the test manager for this project. 198 00:16:34,712 --> 00:16:36,603 So thanks for all your insights. 199 00:16:36,603 --> 00:16:41,002 Um, I see you have a lot of experience here in this company. 200 00:16:41,002 --> 00:16:44,770 I appreciate and yeah, I'll think about it. 201 00:16:45,070 --> 00:16:53,397 And and he continued with his behavior like he started, and then I thought, okay, come on, seriously? 202 00:16:53,397 --> 00:16:56,900 And then I basically mimicked what he was doing, right? 203 00:16:56,900 --> 00:17:00,282 So I also said, Okay, yeah, whatever. 204 00:17:00,282 --> 00:17:00,663 Yeah. 205 00:17:00,663 --> 00:17:04,447 And then just didn't look at him anymore and 206 00:17:04,447 --> 00:17:17,174 You know, I just and then he went off and my colleague was like, Oh, you cannot talk to him like this and I'm like, Well, what what the hell does he think he who he is talking to 207 00:17:17,174 --> 00:17:17,875 us like that? 208 00:17:17,875 --> 00:17:30,222 And by the way, I mean, is he the test manager or yeah, but he's always like, you know, he won he he he always provides a good insights on the architecture and blah blah blah and I 209 00:17:30,222 --> 00:17:33,274 thought mm girl, you have a lot to learn. 210 00:17:33,274 --> 00:17:34,018 uh 211 00:17:34,018 --> 00:17:35,059 Yeah, that was weird. 212 00:17:35,059 --> 00:17:44,324 That was super weird and there was only one uh one example uh in in that company where I really felt, okay, I'm with stupid. 213 00:17:44,324 --> 00:17:47,165 It's just it it's I can't. 214 00:17:48,146 --> 00:17:56,799 I mean, honestly, I'm so amazed because I don't think I would have ever had the um wherewithal to to stand up and uh shift the conversation like that, especially earlier on 215 00:17:56,799 --> 00:17:58,140 in my in my career. 216 00:17:58,140 --> 00:18:06,743 Uh that's that's and to I I know how those the th those bank and enterprise architects in in Switzerland are. 217 00:18:06,743 --> 00:18:11,214 So uh that's that's even even another level on top of that. 218 00:18:11,214 --> 00:18:13,315 Yeah, but there are there are really great ones. 219 00:18:13,315 --> 00:18:25,871 I have to say they are out there and there was and that's and I know that and when I met this guy I was so shocked that I thought, no, no, this no no job title in any anything 220 00:18:25,871 --> 00:18:29,174 close to software development should be with this guy. 221 00:18:30,047 --> 00:18:30,448 Yeah. 222 00:18:30,448 --> 00:18:32,171 So that w that was earlier on. 223 00:18:32,171 --> 00:18:38,700 And did that have an impact on how you decide like which clients to actually pick up now uh for your company? 224 00:18:38,700 --> 00:18:39,400 Yes and no. 225 00:18:39,400 --> 00:18:44,717 Well I really I really I think the financial industry is an interesting one. 226 00:18:45,301 --> 00:18:46,754 No one ever. 227 00:18:48,235 --> 00:18:48,915 Sorry? 228 00:18:48,915 --> 00:18:49,616 I don't know. 229 00:18:49,616 --> 00:19:00,604 It it just happened that I I always ended up from project to project, either in a bank or but in different kinds of you know smaller ones like regional, then more the ones um 230 00:19:00,604 --> 00:19:05,287 focusing on on private banking and here and there in insurance. 231 00:19:05,287 --> 00:19:05,887 I don't know. 232 00:19:05,887 --> 00:19:15,634 So but right now I'm I'm super happy or I really enjoy working with smaller companies, with with startups that 233 00:19:15,690 --> 00:19:24,410 are in the scaling phase and then it's the time the point in time where they need to, you know, build up some structures, a bit more organization. 234 00:19:24,410 --> 00:19:31,877 So so this is where I'm very good at and and um I also feel like it helps my clients the most. 235 00:19:31,877 --> 00:19:33,930 So it's it's a win win for everybody. 236 00:19:33,930 --> 00:19:34,616 Um 237 00:19:34,616 --> 00:19:45,444 I these these are the companies that they uh they finally found pro product market fit for some part of the ver spectrum and they now have enough money to start fixing the things 238 00:19:45,444 --> 00:19:47,956 that in their organization that have gone so totally wrong. 239 00:19:47,956 --> 00:19:59,194 And so what I want to ask is uh like is there a most common pattern that you see in these scale ups that, especially in Switzerland, that keep falling into, or is everyone sort of 240 00:19:59,194 --> 00:20:02,604 like a special snowflake and have their own 241 00:20:02,604 --> 00:20:06,678 special flavor of of problems that you have to come in and uh like adapt to. 242 00:20:06,678 --> 00:20:10,491 Yeah, there are there are patterns and it's not only with the smaller companies. 243 00:20:10,491 --> 00:20:14,024 Basically the same also in the very big organizations. 244 00:20:14,024 --> 00:20:26,304 I feel uh like too much too much transformation or change at the same time is not good because the people you you have you have humans in your team, right? 245 00:20:26,304 --> 00:20:34,361 Whether it's a small team or it's a big organization, you should not forget to to take them with you. 246 00:20:34,361 --> 00:20:36,354 And it's what I see 247 00:20:36,354 --> 00:20:48,241 both in in in startups and in big organizations is that management, whoever that is, they they spend a lot of, you know, time and thinking about okay, where do we wanna go and how 248 00:20:48,241 --> 00:20:54,365 um do we wanna organize our teams and and our product road but blah blah blah. 249 00:20:54,365 --> 00:21:01,469 And then they wanna do it all at once, all at the same time, because now they have already spent so much time in thinking about it. 250 00:21:01,469 --> 00:21:02,700 Uh maybe not 251 00:21:02,700 --> 00:21:04,582 sometimes not even so much time. 252 00:21:04,582 --> 00:21:11,410 Uh and now they even uh now they even give it to the AI so they have the result in like five minutes. 253 00:21:11,410 --> 00:21:12,801 That's perfect. 254 00:21:12,942 --> 00:21:19,689 And so it should also be adapted like in I don't know five days and then the whole organization works perfectly. 255 00:21:19,689 --> 00:21:20,589 Which 256 00:21:20,694 --> 00:21:20,994 Yeah. 257 00:21:20,994 --> 00:21:24,849 I I was gonna say you're being you're being generous to say that they they thought through it. 258 00:21:24,849 --> 00:21:36,102 And I guess I guess one one um retort would be that they're thinking through it now more than ever with access to LLMs before there was no thinking, before trying to roll out 259 00:21:36,102 --> 00:21:41,117 changes, and now they have the benefit of whatever thinking the LLM provides. 260 00:21:41,622 --> 00:21:48,042 yeah, coming back to C level or or yeah, management in general thought it through. 261 00:21:48,042 --> 00:21:56,006 I feel you always had those folks where they really put a lot of thought into whatever they wanna change. 262 00:21:56,006 --> 00:22:01,708 And then you have the other extreme people that are just simply wanna, you know, we try it now, but who said that? 263 00:22:01,708 --> 00:22:04,358 Was it was it Zuckerberg? 264 00:22:04,358 --> 00:22:06,469 Just like move fast and break things. 265 00:22:06,469 --> 00:22:09,010 I feel like you have a lot of those extreme people. 266 00:22:09,010 --> 00:22:10,016 And for me 267 00:22:10,016 --> 00:22:11,507 I I'm missing the mix. 268 00:22:11,507 --> 00:22:13,018 I like to plan a lot. 269 00:22:13,018 --> 00:22:19,891 And then it it's hard for me to do to make the actual step into to try it out in production. 270 00:22:19,891 --> 00:22:20,171 Right. 271 00:22:20,171 --> 00:22:25,434 So I've been dreaming of having my own business basically for 30 years. 272 00:22:25,434 --> 00:22:30,137 And it took me incredibly long to finally do it. 273 00:22:30,137 --> 00:22:31,187 That's one extreme. 274 00:22:31,187 --> 00:22:32,888 And then there are 275 00:22:32,888 --> 00:22:40,902 colleagues of mine who just let the AI wing something and then just deploy it to production and yeah, we'll test in production, we'll see how it goes. 276 00:22:41,303 --> 00:22:54,710 And you know, I I get I get super nervous when her hearing that and I feel like we should be honest with ourselves, no matter on which extreme we are, and just to see that okay, it 277 00:22:54,710 --> 00:23:02,316 it's much better in most of the cases when we try to work together with the other extreme. 278 00:23:02,316 --> 00:23:14,287 And I think a lot of us know that person and then just get their opinion and then you would have a nice mix, uh, which I think is a very good which gives you a good point where 279 00:23:14,287 --> 00:23:17,290 you can say, Okay, now it's it's safe enough to try. 280 00:23:17,290 --> 00:23:17,901 Right? 281 00:23:17,901 --> 00:23:20,713 You don't and you cannot it's also what I had to learn. 282 00:23:20,713 --> 00:23:22,075 You cannot plan everything. 283 00:23:22,075 --> 00:23:23,866 Although I would love to. 284 00:23:24,408 --> 00:23:33,369 Do you have any secret tools to help convince the startups, small me or scale ups to actually make the transitions that you think would be beneficial for them? 285 00:23:33,369 --> 00:23:34,249 No. 286 00:23:36,533 --> 00:23:44,332 I use my divining rod and I throw the the sticks on the ground and they point in the appropriate direction and then all the founders listen to me. 287 00:23:44,332 --> 00:23:44,945 Yeah. 288 00:23:44,945 --> 00:23:47,162 But yeah, thank thanks for the idea. 289 00:23:47,162 --> 00:23:47,894 I love it. 290 00:23:47,894 --> 00:23:49,340 I should try that out. 291 00:23:49,340 --> 00:23:50,201 Yeah. 292 00:23:50,956 --> 00:23:54,506 I think the one the one that definitely works is it has to be their idea. 293 00:23:54,506 --> 00:23:55,502 Yep. 294 00:23:55,502 --> 00:23:56,343 absolutely. 295 00:23:56,343 --> 00:24:05,666 What helps me is I I also have uh have an education in systemical coaching, but that's only one part, right? 296 00:24:05,666 --> 00:24:17,321 I was alwa always interested in, you know, how how are people like how do you work together with different characters, people from different regions, from different 297 00:24:17,321 --> 00:24:21,113 cultures, not having all the same native language. 298 00:24:21,113 --> 00:24:23,982 And that helps me a lot in my work. 299 00:24:23,982 --> 00:24:26,086 uh but also in my private life of course. 300 00:24:26,086 --> 00:24:30,472 And this is what I try to also tell my clients. 301 00:24:30,472 --> 00:24:37,003 The goal is that they that it it it makes click in their heart and then they see things they haven't seen before. 302 00:24:37,003 --> 00:24:39,712 And then what you just said, it's their idea. 303 00:24:39,712 --> 00:24:49,537 One of the things that I've seen come up a lot is that it's challenging to find real world research actually done with even uh a modicum or a small amount of scientific rigor when 304 00:24:49,537 --> 00:24:52,309 it comes to anything related to AI productivity. 305 00:24:52,309 --> 00:24:56,131 And uh I think many people are standing on one of the extremes, right? 306 00:24:56,131 --> 00:24:59,273 Like they without any any even the single piece of data. 307 00:24:59,273 --> 00:25:00,954 One of the extremes like, everything is better. 308 00:25:00,954 --> 00:25:03,175 And on the other side, it's the worst thing ever. 309 00:25:03,175 --> 00:25:04,296 We'll never use that. 310 00:25:04,296 --> 00:25:08,928 But I feel like you must have been able to come by at least some data points from these organizations that 311 00:25:08,928 --> 00:25:17,794 may I I can only imagine our trying to transition to a a different mode of operation with pulling in LMs into some part of the workflow. 312 00:25:17,794 --> 00:25:19,234 Yeah, absolutely. 313 00:25:19,234 --> 00:25:26,946 Yeah, we currently at one one of my clients which is uh yeah, it's international startup. 314 00:25:26,946 --> 00:25:28,637 It it's not a startup anymore. 315 00:25:28,637 --> 00:25:30,057 It's it's a bit bigger now. 316 00:25:30,057 --> 00:25:37,349 So they are having currently round something between fifty and sixty employees two, three months ago. 317 00:25:37,349 --> 00:25:42,001 Uh they decided to it's how d how did they call it? 318 00:25:42,001 --> 00:25:45,621 Like they said, okay, full steam AI development. 319 00:25:45,942 --> 00:25:47,552 So all the uh 320 00:25:47,552 --> 00:25:56,309 not all the engineers, but like um a bigger part of the of the engineering team was put on the side to to run an experiment. 321 00:25:56,309 --> 00:25:57,570 That's how they called it. 322 00:25:57,570 --> 00:26:00,231 Um basically it this is how we work now. 323 00:26:00,231 --> 00:26:01,743 but I will start at the beginning. 324 00:26:01,743 --> 00:26:05,075 So it started out as an experiment. 325 00:26:05,295 --> 00:26:13,061 first thing was they already it started already with forgetting to involve the QA into this experiment team. 326 00:26:13,061 --> 00:26:14,862 Uh 327 00:26:15,822 --> 00:26:17,296 Off to a great start. 328 00:26:17,296 --> 00:26:17,922 Yeah. 329 00:26:17,922 --> 00:26:18,383 Yeah, yeah. 330 00:26:18,383 --> 00:26:25,002 Uh also uh the product owner was also m not super included in there. 331 00:26:25,002 --> 00:26:27,296 Um surprise 332 00:26:28,647 --> 00:26:29,377 I love this already. 333 00:26:29,377 --> 00:26:30,449 You know, you know what? 334 00:26:30,449 --> 00:26:31,380 We're gonna do this right. 335 00:26:31,380 --> 00:26:32,541 We're not gonna do this wrong. 336 00:26:32,541 --> 00:26:36,225 We see all these companies who are just introducing AI and forcing everyone to do it. 337 00:26:36,225 --> 00:26:36,956 We're gonna do it differently. 338 00:26:36,956 --> 00:26:43,754 We're gonna run an experiment um and we're gonna make it make sure we record metrics and that it'll be super successful, and then we can decide whether to roll this out to the 339 00:26:43,754 --> 00:26:44,785 whole organization. 340 00:26:44,785 --> 00:26:48,679 Our experiment, we don't need testing or product managers involved. 341 00:26:48,679 --> 00:26:49,036 We're 342 00:26:49,036 --> 00:26:49,586 Yeah. 343 00:26:49,586 --> 00:26:52,488 No, we only start with the coding part, right? 344 00:26:52,488 --> 00:26:54,468 So you can forget about the rest. 345 00:26:54,468 --> 00:26:56,990 No, I just I'm kidding. 346 00:26:56,990 --> 00:26:59,981 It was like there we had like those two extremes, right? 347 00:26:59,981 --> 00:27:04,323 So the one part of the company which wanted to do exactly what you just said, right? 348 00:27:04,323 --> 00:27:11,256 So really a scientifically kind of like experiment, plan it, have everybody involved who should be. 349 00:27:11,256 --> 00:27:16,378 And then there was other parts of the company saying, No, we need to move fast because otherwise 350 00:27:16,518 --> 00:27:22,785 our competitors they will be faster and then we're screwed and you know everything will go down in flames. 351 00:27:22,785 --> 00:27:23,155 Yeah. 352 00:27:23,155 --> 00:27:32,556 And then very quickly the the more organizational folks, more structured folks, they were they went quiet because it 353 00:27:32,576 --> 00:27:36,889 Started and I was super shocked that this happened so fast. 354 00:27:36,889 --> 00:27:47,265 And we had those two two sides basically, like the ones that are, yeah, we need to do it with AI, and AI is so super and we'll be so much faster and so much better, blah blah 355 00:27:47,265 --> 00:27:48,115 blah. 356 00:27:48,135 --> 00:27:51,197 And then the others that are, yeah, but what about, but what about? 357 00:27:51,197 --> 00:27:57,521 And then the AI folks, they were like, You are against AI, so you're kind of against us. 358 00:27:57,521 --> 00:27:59,442 This is how we felt. 359 00:27:59,894 --> 00:28:04,757 And I was super shocked because I really like every single person in that team. 360 00:28:04,757 --> 00:28:07,238 But I was like, What? 361 00:28:07,238 --> 00:28:08,899 What is going on here? 362 00:28:08,899 --> 00:28:10,000 Are we crazy? 363 00:28:10,000 --> 00:28:12,431 Don't we see what's just happening with our team? 364 00:28:12,431 --> 00:28:17,264 Because it's like just, you know, pulling us more and more away. 365 00:28:17,264 --> 00:28:28,098 And we've worked so hard to to get closer to each other because we are already separated you know, around the world and and in different cultures and all that stuff and now 366 00:28:28,098 --> 00:28:29,939 just because of this AI hype. 367 00:28:29,939 --> 00:28:31,020 It's really sad. 368 00:28:31,020 --> 00:28:34,601 I would love to tell more positive stuff. 369 00:28:35,922 --> 00:28:50,761 But I feel like when we can say so the positive thing is I feel now being in the in the in the third month of this not so experimental experiment right now, people started to 370 00:28:50,761 --> 00:28:52,392 realize what happened. 371 00:28:52,392 --> 00:28:52,742 Right. 372 00:28:52,742 --> 00:28:57,074 Because yes of course we we delivered a lot of code, but 373 00:28:57,174 --> 00:28:59,476 Not all of it is what we've expected. 374 00:28:59,476 --> 00:29:08,474 So whether it's the structure of the code is not what a senior developer would, you know, how you would build stuff, right? 375 00:29:08,474 --> 00:29:12,557 A lot of duplication or like simply spaghetti code, right? 376 00:29:12,557 --> 00:29:18,642 I mean it works on the surface, but yeah, if you look behind it then so that's one thing. 377 00:29:18,642 --> 00:29:24,617 Then the other thing is like it's super important that you know what you want, right? 378 00:29:24,617 --> 00:29:25,658 So this 379 00:29:25,670 --> 00:29:35,210 not including the product owner from the very beginning and not like really trying to to solve all the open questions there were. 380 00:29:35,210 --> 00:29:40,964 Just simply assuming that yeah yeah the AI will figure it out and it will work as surprise, surprise. 381 00:29:40,964 --> 00:29:42,235 It did not. 382 00:29:42,295 --> 00:29:54,338 And what we wanted to deliver in four weeks, we didn't deliver in eight weeks because there were so much um gaps to fill and and open questions to discuss and 383 00:29:54,338 --> 00:29:55,909 The AI couldn't help with that. 384 00:29:55,909 --> 00:30:01,314 So the product owner had a lot of meetings, had to explain stuff over and over again. 385 00:30:01,314 --> 00:30:01,884 Yeah. 386 00:30:01,884 --> 00:30:03,471 And then also the QA, right? 387 00:30:03,471 --> 00:30:11,432 I mean, she's also forced to to put more effort in into automation, also uh using AI to help her automate tests. 388 00:30:11,432 --> 00:30:24,118 But also she she found out so yeah, it's nice, it delivered good looking API tests, but it just simply like the AI produced tests that simply trusted the wrong API responses. 389 00:30:24,118 --> 00:30:26,079 So they were worth nothing. 390 00:30:26,079 --> 00:30:38,646 So it was important that she reviews the output of the air sort of so it's it's a process for the people to sometimes I feel people need to to feel the pain themselves. 391 00:30:38,646 --> 00:30:44,669 And then it's like when you tell your children not to put their hands on the you know, on the plate. 392 00:30:44,669 --> 00:30:45,920 Yeah, on the stove. 393 00:30:45,920 --> 00:30:46,490 Exactly. 394 00:30:46,490 --> 00:30:46,830 Yeah. 395 00:30:46,830 --> 00:30:48,521 Yeah, you shouldn't do that, you shouldn't do that. 396 00:30:48,521 --> 00:30:51,273 It's hot, you're gonna burn your hand and they do it. 397 00:30:51,273 --> 00:30:53,898 And then hopefully they learn in the end. 398 00:30:53,898 --> 00:30:57,604 And you're you are there, ready to write with the ice. 399 00:30:58,306 --> 00:31:06,798 Do you think do you think that going back the company would be able to construct an experiment more like I I hate to say correctly? 400 00:31:06,798 --> 00:31:08,509 Yeah, let me try that again. 401 00:31:09,009 --> 00:31:18,591 Do you think that if the if the company would go back and repeat um creating an experiment to see whether or not LLMs would be an effective use, do you think that that would be an a 402 00:31:18,591 --> 00:31:19,732 successful experiment this time? 403 00:31:19,732 --> 00:31:28,224 Not necessarily that it would turn out that it would be better, but they would be able to derive some learning from it rather than it being a complete mess. 404 00:31:28,556 --> 00:31:30,927 I do hope so, but I'm not sure. 405 00:31:30,927 --> 00:31:34,759 But it's not it's just because I because I know the mix of the people. 406 00:31:34,759 --> 00:31:36,820 Yeah and how they who they right. 407 00:31:36,820 --> 00:31:50,557 I think like when you I think it would be better when they do it the same because now also some super enthusiastic uh folks learn that okay, not everything is gold just because it 408 00:31:50,557 --> 00:31:51,717 looks like 409 00:31:52,128 --> 00:31:52,978 Yeah. 410 00:31:53,119 --> 00:31:57,601 So do you think that uh a large part of it is the tools that we have available? 411 00:31:57,601 --> 00:32:02,614 Like it's not whether or not we can introduce L LMs and see if there's an improvement. 412 00:32:02,614 --> 00:32:08,627 It's that the tools themselves make it uh a struggle to actually even have an experiment. 413 00:32:08,627 --> 00:32:10,788 Or do you think it's an organizational problem? 414 00:32:10,788 --> 00:32:20,263 The people performing the ex experiment don't have uh good attention to what their internal processes already are, understand what they're actually changing by switching to 415 00:32:20,263 --> 00:32:20,774 L LMs. 416 00:32:20,774 --> 00:32:21,494 Is it a 417 00:32:21,494 --> 00:32:22,860 A human focused problem. 418 00:32:22,860 --> 00:32:29,653 I feel it's it's more I think it's it's a mix, but for me it's more on the human side. 419 00:32:29,953 --> 00:32:41,468 Because when looking back in my career, um when I used to work in in the testing area, um there was the same thing happening with automation and and all the testers were like so, 420 00:32:41,468 --> 00:32:46,250 my god, now I need to learn how to code because otherwise I won't have a job anymore, blah blah blah. 421 00:32:46,250 --> 00:32:51,882 And everybody went crazy like chickens without heads running around and also they are 422 00:32:51,882 --> 00:32:58,085 it wasn't the tool that caused the problem or for me it was never the the tool. 423 00:32:58,085 --> 00:33:03,268 So now it's also not whether AI tool or or any other tool. 424 00:33:03,328 --> 00:33:12,362 It's we as humans we we cannot outsource something to a tool, especially not when it says it's it's intelligent. 425 00:33:12,362 --> 00:33:14,945 Uh that that's my my feeling, right? 426 00:33:14,945 --> 00:33:18,877 So I think we need to do our homework ourselves. 427 00:33:18,877 --> 00:33:19,517 Yes. 428 00:33:19,517 --> 00:33:21,740 Whether we like it or not. 429 00:33:21,896 --> 00:33:23,180 And and 430 00:33:23,874 --> 00:33:33,877 That's good though, because I I mean it sounds optimistic because if you say that it's not the tool set or chain or companies that are providing products for us that make it 431 00:33:33,877 --> 00:33:44,660 difficult for us to experiment, it may be just our lack of expectations or knowledge in a particular area that are are holding us back to effective uh experimentation with 432 00:33:44,660 --> 00:33:45,820 scientific rigor. 433 00:33:45,820 --> 00:33:47,560 That means that we can learn and improve. 434 00:33:47,560 --> 00:33:53,672 We're in full control of that as an organization and you can rely on third parties to come in and potentially help. 435 00:33:53,828 --> 00:33:56,760 an organization actually run effective experiments. 436 00:33:56,760 --> 00:34:00,602 I think that that's for me a little bit of of a positive side here. 437 00:34:00,723 --> 00:34:11,639 What I do want to ask is that not everyone's in a leadership position that can help influence directly how the experiments are set up or how the tools are integrated in the 438 00:34:11,639 --> 00:34:12,650 organization. 439 00:34:12,650 --> 00:34:19,394 So given that you have a unique position where you're often integrating with the leaders of these technical organizations, what can 440 00:34:19,600 --> 00:34:29,186 engineers, uh more technical people, ICs that are on the ground do to convince, say, their leadership that their current decisions or their processes that they're trying to put in 441 00:34:29,186 --> 00:34:31,930 place actually have, say, a negative impact on the business. 442 00:34:32,174 --> 00:34:43,004 Personally, and I know it might not be everyone's thing to do, but I would uh always think why did me did they hire me in the first place? 443 00:34:43,004 --> 00:34:52,162 So really focus on that and not let yourself get crazy just because of this ooh, there is this AI thing now and this will take away my job. 444 00:34:52,162 --> 00:34:56,795 'Cause I see that a lot now, uh across all the roles. 445 00:34:57,136 --> 00:34:59,372 and also sometimes I feel it myself. 446 00:34:59,372 --> 00:35:03,903 Yeah, I'm wondering, okay, is this what I'm doing actually can an AI replace me? 447 00:35:03,903 --> 00:35:05,574 Should I focus on something else? 448 00:35:05,574 --> 00:35:12,616 But then I go back to and and I would recommend it to every everyone, independent of where you are in the hierarchy. 449 00:35:12,616 --> 00:35:24,005 Really just if it's too much, take a step back, close the laptop, and remind yourself of everything you bring with you, like all the experience you have, um or if it's only your 450 00:35:24,005 --> 00:35:25,709 gut feeling, it doesn't matter, right? 451 00:35:25,709 --> 00:35:28,280 So everything you bring is a human and 452 00:35:28,280 --> 00:35:31,451 They hired you and they hired you for a reason. 453 00:35:31,451 --> 00:35:33,953 And then raise your voice. 454 00:35:33,953 --> 00:35:39,415 Whether this this can be it doesn't have to be like loud in front of a big round. 455 00:35:39,415 --> 00:35:49,679 It can be, I don't know, maybe your organization has like some anonymous, I don't know, mailbox where you can put feedback in anything. 456 00:35:49,679 --> 00:35:55,874 But I would really like to encourage people just say what how you feel about it. 457 00:35:55,874 --> 00:36:04,166 But at the same time stay open for for all the, you know, all the technology innovation that that's coming our way. 458 00:36:04,166 --> 00:36:06,837 Because I don't think it we are at the end right now. 459 00:36:06,837 --> 00:36:09,578 I don't think AI will go away. 460 00:36:09,578 --> 00:36:16,960 So I feel we need to adapt and we need to find our way, every single one of us, um, to deal with it. 461 00:36:16,960 --> 00:36:24,982 Just remember why we are here in this job and and why they hired us and what makes us special. 462 00:36:25,142 --> 00:36:31,616 And then they should they should listen, hopefully they listen to to what we what we have to say. 463 00:36:31,616 --> 00:36:36,645 I would recommend it to management that they listen to their people. 464 00:36:38,816 --> 00:36:41,438 I I feel like you you reminded me of two things. 465 00:36:41,438 --> 00:36:50,286 One, it's the uh just the real challenge of being in any position feeling like you're with you're an imposter in that position. 466 00:36:50,286 --> 00:36:52,507 imposter syndrome is the is the aspect. 467 00:36:52,668 --> 00:37:02,286 And that you're not capable of or or you shouldn't you're afraid that you'll lose your job if if you do say something, that you don't even have the expertise to be able to stand up 468 00:37:02,286 --> 00:37:05,206 and maybe offer critical feedback. 469 00:37:05,206 --> 00:37:15,652 But you know, you remind the other thing you reminded me about, uh, which is linked to that, is even before LLMs uh completely ruined uh a lot of organizations, there was this 470 00:37:15,652 --> 00:37:25,017 methodology that I really had in my mind that the most effective or long-term members of organizations are the ones who stand up and say something and offer feedback. 471 00:37:25,017 --> 00:37:29,759 because chances are they were hired, as you said, for a particular reason that was identified. 472 00:37:29,759 --> 00:37:34,682 Like if you made it through the hiring round where you were in a stack of thousands of 473 00:37:34,818 --> 00:37:43,355 resumes in a pile and then after that got through the interview round and actually got hired and have been there for even a couple of months, then as you said, there there's 474 00:37:43,355 --> 00:37:44,806 something was recognized. 475 00:37:44,806 --> 00:37:52,122 But if you keep your mouth shut in you are completely no different than everyone else in the organization. 476 00:37:52,122 --> 00:37:53,833 There's nothing that that stands you out. 477 00:37:53,833 --> 00:37:57,086 So if something were to happen, you are not unique. 478 00:37:57,086 --> 00:37:59,208 You offer no extra value. 479 00:37:59,208 --> 00:38:04,622 Whereas if you are someone who stands up and complains, uh complains l loud enough, but not too loud. 480 00:38:04,788 --> 00:38:09,010 then you are at least recognizable as someone that may be offering value in some way. 481 00:38:09,010 --> 00:38:19,386 And I I do I do understand that may be also what gets you fired at the end of the day, uh, because there are definitely those engineers, I've I've been that one in the past that 482 00:38:19,386 --> 00:38:28,431 that open their mouth too wide, uh it there is this unique aspect where you are providing a lot of value in doing this that not anyone else is potentially doing. 483 00:38:28,431 --> 00:38:34,124 And if LMs do replace all software engineering and and testing and product 484 00:38:34,124 --> 00:38:42,959 development lifecycle, et cetera, and support, feedback, et cetera, then the only thing left that you can offer value is by your own opinions. 485 00:38:43,219 --> 00:38:47,510 so it it's even better to refine the mechanism in which you communicate. 486 00:38:47,510 --> 00:38:48,464 Yeah, absolutely. 487 00:38:48,464 --> 00:38:50,459 Nothing to add here. 488 00:38:51,887 --> 00:38:57,271 So one one thing I I do want to get your perspective on, especially coming historically from the I hate to say QA. 489 00:38:57,271 --> 00:39:04,637 I feel like it's it's just such a demeaning uh label that's added just from historically in and organizational structures. 490 00:39:04,637 --> 00:39:14,386 People who end up taking up that those titles are heavily under evaluated for the experience and abilities that they really have. 491 00:39:14,386 --> 00:39:18,389 So that being said, I I I do like the the label more of a tester. 492 00:39:18,389 --> 00:39:20,118 And when I think about testing 493 00:39:20,118 --> 00:39:22,009 Um, which is obviously different than being a tester. 494 00:39:22,009 --> 00:39:28,332 Uh a lot of people are are now standing up and saying, yeah, software development, that was never our bottleneck. 495 00:39:28,332 --> 00:39:32,265 Well, I guess if I take a a step back, LLMs are helping us write so much code. 496 00:39:32,265 --> 00:39:33,955 Software development was always our bottleneck. 497 00:39:33,955 --> 00:39:35,076 Now that's eliminated. 498 00:39:35,076 --> 00:39:42,370 And then we get lots of articles online saying software development is is uh was our bottleneck and that's completely over, and now we can move on to other things. 499 00:39:42,370 --> 00:39:46,854 And then we get articles retorting those articles saying, no, software development was never our bottleneck. 500 00:39:46,854 --> 00:39:49,376 Now we have to focus on the business and doing other things. 501 00:39:49,376 --> 00:39:51,617 The bottleneck is really pull requests. 502 00:39:51,778 --> 00:39:54,450 And I'm just like, LOL. 503 00:39:54,450 --> 00:39:59,264 Like pull requests are are not the bottom are sure, they're a bottleneck, but they're not the real bottleneck. 504 00:39:59,264 --> 00:40:04,349 And I feel like we'll very quickly have companies standing up and saying, yeah, we automate pull request reviews. 505 00:40:04,349 --> 00:40:08,182 And then we'll get articles saying, pull request reviews were always our bottleneck. 506 00:40:08,182 --> 00:40:10,134 And they were that, you know, now they're resolved. 507 00:40:10,134 --> 00:40:10,604 And 508 00:40:10,604 --> 00:40:14,586 Then there's gonna be the r the response article saying, pull requests for never a bottleneck. 509 00:40:14,586 --> 00:40:16,030 It was fill in the blank. 510 00:40:16,030 --> 00:40:18,070 What's what's the trajectory here? 511 00:40:18,070 --> 00:40:27,237 I've seen now now uh I'm I'm with one client helping them out in in the product uh in the product team. 512 00:40:27,237 --> 00:40:35,233 So I'm actually now the bottleneck with uh defining requirements that that are that first that makes sense, right? 513 00:40:35,233 --> 00:40:43,926 So so scope out a feature, like traditional business analysis requirements, work requirements engineering work. 514 00:40:43,926 --> 00:40:48,377 And I tried to do it with AI and I was not happy at all. 515 00:40:48,377 --> 00:40:49,128 So yeah. 516 00:40:49,128 --> 00:40:54,811 So currently um me and my other colleague in Adroll, we are kind of a bottleneck. 517 00:40:54,811 --> 00:40:56,532 But that's okay for us. 518 00:40:56,532 --> 00:41:06,036 Because we've you know, we we showed the the AI fans why we are not giving everything to the AI. 519 00:41:06,036 --> 00:41:07,307 So what comes out, right? 520 00:41:07,307 --> 00:41:10,720 'Cause when we start already at the beginning to give 521 00:41:10,720 --> 00:41:13,752 undefined work in there, it only gets worse and worse. 522 00:41:13,752 --> 00:41:25,518 And at the end, like our poor tester, she will have no idea what to automate, uh, or what let her AI agent automate because it's just, you know, it's basically in German we have 523 00:41:25,518 --> 00:41:31,222 this we have this uh this game, uh when children play it's called Stille Post. 524 00:41:31,222 --> 00:41:39,008 So it's a silent male when you know one they all the children stand in a line and one the first one starts to say something very 525 00:41:39,008 --> 00:41:46,740 you know, silent into the ear of the other one and then, you know, they just take the whole message to the end and at the end it comes out something completely different. 526 00:41:46,740 --> 00:41:56,923 And this is what I feel like happens when we scream like this, now, now you are the bottleneck, you need to be faster, just throw it into the AI and then like, yeah, okay, 527 00:41:56,923 --> 00:41:57,984 now the AI does it. 528 00:41:57,984 --> 00:41:59,684 For me, I'm not the bottleneck anymore. 529 00:41:59,684 --> 00:42:00,184 Super. 530 00:42:00,184 --> 00:42:06,626 But then someone else is and then in the end we end up with something not useful, not wanted. 531 00:42:06,690 --> 00:42:11,873 Th you know what I think it's a much better name than the English version of the game, which is just called telephone. 532 00:42:12,993 --> 00:42:14,174 I know, isn't it lame? 533 00:42:14,174 --> 00:42:17,636 Yeah. 534 00:42:17,636 --> 00:42:28,984 Uh yeah, so it's it's a telephone game, uh having having lots of middle people in in between where you're passing off messages and at the end of the day you get something uh 535 00:42:28,984 --> 00:42:30,484 uh completely different. 536 00:42:30,484 --> 00:42:32,287 I mean, usually more than a couple of words. 537 00:42:32,287 --> 00:42:39,243 So it you get some enjoyment out of what what ends up with uh what you started with versus uh at the end. 538 00:42:39,243 --> 00:42:49,042 It's interesting to bring LMs into that mix though and already start to see that it's compounding the confusion uh or complexity of of the messages that get passed around the 539 00:42:49,042 --> 00:42:55,328 organization and to see it in the light of still the problem of throwing the work over the wall to someone else. 540 00:42:55,328 --> 00:42:56,066 It's 541 00:42:56,066 --> 00:42:56,466 Yeah. 542 00:42:56,466 --> 00:43:05,964 I I mean, if you're evaluating people's success or their careers or even assign them the label or the title to do a particular thing and they can offload all of that work to an 543 00:43:05,964 --> 00:43:18,204 LLM or 90% of it, then they're just encouraged to have it go through this sort of extra mutation or transformation layer that doesn't understand the original intent, that it has 544 00:43:18,204 --> 00:43:21,066 no like there's no reasoning or thinking process behind it. 545 00:43:21,066 --> 00:43:22,618 And then taking that and passing it off. 546 00:43:22,618 --> 00:43:25,738 I if you look at it from that perspective, it seems obvious. 547 00:43:25,738 --> 00:43:27,991 that it can't end well. 548 00:43:28,000 --> 00:43:28,731 Absolutely. 549 00:43:28,731 --> 00:43:29,231 Yeah. 550 00:43:29,231 --> 00:43:33,316 So I I really do hope that that we'll learn that. 551 00:43:33,316 --> 00:43:37,210 Like all of us as a society will learn that sooner than later. 552 00:43:37,210 --> 00:43:43,165 But there are days where I'm more worried and there are other days where I'm more positive. 553 00:43:44,766 --> 00:43:48,035 Um, well then that's a good point, I think, for us to switch over to picks. 554 00:43:48,035 --> 00:43:51,146 So, Pia, what have you brought for us today? 555 00:43:51,146 --> 00:43:53,668 I brought one of my favorite books. 556 00:43:53,668 --> 00:43:57,972 Um, it's The Culture Map by Erin Meyer. 557 00:43:57,972 --> 00:44:09,701 And uh it's all about how you deal with it's focused on the business area, but how you work internationally, you know, with people from different cultures, countries, 558 00:44:09,701 --> 00:44:12,784 backgrounds, and it's super super interesting. 559 00:44:12,784 --> 00:44:21,152 Shed a lot of light um assumptions I've had about different areas or countries around the world. 560 00:44:21,152 --> 00:44:22,412 It was really eye opening. 561 00:44:22,412 --> 00:44:35,596 Yeah, I love it how she uh how she describes the the differences between cultures and and she, you know, every everything is described by at least one concrete example from her own 562 00:44:35,596 --> 00:44:36,546 experience. 563 00:44:36,546 --> 00:44:37,627 So I really love that. 564 00:44:37,627 --> 00:44:40,627 So it's not like it's not super scientific written. 565 00:44:40,627 --> 00:44:43,318 It's just something you can easy read. 566 00:44:43,318 --> 00:44:44,449 Yeah, it's really cool. 567 00:44:44,449 --> 00:44:48,850 And it helped me a lot to work with my international clients now. 568 00:44:48,850 --> 00:44:49,730 Yeah. 569 00:44:50,392 --> 00:44:55,729 Was there any like one particular insight that you liked above all the other ones? 570 00:44:56,032 --> 00:44:58,703 then it's all about perspective. 571 00:44:58,703 --> 00:45:11,487 So for example, people outside of Germany, Austria, Switzerland, they always feel like, okay, those those German speaking countries, all the people there, they are always super 572 00:45:11,487 --> 00:45:12,887 on time, for example. 573 00:45:12,887 --> 00:45:20,330 And and now like as I am I'm Austrian, uh, but I live in Switzerland for more than thirteen years now. 574 00:45:20,330 --> 00:45:20,990 And 575 00:45:20,990 --> 00:45:25,992 I know the Swiss version of being on time and I know the Austrian version. 576 00:45:25,992 --> 00:45:29,893 And that's are completely different thing, like totally different. 577 00:45:29,893 --> 00:45:40,237 And it drives me crazy uh working with Austrians because I so adapted the the Swiss timing and and there like it it's huge. 578 00:45:40,657 --> 00:45:43,158 so it's always about perspective. 579 00:45:43,523 --> 00:45:54,453 Yeah, the the being on time thing is uh and obviously if you extend that to other cultures around the world, it's I think in the book Aaron uses the term whether or not time is 580 00:45:54,453 --> 00:45:56,034 fixed or flexible. 581 00:45:56,034 --> 00:45:56,615 Yes. 582 00:45:56,615 --> 00:46:02,680 And uh you could definitely see some cultures are way more flexible on when they like if you say I always found this really interesting. 583 00:46:02,680 --> 00:46:04,994 In in German there isn't a great way to say 584 00:46:04,994 --> 00:46:12,616 Like we'll meet at a particular time, but with the assumption that it's a flexible time, it's if you like if you say you're gonna meet at twelve o'clock, like you are meeting, you 585 00:46:12,616 --> 00:46:13,536 are meeting at twelve o'clock. 586 00:46:13,536 --> 00:46:15,557 Like there is no there is no other time. 587 00:46:15,557 --> 00:46:23,409 But in other in other cultures, that's definitely like, well, twelve could be one thir one thirty or something, like you know, stuff can happen at that point. 588 00:46:23,409 --> 00:46:24,779 Yeah, I I like that one. 589 00:46:24,779 --> 00:46:34,412 The one that actually got me in the book that I I really liked was that uh a better understanding of this concept of co like high context versus low context. 590 00:46:34,412 --> 00:46:45,850 Where in especially uh like Eastern Asian cultures, when you say something, there's like a lot of different implied meanings with whatever that that statement is that you're saying. 591 00:46:45,850 --> 00:46:53,346 And so if I say, uh, like your hair looks nice today, that that may mean so many different things on so many levels. 592 00:46:53,346 --> 00:46:59,971 Like, does that mean that like yesterday and the day before your hair was terrible and and today you finally decided to fix it? 593 00:46:59,971 --> 00:47:01,912 And there's like a lot of different levels to that. 594 00:47:01,912 --> 00:47:07,016 Whereas in I feel like a a lot in Western cultures, things are very uh like to the point. 595 00:47:07,016 --> 00:47:08,087 They're low context. 596 00:47:08,087 --> 00:47:11,490 If you say something, don't try to interpret it more than what's there. 597 00:47:11,490 --> 00:47:14,353 There really was no extra thought put behind it. 598 00:47:14,353 --> 00:47:22,539 And I feel like that was a huge learning for me, especially around how uh different languages or cultures are constructed and whether or not you should read into something 599 00:47:22,539 --> 00:47:23,560 that someone is saying. 600 00:47:23,560 --> 00:47:27,443 Talking to someone from Asia, feel free to read into it. 601 00:47:27,443 --> 00:47:30,906 And so, like now, I have to be extra careful when I say things. 602 00:47:31,011 --> 00:47:33,161 how it may be taken by different people. 603 00:47:33,161 --> 00:47:33,666 Yeah. 604 00:47:33,666 --> 00:47:34,707 Yeah, absolutely. 605 00:47:34,707 --> 00:47:36,928 And that reminds me of yeah, one more thing. 606 00:47:36,928 --> 00:47:37,978 I was surprised. 607 00:47:37,978 --> 00:47:39,089 I didn't expect that. 608 00:47:39,089 --> 00:47:50,225 Like when you, for example, as uh European or l myself, when I give feedback in in a round, that's that's normal for me, right? 609 00:47:50,225 --> 00:47:58,379 And also with uh the clients like from Austria, that's totally fine no matter which level in the hierarchy they are. 610 00:47:58,379 --> 00:48:02,702 But it's completely weird when we have colleagues from the US in the call. 611 00:48:02,702 --> 00:48:03,576 So they 612 00:48:03,576 --> 00:48:09,909 They fa they would never do that because it's like together we stand divided we fall. 613 00:48:09,909 --> 00:48:22,574 This um you know, this way of thinking um in in the US um culture I wasn't aware of because I um I experienced Americans from the US always is very like straightforward, like 614 00:48:22,574 --> 00:48:25,610 to the point, saying what they wanna say. 615 00:48:25,610 --> 00:48:32,810 But yeah, now I I understand more why in certain situations they don't speak up. 616 00:48:32,810 --> 00:48:41,088 Although I know they also don't agree with something, but they would not like say something against the boss in front of all the others. 617 00:48:41,088 --> 00:48:52,581 I I think the the most common known scenario of professional workplace engagement for Americans is the feedback sandwich where you say something very nice and then you give the 618 00:48:52,581 --> 00:48:55,962 actual feedback and then you say, no, it's actually okay, it's not that bad. 619 00:48:55,962 --> 00:49:00,853 And you're supposed to you're supposed to understand that it was a really negative feedback. 620 00:49:00,853 --> 00:49:02,524 Things aren't going very well. 621 00:49:02,524 --> 00:49:05,655 But uh and and pull and pull that important piece out. 622 00:49:05,655 --> 00:49:07,465 Uh I've always hated that. 623 00:49:07,465 --> 00:49:09,806 But on the other side, you know, I I I get it. 624 00:49:09,806 --> 00:49:10,666 So 625 00:49:11,102 --> 00:49:20,720 there's also there's also this huge aspect of if you engage with people from other cultures who work in international companies, they tend to have been more exposed to other 626 00:49:20,720 --> 00:49:30,428 cultures and so may have picked up on some of those things more than those that if you're working like you're consulting or contracting for a a foreign comp company where that 627 00:49:30,428 --> 00:49:37,434 company only has employees from that local country, have only ever worked locally, then they definitely embody a lot of those. 628 00:49:37,434 --> 00:49:40,576 And I don't want to call them stereotypes, but they're 629 00:49:40,576 --> 00:49:42,838 in a particular part of each of those spectrums in the book. 630 00:49:42,838 --> 00:49:44,989 So I love the pick, Pia. 631 00:49:44,989 --> 00:49:46,391 I the culture map is great. 632 00:49:46,391 --> 00:49:48,489 I still bring it up as a recommendation for people. 633 00:49:48,489 --> 00:49:58,540 It it's you know, even if you don't work across cultures, just even in a single company, when you're working with colleagues, they could be have their own values that differ from 634 00:49:58,540 --> 00:50:00,642 yours and how you understand things. 635 00:50:00,642 --> 00:50:06,200 And it may not be because they're, you know, maybe they're have heritage from a different place or 636 00:50:06,200 --> 00:50:08,066 who they've engaged with or just personally. 637 00:50:08,066 --> 00:50:11,328 And I I found there's a lot of insight in that book that I think is very good. 638 00:50:11,328 --> 00:50:12,785 Awesome, happy you liked it. 639 00:50:12,785 --> 00:50:14,130 So what did you bring? 640 00:50:14,130 --> 00:50:15,714 Did you bring something? 641 00:50:15,864 --> 00:50:19,006 Yeah, no, I I I have I have to have a pick every single week. 642 00:50:19,006 --> 00:50:20,798 And so that's a lot of that's a lot of picks. 643 00:50:20,798 --> 00:50:23,069 My pick is well, first is a question. 644 00:50:23,069 --> 00:50:25,311 Uh this one's hype a uh rhetorical. 645 00:50:25,311 --> 00:50:28,963 Uh am I a little less human than the rest of us? 646 00:50:29,123 --> 00:50:37,929 And well, I've definitely been accused of being so uh before, uh, but there's a really great episode of it's called The Rest is Science. 647 00:50:38,030 --> 00:50:44,864 it's a YouTube series where they talk about if logic is built into human tendency or not. 648 00:50:44,864 --> 00:50:48,776 Is it something that we learn or something that we have and we express? 649 00:50:48,776 --> 00:50:54,219 And the uh the actual episode is called the the reasoning test. 650 00:50:54,219 --> 00:50:56,441 Psychologists still can't explain. 651 00:50:56,441 --> 00:51:00,883 And it it they talk a lot a little bit of what's called the Wasson selection task. 652 00:51:00,903 --> 00:51:12,609 And what it does is it goes into how, depending on the context, if it resembles something that we have grown up with or cultural standards or norms, we're very it's much easier for 653 00:51:12,609 --> 00:51:13,792 us to answer. 654 00:51:13,792 --> 00:51:15,683 Or have intuition about that. 655 00:51:15,683 --> 00:51:23,745 But if the topic is very mathematical, or is based in logic only, then our reasoning doesn't kick in as fast. 656 00:51:23,745 --> 00:51:25,025 And that's interesting. 657 00:51:25,025 --> 00:51:28,506 If it's a cultural bias, reasoning very quickly. 658 00:51:28,506 --> 00:51:35,968 And uh I'm gonna have some further picks in the future, but for this one in particular, P I have a question for you. 659 00:51:35,968 --> 00:51:39,189 Are you a fan of proof by contradiction? 660 00:51:39,849 --> 00:51:41,059 You can say I don't know what that is. 661 00:51:41,059 --> 00:51:41,539 Yeah. 662 00:51:41,539 --> 00:51:41,870 Yeah. 663 00:51:41,870 --> 00:51:43,980 Uh so this is 664 00:51:44,980 --> 00:51:57,200 Yeah, so proof by contradiction is this strategy for deter to countering arguments where you show that there's a flaw in the argument that's being made by showing the outcome of 665 00:51:57,200 --> 00:52:01,303 that argument directly contradicts one of the original premises. 666 00:52:01,303 --> 00:52:10,891 Without going into a mathematical proof, it could be that someone just says, you know, we should work on feature A because we need it for customer A, uh, because they have some 667 00:52:10,891 --> 00:52:12,072 requirements, A. 668 00:52:12,072 --> 00:52:14,874 But when you look into it and you ask questions about that, 669 00:52:14,886 --> 00:52:19,811 you find out that what the customer actually needs is the opposite of A. 670 00:52:19,811 --> 00:52:22,343 And you say, wait, this customer says I don't want A. 671 00:52:22,343 --> 00:52:25,897 And then you bring this as evidence to why we shouldn't do this feature. 672 00:52:25,897 --> 00:52:29,100 They want this thing and it directly contradicts this other thing. 673 00:52:29,100 --> 00:52:32,513 Well, it for me, this is so obvious. 674 00:52:32,513 --> 00:52:36,216 I had I learned about proof by contradiction and I fell in love with it. 675 00:52:36,216 --> 00:52:40,520 It just seems so like such a natural thing to use in a conversation or an argument. 676 00:52:40,682 --> 00:52:46,526 but it only occurs to me recently that this is a learned behavior, a learned i idea or concept. 677 00:52:46,526 --> 00:52:48,087 It's not something that we're born with. 678 00:52:48,087 --> 00:52:57,254 Understanding that things contradict each other is a logical paradigm that's natural, but not something that we have a basic tendency for. 679 00:52:57,254 --> 00:53:04,018 And what's really interesting to me is that it may actually be incompatible with anyone that doesn't have a logical or technical background. 680 00:53:04,018 --> 00:53:09,494 The the concept of that we can have a discussion and we can lay out axiom or premises. 681 00:53:09,494 --> 00:53:14,998 and come to a conclusion based off of that and then show how our conclusion is flawed based off of new data. 682 00:53:14,998 --> 00:53:20,492 That isn't something that everyone actually is born with or fundamentally understands. 683 00:53:20,568 --> 00:53:21,621 Yeah, I agree. 684 00:53:21,621 --> 00:53:22,924 I had to learn that one. 685 00:53:22,924 --> 00:53:28,979 And I learned it actually from a good friend who's uh yeah, who used to work in software engineering. 686 00:53:30,254 --> 00:53:33,495 This seems like a a a long and interesting stor a story. 687 00:53:33,495 --> 00:53:39,647 Uh but for the maybe that's a m another topic for uh another day. 688 00:53:39,647 --> 00:53:51,761 so it's the series is called The Rest is Science and it has Michael Stevens of V Sauce Fame, the U influencer, uh, and Hannah Fry, the PhD mathematician out of I believe 689 00:53:51,761 --> 00:53:52,631 England. 690 00:53:52,631 --> 00:53:53,451 they're they're really great. 691 00:53:53,451 --> 00:53:55,932 They're very technical and they really dive into each of the topics. 692 00:53:55,932 --> 00:53:56,662 So 693 00:53:56,662 --> 00:54:02,589 I think it's very interesting and it's definitely giving me a new insight into when I engage with conversations with other people. 694 00:54:02,589 --> 00:54:10,528 If I'm trying to argue against them, I also need to make sure that we understand how disagreements work. 695 00:54:10,914 --> 00:54:11,636 Absolutely. 696 00:54:11,636 --> 00:54:12,227 I love it. 697 00:54:12,227 --> 00:54:12,648 Thank you. 698 00:54:12,648 --> 00:54:14,412 I'll definitely check it out. 699 00:54:14,554 --> 00:54:19,797 Uh okay, so with that I wanna say thank you, Pia so much for joining us uh this week. 700 00:54:20,959 --> 00:54:26,534 Um and thanks for all the listeners for for tuning in and I hope to see everyone back again next.