Latest / Coffee with Developers / Agentic Software Engineering - Dr. Ralf S. Engelschall

Transcript

Agentic Software Engineering - Dr. Ralf S. Engelschall · Coffee with Developers

• 0:01
  SPEAKER_00: Hello and welcome to another coffee with developers.
• 0:04
  SPEAKER_00: I'm here with a person that uh knows a lot about security, knows a lot about development.
• 0:09
  SPEAKER_00: We just actually chatted for about 20 minutes about how it was like in the 80s and 90s to be a developer and how it's differently today.
• 0:17
  SPEAKER_00: So uh without further ado, here's Dr.
• 0:19
  SPEAKER_00: Ralf Engelschall from CT.
• 0:21
  SPEAKER_00: He's the CTO of MSG Group.
• 0:22
  SPEAKER_00: So, what is what first of all was MSG Group?
• 0:25
  SPEAKER_01: What do you do?
• 0:26
  SPEAKER_01: Chris, good morning.
• 0:27
  SPEAKER_01: Uh what is MSG?
• 0:28
  SPEAKER_01: Well, it's uh a software engineering company and uh with 11,000 people located in Germany, actually in Munich, Germany, where I'm sitting and um we're doing uh business information system for large-scale enterprise customers.
• 0:39
  SPEAKER_01: So these are the pieces of software which well have a few hundred thousand lines of code and drive the uh core processes of enterprise customers.
• 0:48
  SPEAKER_00: You've been around for quite a while.
• 0:49
  SPEAKER_00: I mean, you've been part of the Apache Foundation, you do you've done a lot of security little bits and bobs that we all use still in our environments now.
• 0:57
  SPEAKER_00: How do you see the world changing?
• 0:59
  SPEAKER_00: Like, uh I mean I remember when I when I went from that enterprise world, and then we got the web 2.0 startup world, and then we got the e-commerce world, and then we got crypto, and everybody told me I have to do that, and now it's basically AI.
• 1:12
  SPEAKER_00: How do you keep up?
• 1:13
  SPEAKER_00: And how do you or are you as confused as I am about what's happening at the moment?
• 1:17
  SPEAKER_01: Well, I've at least the opportunity to do it as my my primary job as a CTO.
• 1:22
  SPEAKER_01: So uh AI and cloud and all those things is part of my day job.
• 1:26
  SPEAKER_01: So I don't have to do it only as in past in my free time.
• 1:29
  SPEAKER_01: I can do it uh in the regular time.
• 1:31
  SPEAKER_01: But yes, it's uh hard to keep up because especially in the AI field where more or less uh well every week a partly new world order occurs, and at least one uh after month after month, uh a new world order uh occurs.
• 1:44
  SPEAKER_01: Uh, this is horrible, actually, and especially if you get older.
• 1:48
  SPEAKER_01: I'm uh over 50 now, and it's not such easy as it was uh 30 years ago, uh definitely.
• 1:54
  SPEAKER_01: So it's uh sometimes uh confusing world because too many things happen on all edges, and it's um it's hard to cope with all of those things.
• 2:02
  SPEAKER_01: Uh for me, uh the main primary focus, actually, well, I would say 90% of my CTO job is located in the AI field currently.
• 2:11
  SPEAKER_00: And uh I guess with like customers having to uh wanting to, needing to, and uh and wanting to have AI in their things and not knowing how to.
• 2:21
  SPEAKER_00: So I think it's it's easy for a startup to embrace the coolest, newest stuff, but for a company of like 600 people with like a software package that's like 23 years old, not so much.
• 2:32
  SPEAKER_00: But do you still get a lot of requests from customers to actually say, like, we need to do this because there's a FOMO kind of feeling?
• 2:39
  SPEAKER_01: Uh definitely.
• 2:40
  SPEAKER_01: Uh all uh enterprise customers have uh AI transformation programs and other things running where they on one side try to uh transform their own uh delivery and their own employees to use AI and uh gain uh product uh productivity here.
• 2:57
  SPEAKER_01: And the other one is uh to do in their business, put more AI for their end customers in into their products.
• 3:02
  SPEAKER_01: And this is where uh companies like MSG help out through consulting, but also to through software, because uh, well, today you cannot ship any piece of software without at least an AI label, and uh, this AI label underneath uh has to show AI-based features and functionalities, more or less to show uh new features and new uh possibilities to AI.
• 3:24
  SPEAKER_01: So all enterprises evaluate AI things and uh actively and aggressively put those AI things into their own offerings.
• 3:32
  SPEAKER_01: And uh companies like MSG, which are in the second row and delivering those solutions uh this way has a lot of stress to deliver those AI solutions.
• 3:41
  SPEAKER_01: But even on our internal delivery, we also uh have an AI transformation program where we have to enable more and more our developers to gain even more productive through the use of AI for ourselves in the software engineering itself.
• 3:55
  SPEAKER_00: The other problem that I found is that we're we seem to be in a world where there's like the the uh uh the first level people that get it, and then Europe gets it.
• 4:03
  SPEAKER_00: When I worked for Microsoft, and especially with when I talked to Microsoft Germany, because I work for Microsoft US, they were all like, we're still trying to get German customers to embrace the cloud rather than like have the one server farm that they bought in 1983 and have back in the basement of their of their housing.
• 4:19
  SPEAKER_00: Do you think the the it's now the speed of what we have right now forces people to actually embrace new technology more?
• 4:27
  SPEAKER_00: And if they do, oftentimes it basically is like here's a cool new model that you can only use if you're in America.
• 4:33
  SPEAKER_00: How do we deal with that?
• 4:34
  SPEAKER_01: Well, at the end it it boils down to the sovereignty discussion.
• 4:38
  SPEAKER_01: Uh, but yes, you you're you're forced to use the things which are available because you cannot afford to just ignore the how fast the technology, especially in the AI field, uh, drives.
• 4:49
  SPEAKER_01: So um, even for us, uh, it means to use uh US uh models, pharmacic open AI, and other things.
• 4:55
  SPEAKER_01: Yes, there are uh alternatives from the Asia side, but Europe has too less to offer here currently.
• 5:03
  SPEAKER_01: So if you are in the business and have to use AI, you are more or less forced to use even the uh US offerings.
• 5:09
  SPEAKER_01: You have more and more now uh through the uh sovereignty um um discussions, uh more and more possibilities in Europe, but it's still too less.
• 5:19
  SPEAKER_01: You cannot go without more or less in practice.
• 5:22
  SPEAKER_01: Uh just take the example of uh the offering of uh clothed code and the clothes uh uh LM from Anthropic.
• 5:29
  SPEAKER_01: It's uh really a frontier model.
• 5:31
  SPEAKER_01: And if you want to do first-class development, really be on the frontier yourself, you have to use it, yes?
• 5:37
  SPEAKER_01: Uh and even uh things like uh a lot of people talking, for instance, about the okay, let's do it here locally in Europe, or even locally in your own uh room.
• 5:45
  SPEAKER_01: Uh it's uh nearly impossible currently because if you look on uh really locally I on own hardware, you don't get the necessary token per second.
• 5:54
  SPEAKER_01: You don't get uh near this quality the frontier models from the US currently provides.
• 5:59
  SPEAKER_01: So, in practice, uh it's uh it's a um a schizophrenic situation because we are we are talking about sovereignty on one side and would like to have more things locally in Europe.
• 6:10
  SPEAKER_01: On the other side, we are forced to use the US and Asia offerings because of the quality and and the speed, uh, and especially in the cloud, and you cannot really do it uh on premise.
• 6:20
  SPEAKER_01: So it's uh it's a hard uh situation currently where we would like to do more locally and on our own, but it's uh really not possible on the market, at least if you want to leverage the high quality and speed which is currently offered by others in the cloud.
• 6:35
  SPEAKER_00: I mean, we have things like Aleph Alpha offering things in Europe, stack it is trying to do the hosting stuff, but yeah, it feels it feels more convenient to actually use the American and the Chinese offerings, but at the same time, convenience sometimes means lock-in as well.
• 6:50
  SPEAKER_00: That's the that's the other problem with that.
• 6:52
  SPEAKER_00: Uh but and I mean as you said, like on-prem is almost impossible because you can't buy hardware anymore.
• 6:57
  SPEAKER_00: I mean, the RAM is basically out there.
• 6:59
  SPEAKER_00: Like, I've I just got Nvidia just gave me a GTX Spark, and I I still have to set it up because I'm super excited about it.
• 7:05
  SPEAKER_00: But I was like, this took this took like four months to deliver, and that was from NVIDIA directly.
• 7:10
  SPEAKER_00: So it feels like the market is pretty empty on that.
• 7:13
  SPEAKER_01: This NVIDIA technology definitely has a large potential to give us new possibilities, but yeah, only once it is really available and for an affordable price at the end.
• 7:23
  SPEAKER_01: Uh, and um currently I see as a CTO, I see no possibility to really, at least for the next uh six or twelve months, to go without the uh cloud services uh of the frontier um um offerings in in the US.
• 7:38
  SPEAKER_00: Mind you, we still got Microsoft and Google, which all have German server farms as well, if you wanted to use them.
• 7:43
  SPEAKER_00: But I I I feel like both of them have kind of lost the pace compared to the others, to the smaller, faster moving ones.
• 7:51
  SPEAKER_00: So it feels it feels kind of stuffy to actually start using Google Cloud or or Microsoft Cloud instead of OpenAI or Cloud.
• 7:57
  SPEAKER_01: Yeah, OpenAI and Cloud idea from Anthropic is this, these are really the frontier ones.
• 8:02
  SPEAKER_01: And if you as I said, if you want to be on the frontier from quality and speed, currently you have to use them.
• 8:09
  SPEAKER_01: I dislike it myself as a European guy, but um currently I see no real alternative.
• 8:14
  SPEAKER_01: But I hope it comes because to be fair, uh, the way it currently goes in the market, that there is no end, even when it comes to prices, it's fully sponsored.
• 8:24
  SPEAKER_01: Even the high prices currently are still fully sponsored.
• 8:26
  SPEAKER_01: They do not uh get the never necessary revenue what uh they have on the other side on costs.
• 8:31
  SPEAKER_01: So even those uh companies like OpenAI and Entropic have large gaps between their revenue and uh their costs.
• 8:38
  SPEAKER_01: So uh this is not the end.
• 8:40
  SPEAKER_01: And if it becomes even more expensive and expensive over time, there will be uh an explosion, I think.
• 8:46
  SPEAKER_01: This cannot uh work uh any longer.
• 8:48
  SPEAKER_01: So I definitely hope that something changes.
• 8:51
  SPEAKER_01: But either technologies, for instance, like Nvidia Spark, could help here.
• 8:55
  SPEAKER_01: Uh, the other would be perhaps that uh new transformer architectures and other things on the conceptual side perhaps are invented, and this way um, as good um from the quality side, models can be established with a lot less uh resource uh uh consumption.
• 9:12
  SPEAKER_01: So this would be another possibility, but currently it is for the for the next six or twelve months.
• 9:16
  SPEAKER_01: I personally don't see it that uh this world changes here.
• 9:20
  SPEAKER_00: Well, Jeff showed a good way of actually how you can actually pre-u uh save on tokens by having a different model that's pre-trained, that's pre-weighted.
• 9:28
  SPEAKER_00: These kinds of things are possible.
• 9:30
  SPEAKER_00: Also, you can put your own racks in front and basically make sure that you that in the company, when you have 11,000 people, that some knowledge that has been done has is cached locally with a with a vector database or something like that.
• 9:41
  SPEAKER_00: That makes uh that makes the for lesser consumption.
• 9:44
  SPEAKER_00: I'm very happy that that token maxing thing is off the table again, because that was the most ridiculous thing I heard in a while.
• 9:50
  SPEAKER_00: Like it was like it's like when we got paid for lines of code, and you're like, great, I'm gonna write the most ineffective code that is really, really long and make myself a car for that.
• 10:03
  SPEAKER_00: Seeing that you are a patchy person and open source person, it very much uh cares of my uh of my uh uh statue.
• 10:10
  SPEAKER_00: We throw the world or the word open around a lot in the AI space, but then it never is open.
• 10:16
  SPEAKER_00: It's only open weights, it's not open models.
• 10:19
  SPEAKER_00: Do you think there is uh there is a chance for that?
• 10:22
  SPEAKER_00: Because right now it seems like uh there's like all this up uh uh uh let's make it not up not public, so we can say it's actually an amazingly powerful thing.
• 10:31
  SPEAKER_00: Like with open source, you cannot hide anything, but with closed source you can.
• 10:35
  SPEAKER_00: And I think there's uh when it comes to getting investments, you need to hide things, right?
• 10:39
  SPEAKER_01: Yeah, this is what currently happens.
• 10:42
  SPEAKER_01: Uh as you mentioned, open weight is not open source here.
• 10:45
  SPEAKER_01: It means the training data and other things is not available, it's just the resulting weights.
• 10:49
  SPEAKER_01: Uh, a few of the uh LM vendors start uh more and more to really also show how is the training done, what is the training material, but it's it's very thin currently.
• 11:00
  SPEAKER_01: Most of the stuff is is closed and uh, well, at maximum it's open weight at the end, but not really when it comes to uh do it yourself with the training data and all this stuff at once.
• 11:10
  SPEAKER_01: So um it can become better.
• 11:12
  SPEAKER_01: I would like as an open source guy that we have really open source models at the end, but uh I can imagine that um and I understand they protect this way their own investments by keeping or hiding things.
• 11:24
  SPEAKER_01: Um and the point is uh if you compare it with the open source software field, um, here it's easier because your investments are not such high.
• 11:33
  SPEAKER_01: But once you have to spend millions to train things, I can also, as an open source guy, I understand that I have to do something uh more to protect it and not lose those things because this is really a lot more investment than we had on the bare software side.
• 11:48
  SPEAKER_01: So, yes, even as an open source guy, I can understand it, but I dislike it that it's uh not uh really open source, what we see here.
• 11:55
  SPEAKER_00: Now, the other the other tension that we feel right now is that everybody says, like, oh, agentic coding, don't do any code by hand anymore, that's only for old people.
• 12:03
  SPEAKER_00: Uh, I still like writing code, it makes me happy.
• 12:06
  SPEAKER_00: Yeah, and uh, but it feels like that there is a pace issue that like uh generated code in an agentic environment is so much faster to create and also much faster to discard as well as handwritten code.
• 12:19
  SPEAKER_00: So, how do these two worlds come together?
• 12:21
  SPEAKER_00: Because I guess in your space, uh it this is basically a tricky bit because the the generated code will never be uh will never be merged.
• 12:29
  SPEAKER_01: Yeah, the point is uh my heart bleeds actually after four decades of intensive coding myself in this field.
• 12:36
  SPEAKER_01: So, yes, I really it bleeds all the time.
• 12:39
  SPEAKER_01: On the other hand, I have the job of a CTO in the industry, and uh uh here I have to do a different point of view.
• 12:45
  SPEAKER_01: Um, I can just uh tell you with uh projects like agentic software engineering, this AZ.tools, what uh in the open source field, I try to make my peace with the situation by merging those things.
• 12:57
  SPEAKER_01: So leverage from a Gentic eye on one side, even if yes, my heart bleeds, because bare coding, yes, it's dead, actually.
• 13:05
  SPEAKER_01: Yeah, people like you and me, we still like it, and our heart bleeds, but on a bare fact uh uh level, we have to uh say uh manual coding is dead because the AI can do it faster, more precise, and actually cheaper at the end.
• 13:22
  SPEAKER_01: So this we we have to accept uh it's a new uh era uh where we entered uh about in in the quarter one of uh 2025, um, and with also tools like Clot Code and the uh uh versions of Cloud uh LM at these times.
• 13:37
  SPEAKER_01: So this is an agentic AI era where new possibilities exist, and it doesn't matter whether our uh heart bleeds, we have to cope with this.
• 13:44
  SPEAKER_01: And uh well, I might try to make peace by fusing those things together and saying, okay, on one side we have agenti AI with new possibilities.
• 13:52
  SPEAKER_01: On the other hand, uh, I like code, I like software, that's my my my my life.
• 13:57
  SPEAKER_01: And uh, how can we still produce quality results at the end, even if we are using uh uh AI to produce this stuff?
• 14:05
  SPEAKER_01: And um, this is not easy because at the end, uh you can tell uh an uh in clot code, just enter a few prompts and tons of code immediately can get generated.
• 14:16
  SPEAKER_01: And this is what you see all the time on Reddit when someone says, I have built something.
• 14:20
  SPEAKER_01: Uh, I sometimes even get angry when I when I see this.
• 14:23
  SPEAKER_01: I say you have nothing built.
• 14:25
  SPEAKER_01: It was the AI, but it's okay, okay, on one side.
• 14:29
  SPEAKER_01: Um, the point just is what those people most of the time create is convenience software, something a little utility or desktop app, uh, which where there is no risk or anything, and where it actually doesn't matter whether the code is really good or not, it's just essential that it works.
• 14:46
  SPEAKER_01: And even if it breaks, you just restart it.
• 14:48
  SPEAKER_01: There is no risk.
• 14:50
  SPEAKER_01: Um, if you compare this with the regulated market where we are in the industry are working for banking, insurance is uh, etc., where software has to last for uh 15, 20, 25 years on one side, have to really be compliant to a lot of law uh issues, etc.
• 15:08
  SPEAKER_01: Um, here you cannot just white coat something, so this doesn't work.
• 15:12
  SPEAKER_01: Yeah, so we cannot directly transfer these the same idea, okay.
• 15:16
  SPEAKER_01: Let's sit on a software engineer in front of uh code and let's enter a few prompts and get tons of code generated.
• 15:23
  SPEAKER_01: Here we really have to find a balance between the new possibilities on one side with AI and the constraints on the other side.
• 15:31
  SPEAKER_01: And this is more or less the difference for me between software programming or bear development and software engineering, because engineering, all the time, even in the past without AI, was about the processes and structuring and all those things around to really ensure that you get a transparent process where traceability exists, where you can at least ensure that certain qualities exist, etc.
• 15:56
  SPEAKER_01: So this is more or less a risk mitigation process, if you want, uh software engineering.
• 16:01
  SPEAKER_01: And yeah, in these days now, we have to bring those pieces together: the software engineering risk uh mitigation process on one side, and the possibilities of urgent AI coding tools like Look Code, where a lot of things can be generated in just a few minutes, uh, because they actually don't fit immediately together because there's uh an obvious clash, because it's different types of software you create, actually, with those different pieces.
• 16:28
  SPEAKER_00: And you don't want to be a gatekeeper, you want to actually allow people to be creative with generated code and generated apps.
• 16:37
  SPEAKER_00: And I'm I mean, I'm seeing people in our sales team using using Claw to build little apps for themselves.
• 16:43
  SPEAKER_00: That actually asking us in the engineering team would have done more, would have been like, yeah, we put it on the backlog and then we get to it when we get to it, rather than just empowering them to do the stuff that, as you said, is throwaway because it's only used internally.
• 16:57
  SPEAKER_00: It's still an opportunity to leak your tokens and to leak your keys, uh, which happens a lot as well.
• 17:04
  SPEAKER_00: But you don't want to be that that Starboard person that says, like, oh, only engineers can touch the code.
• 17:09
  SPEAKER_00: It's actually fine to do that.
• 17:11
  SPEAKER_00: At the same time, it reminds me of when what you see is what you get editors came out, and I was a front-end developer, and people like, oh, my cousin has Dreamweaver, he can make it for 200 euros rather than the 1200 that you want to have.
• 17:22
  SPEAKER_00: And that's still the same thing.
• 17:24
  SPEAKER_00: We or we sort of basic people in the past, like you know.
• 17:27
  SPEAKER_01: Well, actually, this pattern goes over all the decals I was involved.
• 17:31
  SPEAKER_01: Uh, in I can remember in the year 2000, we are talked about case, computer-aided software engineering.
• 17:38
  SPEAKER_01: Later in the 2010, we talked about uh model-driven development, then we talked about low-code, no code.
• 17:45
  SPEAKER_01: Currently, we are doing wipe coding and in a Gent D GI.
• 17:48
  SPEAKER_01: It's always, I would say, the same pattern.
• 17:50
  SPEAKER_01: People like to get rid of the nasty programming.
• 17:53
  SPEAKER_01: Even I like programming, but a lot of people say, ah, it's nasty, it's a lot of effort I have to place.
• 17:59
  SPEAKER_01: Uh, I want to draw just software or I sketch software, and it should come out and it immediately work.
• 18:04
  SPEAKER_01: So there is a large track record in our society that uh in the IT society that we want to get rid of programming a little bit all the time with different approaches.
• 18:15
  SPEAKER_01: And I would say the Atlantic AI area currently is the latest one, um, certainly the most powerful one, also, to get rid of this stuff.
• 18:22
  SPEAKER_01: Uh, but it has its limits because it uh doesn't work for for, as we said, for convenience software, a little bit desktop app, utility.
• 18:30
  SPEAKER_01: It it doesn't matter what the code is about, it doesn't matter what the it just has to work.
• 18:35
  SPEAKER_01: And if it doesn't work, well, it's just this particular use case is broken.
• 18:38
  SPEAKER_01: Nothing happens, there's no real risk.
• 18:41
  SPEAKER_01: So uh I fully understand those approaches.
• 18:43
  SPEAKER_01: Uh, even for low code, it's uh there are brilliant low-code and no-code platforms on the world, but also those have limits.
• 18:52
  SPEAKER_01: And the limit more or less is obvious once you want to customize the solution uh towards more your shaping in the UI and particular functionalities, then though you have to work against those platforms all the time.
• 19:04
  SPEAKER_01: And similar here now in the agentic AI era.
• 19:07
  SPEAKER_01: Um, you can say, okay, create me something, but if this should have a certain quality, if it should be really this way and that way, you have to prompt a lot of things and it becomes more and more complicated.
• 19:19
  SPEAKER_01: So it's, I would say, the same pattern all the time.
• 19:22
  SPEAKER_01: People in the IT like to get rid of their nasty efforts to create software with different patterns over the time.
• 19:29
  SPEAKER_01: Currently it's a Genti AI.
• 19:31
  SPEAKER_01: And to a certain extent, it works great.
• 19:33
  SPEAKER_01: Uh, but one has to understand where the limits are.
• 19:37
  SPEAKER_01: And once you hit those limits, for us, it's for instance, we have well, a business information system with a few hundred lines of code where uh they are uh used in uh regulated markets like insurance and banking.
• 19:48
  SPEAKER_01: There are different constraints than you have on a desktop application.
• 19:52
  SPEAKER_01: And once you uh hit those limits, you have to find a way to fuse classical software engineering once again with a Gent DGI, because else you will not be able to cope with this situation of this limiting here.
• 20:07
  SPEAKER_00: Yeah, I think the the uh it's an interesting world where we actually try to do that.
• 20:11
  SPEAKER_00: I mean, I'm I'm actually happier to be gotten rid of the enterprise world where you had like UML, SOAP, XML, XSLT work back then.
• 20:20
  SPEAKER_00: Like that was the thing where I'm like, okay, the web was so much faster, and now we got these things.
• 20:25
  SPEAKER_00: One worry I have, I'm I mean, we just have a coding competition coming up, and I just said, like, do something creative.
• 20:30
  SPEAKER_00: So I tried all the different uh different platforms out to give it an HTML document and say, like, do something creative with it.
• 20:36
  SPEAKER_00: All of them gave me an HTML document back that I can put on GitHub and show people right now.
• 20:41
  SPEAKER_00: In one provider, basically, like, oh, you have to use our IDE to actually access the thing.
• 20:46
  SPEAKER_00: You do it for the first time.
• 20:48
  SPEAKER_00: We need to verify you, you have to pay$20 to get access and create a key.
• 20:52
  SPEAKER_00: And then it generated a uh a dynamic HTML page, not the HTML, but dynamic HTML page, that basically had the key inside.
• 21:02
  SPEAKER_00: And I'm like, okay, I can't share this on a public repo now.
• 21:06
  SPEAKER_00: So a lot of this convenience is basically just a lock-in, isn't it?
• 21:10
  SPEAKER_01: Yeah, sure.
• 21:11
  SPEAKER_01: This is also the problem of those platforms.
• 21:14
  SPEAKER_01: Uh, all platforms have more or less, uh, from the business side, this built-in lock-in effect.
• 21:20
  SPEAKER_01: This is one of the reasons why vendors actually do this.
• 21:22
  SPEAKER_01: Um, you have to accept it or not.
• 21:24
  SPEAKER_01: Uh sometimes it's nasty and you don't want it because this login can be nasty.
• 21:29
  SPEAKER_01: You cannot change the vendor easily.
• 21:31
  SPEAKER_01: Uh, on the other hand, it is very convenient because you can uh immediately uh get your stuff running.
• 21:37
  SPEAKER_01: It's uh I would say it's it's very similar to cloud offerings.
• 21:40
  SPEAKER_01: Uh look here.
• 21:41
  SPEAKER_01: Uh, if you go to AWS, they have uh an immense large amount of services they can offer you.
• 21:47
  SPEAKER_01: But once you pick them, you get locked because you cannot, for instance, easily switch from AWS, Lambda to Azure Functions, for instance.
• 21:55
  SPEAKER_01: Uhoretically, you could, but uh at the end, it's a lot of effort to transport the things.
• 22:00
  SPEAKER_01: So, yes, uh it's uh clear that from a business perspective, AWS tries hard to establish this login on one side.
• 22:08
  SPEAKER_01: So you have to accept uh is it uh in my case convenience I really want to have, then you have to accept the login.
• 22:15
  SPEAKER_01: If you don't uh need this type of convenience and uh can put a more effort on it and want to avoid the login, yeah, you have to go another uh uh uh way and uh create more standalone solutions.
• 22:26
  SPEAKER_01: So I would say it's always the same problem with platform with platforms, uh even with frameworks in programming.
• 22:33
  SPEAKER_01: They give you limits, but within those limits, you have great convenience.
• 22:38
  SPEAKER_01: But once you want to get out of those limits, you are out of the game.
• 22:43
  SPEAKER_00: Cool.
• 22:44
  SPEAKER_00: So let me talk, uh let's talk about your project right now that you're excited about, and that is ASE agentic software engineering.
• 22:51
  SPEAKER_00: That sounds like it's actually two things that shouldn't fit together.
• 22:56
  SPEAKER_01: Exactly.
• 22:57
  SPEAKER_01: Agentic AI on one side with tools like Cload Code, and then came on the other side the software engineers, which are proud of their, as I said, uh traceable processes and all this other stuff.
• 23:07
  SPEAKER_01: Um, here we first have to understand, and this is a misunderstanding for most people, software engineering is not software development.
• 23:13
  SPEAKER_01: Okay, so software development on one side can be, if you want, broken down to ad hoc creating your user stories and other things and creating uh the software, so the the bare programming if you want.
• 23:24
  SPEAKER_01: So for me, it's an onion model.
• 23:25
  SPEAKER_01: You have programming, you have software development, you have software engineering.
• 23:28
  SPEAKER_01: And software engineering is all those additional things for uh the processes together, traceable process, requirements engineering, software architecture, testing, project management, etc.
• 23:40
  SPEAKER_01: Okay.
• 23:40
  SPEAKER_01: And uh yes, it sounds uh those two things uh do not belong together, or how can they belong together?
• 23:46
  SPEAKER_01: Well, for me, it was very simple.
• 23:48
  SPEAKER_01: On one side, I want in the industry that uh even we are a software engineering company, have to do large-scale business information systems with hundred lines of code for enterprise customs.
• 23:57
  SPEAKER_01: On one side, where software engineering is the core business, I want to leverage from a Gent DGI because uh I like Agen DGI.
• 24:04
  SPEAKER_01: It's great what what possibilities exist, but yes, you immediately catch it.
• 24:08
  SPEAKER_01: It doesn't directly belong together.
• 24:10
  SPEAKER_01: So, what I've done is uh in this Gentic Software Engineering, or in short, AZ as I call it, in this AZ project, is to do a fusion here.
• 24:18
  SPEAKER_01: Uh, technically, you can just imagine it's a plugin for a cloud code, uh GitHub Copilot, or uh OpenAI codex.
• 24:25
  SPEAKER_01: So you have your Gentic AI tool, you plug in this ASI plugin, and you get additional functionalities.
• 24:32
  SPEAKER_01: Those functionalities hook into this agent through so-called uh, yeah, here this is uh the setup of what you see on the screen.
• 24:39
  SPEAKER_01: Um, you get additional skills, you get uh status lines, you get hooks, uh mods, uh whatever the particular underlying tool actually provides, and AZ adds additional functionalities.
• 24:53
  SPEAKER_01: Those functionalities, what a software engineer in industrial practice needs all the time.
• 24:57
  SPEAKER_01: So this starts from doing things like I can do my requirements engineering, um, in a fashion where not just entering a talk prompt, but I do either task-based, user story-based uh uh spectrum development or the other way of spectrum development, uh coherent binding document, but not in a way that I write a Word document or a confluence wiki or something like this as a document, but with the Gentic AI tool.
• 25:25
  SPEAKER_01: So you can imagine, for instance, with AZ, if you do uh a specification, it means you have on your uh JIT repo uh a few markdown files.
• 25:34
  SPEAKER_01: But it's not just arbitrary markdown files, it's typed markdown files, which gets strictly linted in your build process and your gentic AI coding tool, like uh Cloud Code, through the help of AZ, gets known all the meter information, the meter model behind the specification, the schema, etc.
• 25:53
  SPEAKER_01: So it understands your specification structurally wise, exactly the way it understands your TypeScript code, for instance.
• 26:01
  SPEAKER_01: And this brings you onto a new level.
• 26:03
  SPEAKER_01: So Cloed Code is great to do ad hoc things, it has a lot of knowledge.
• 26:07
  SPEAKER_01: But when you want more strict software engineering through a requirements process here in this situation with a binding document, if you want to do task-based uh agentic development pipelines where engineers, though humans, and agents uh alternate in the in uh working on a particular user story, you need more.
• 26:28
  SPEAKER_01: And this is what agentic software engineering provides.
• 26:30
  SPEAKER_01: Um, agentic software engineering, for instance, has the possibility to create your user story in a task, move it to an engineer.
• 26:36
  SPEAKER_01: The engineer takes this task, works on it through cloed code, and then it hands is it's picked up by an agent.
• 26:42
  SPEAKER_01: This agent implements this code, and then the human once again comes, picks it up, uh, and does the review.
• 26:48
  SPEAKER_01: And later another agent picks it up and merges, for instance, the feature from the feature branch to the master branch.
• 26:55
  SPEAKER_01: So AZ is more or less putting the software engineering traditional processes onto agentic AI coding tools like Cloud Code.
• 27:04
  SPEAKER_01: And yeah, it's a little bit strange fusion, perhaps, but it is actually what allows you at the end to drive software engineering on one side with or leverage from the possibilities of agentic AI tools like Cloud Code.
• 27:18
  SPEAKER_01: So it's really a fusion of two things where on the first spot, yeah, do not belong together, but work like Wonder, actually.
• 27:25
  SPEAKER_00: So, how does that differ from a harness environment that you put around your code that gets generated?
• 27:32
  SPEAKER_01: Um, the harness itself is it's more or less pimped up with AZ on one side through hooks, mod skills, all the stuff.
• 27:38
  SPEAKER_01: Uh so though, this this changes, but it still feels like your regular cloed code if you want, but you have additional features all the time which uh guide you.
• 27:47
  SPEAKER_01: So, in technically, it's most of the time skills, but you have additional tools around this agent harness, like a Kanban board for visualizing uh your uh genti development pipeline, uh, all those additional things.
• 28:00
  SPEAKER_01: So it's more or less an extension of Cloud Code, if you want.
• 28:03
  SPEAKER_01: Yeah.
• 28:05
  SPEAKER_00: Or any other environment as well, it works with the other ones as well.
• 28:07
  SPEAKER_01: We could have copilots here line, open, yeah, because it just but the main focus is on Cloud Code because it's uh the most powerful uh Genti uh um agent harness currently on the market.
• 28:19
  SPEAKER_00: Now uh uh it's interesting to see you have the uh you have the uh uh the testimonials, which is like the first testimonials from yourself, which is an interesting way to like how how people embraced it?
• 28:32
  SPEAKER_00: Like, have you tried that with customers of MSG?
• 28:34
  SPEAKER_00: Have you tried an MSG internally, or is this a side project that you're working on?
• 28:39
  SPEAKER_01: Um all kinds of this.
• 28:41
  SPEAKER_01: Uh on one side, I'm developing uh ASI with ASI itself.
• 28:44
  SPEAKER_01: So all my open source uh projects in the last year are developed with ASI itself on on side projects.
• 28:52
  SPEAKER_01: Then we are using it internally inside MSG.
• 28:55
  SPEAKER_01: And uh we are also because we are doing not just uh creating products, we also do project uh with individualized uh custom software development for uh customers.
• 29:04
  SPEAKER_01: We are using it also there.
• 29:06
  SPEAKER_01: So it's used in multiple situations here because it's a toolkit, and as a toolkit, it's very flexible.
• 29:12
  SPEAKER_01: Uh sometimes just part of ASI is used.
• 29:15
  SPEAKER_01: Um, it can be even used just for requirement engineering, uh, and completely you can completely ignore all the code development stuff inside AZ.
• 29:24
  SPEAKER_01: Uh, on the other hand, you can just do your open source project with it and just focus on bare metal coding, more or less, with the help of a Genty GI and AZ and ignore, for instance, requirements, engineering, testing, and other things.
• 29:35
  SPEAKER_01: So, this is uh the the interesting point that it's a toolkit and you have a lot of tools inside there, and you can pick the particular tools.
• 29:42
  SPEAKER_01: They are not tied to a particular process or workflow or something like this.
• 29:46
  SPEAKER_01: And this is why on the website uh you can even read that you're in a driver's seat, so you decide what to do all the time.
• 29:53
  SPEAKER_01: It's not a fixed framework which enforces a particular process or enforces a particular type of uh tool to use.
• 30:00
  SPEAKER_01: So it's really a toolkit where you can choose on uh individual steps you do over your daily uh work hours, uh, what tool helps me and what uh can I ignore?
• 30:13
  SPEAKER_01: So I'm using even AZ myself in completely different fashions.
• 30:16
  SPEAKER_01: I'm sometimes even open clothing code and do just brainstorming and other things through those skills because the ADC has even all those things a consultant needs.
• 30:26
  SPEAKER_01: Uh just an example you want to find uh, for instance, software components on the internet, want to evaluate them with weighted decision matrices, want to uh create a decision for the customers, want to steal man this decision, or want an advocato diaboli to challenge your decision.
• 30:44
  SPEAKER_01: So this has nothing to do with coding.
• 30:46
  SPEAKER_01: This is also provided by AZ through a lot of skills.
• 30:49
  SPEAKER_01: Um, because uh yeah, in the daily life of a software architect and software engineer, you have to do a lot more than just coding.
• 30:56
  SPEAKER_01: So AZ supports also the coding part, but it provides a lot of additional functionalities for what software engineers need to do all the time.
• 31:06
  SPEAKER_01: And this is uh a lot more than just coding.
• 31:09
  SPEAKER_00: I love that it's really called Diaboli.
• 31:11
  SPEAKER_00: This is amazing.
• 31:12
  SPEAKER_01: Yeah, this is uh exactly this Diaboli is exactly the skill where you can give uh your um your statement or whatever you want and as an argument, and it tries to play the advocato diaboli.
• 31:24
  SPEAKER_01: And uh yeah, it's interesting what happens there, uh, because uh you will be surprised uh what the AI actually finds as counter-arguments or antithesis for your arguments.
• 31:36
  SPEAKER_01: I'm always surprised.
• 31:37
  SPEAKER_01: My most uh um yeah enjoyed feature of AZ is actually named grilling, uh, just to get you an impression here.
• 31:45
  SPEAKER_01: Uh, if you work with agentic AI coding tools like Lot Code, you can enter your prompt and it creates code.
• 31:51
  SPEAKER_01: But at the end, you will be not fully satisfied with the result because uh you understand, okay, this I want a little bit different and that.
• 31:59
  SPEAKER_01: It can be on the code level, it can be on the functionality side, it can be on the visible side on the UI.
• 32:05
  SPEAKER_01: And what you do is uh you prompt against the result and let the uh Gen TI fix it.
• 32:11
  SPEAKER_01: That's the usual thing people do.
• 32:13
  SPEAKER_01: And what we found is that uh it helps a lot more if you create your task and before it is implemented, you get grilled on it.
• 32:22
  SPEAKER_01: To get grilled on it means uh it uh the AI tries to relentlessly grill it your decisions, more or less, and find the open points because it's more efficient if the AI first tried to understand what later during implementation should be interpreted, and because it's open, it's most underspecified, so it's better to uh get questions on this and answer it before it is uh uh implemented than to post adjust the result all the time.
• 32:52
  SPEAKER_01: And uh this is interesting because when I invented this feature over um multiple iterations, um people were rather skeptic and said, Okay, I should be grilled for I'm already uh telling in my prompt exactly what I want.
• 33:05
  SPEAKER_01: And you would be surprised what uh then the bare uh world knowledge of an LM, a frontier LM, is able to do with your prompts and really figure out from the domain perspective, architecture perspective, implementation perspective, what the open points are.
• 33:21
  SPEAKER_01: And uh in practice, it means you give a very precise, from your perspective, prompt, and the AI comes back with a table of about 10 questions, and I can tell you, more or less uh nine to ten questions are absolutely essential, and you are surprised.
• 33:36
  SPEAKER_01: Oh, good that you actually uh uh raise those questions beforehand, because at the end, for all those decisions, which I usually would not have done, I had to do post adjustments.
• 33:48
  SPEAKER_01: So, this is one more experience from practice.
• 33:51
  SPEAKER_01: Um, agentic AI is great, but if you lap the agentic AI tool to really grill you for your decisions, the results become a lot better and you have to do less iterations all the time.
• 34:03
  SPEAKER_00: That's what people keep saying about by coding as well, that instead of just prompting, you should actually ask the uh the LLM to interview you, to basically say, like, I want to build this, interview me about specs.
• 34:15
  SPEAKER_00: And basically, much like a good uh software architect would do when we go to a customer, we just say, like, they're like, Oh, we want a login system.
• 34:22
  SPEAKER_00: Okay, what kind of login system, what kind of issues, what kind of like you know, that grilling happens in in meetings normally, and it seems like we're getting away from that, like, just tell the machine to do things, but like let the machine ask me to find the unknown needs that we had before.
• 34:40
  SPEAKER_00: Exactly.
• 34:40
  SPEAKER_01: This is what some people call brief engineering currently.
• 34:44
  SPEAKER_01: So you do a briefing of the machine, uh, and this way get a lot better uh results at the end because it's easier to work on particular domain-specific questions than you have to work on tons of generated code afterwards.
• 34:58
  SPEAKER_01: Uh, so this is exactly what can be done.
• 35:00
  SPEAKER_01: But you're uh here on the screen is uh, for instance, the Kanban board.
• 35:04
  SPEAKER_01: Um, you as a um an old school uh IT veteran uh certainly will like that.
• 35:09
  SPEAKER_01: This is grilling what you see here.
• 35:11
  SPEAKER_01: This is exactly you get uh a question, get the the be grilled, and can click on answers, and below you see the Kanban board.
• 35:18
  SPEAKER_01: And what you like is that in the left is the web UI, and you have the same on the terminal.
• 35:22
  SPEAKER_01: So even the Unix hackers like me uh have all the terminal available.
• 35:26
  SPEAKER_01: This is also uh sometimes people hate me for this, uh, but I like it.
• 35:30
  SPEAKER_01: I'm a Unix veteran, and uh AZA all skills have Unix uh long and short options and look like a Unix shell.
• 35:38
  SPEAKER_01: And uh even uh such a Kanban board, what we see here on the screen is actually identically.
• 35:43
  SPEAKER_01: If you just click on the uh uh screenshot on the uh right on the website, you see exactly the same on the terminal.
• 35:50
  SPEAKER_01: So it's uh implemented twice actually.
• 35:52
  SPEAKER_01: So the Unix terminal hackers can get uh the terminal exactly.
• 35:56
  SPEAKER_01: This is the terminal version, so you see that it resembles uh even from the colors and other things, the web version.
• 36:02
  SPEAKER_01: And this is the Kanban board where uh the lanes are more or less the agentic development pipeline where you put through your user stories, and uh you can imagine that the story is picked up by humans and agents all the time.
• 36:15
  SPEAKER_01: Um, and this is about statistics in this uh in the pipeline, etc.
• 36:19
  SPEAKER_01: So you see, it's a lot uh infrastructure in addition to what the regular agent GI coding tools like Cload Code provide in order to drive software engineering because soft engineering is a lot more than the bare coding part.
• 36:32
  SPEAKER_00: But you're using you're using uh uh uh light mode.
• 36:36
  SPEAKER_00: This is weird.
• 36:39
  SPEAKER_01: Well, the website is in dark mode, yes.
• 36:41
  SPEAKER_01: Uh uh, yes, it's it's real, it's true.
• 36:43
  SPEAKER_01: Uh, this is in light mode here, and uh but well, with the help of a gente GI we can easily add also a dark mode in the future if it's light.
• 36:51
  SPEAKER_01: Yes, it's it's uh the simple it's very simple because my terminal is in light mode, actually.
• 36:56
  SPEAKER_01: And that's the reason why even the web version is in light mode.
• 37:00
  SPEAKER_01: But light attracts bugs, that's the problem, isn't it?
• 37:04
  SPEAKER_01: Oh well, it it it it it depends uh what we're used to.
• 37:08
  SPEAKER_01: Uh, I'm working actually in in more or less in light mode all the time, uh, when it comes to the terminal since 40 years.
• 37:14
  SPEAKER_01: So this is my preference, but it doesn't matter very much at the end.
• 37:17
  SPEAKER_01: Most of the things uh inside AZ are uh, even for instance, uh things like uh the specification.
• 37:23
  SPEAKER_01: Um, yeah, here you see it on the screen, just go uh up.
• 37:26
  SPEAKER_01: Uh this is a light and dark mode uh stop here, no, a little bit down on spec, wherever the spec is here.
• 37:32
  SPEAKER_01: Uh you see uh there's light and dark mode equally.
• 37:35
  SPEAKER_01: So this is uh the generated specification out of AZ with uh uh sub-project is named Spec Book.
• 37:41
  SPEAKER_01: And here you see it's light and dark mode for both people who like dark or the other one who like light.
• 37:48
  SPEAKER_00: Now be honest, did you wipe code the website and the documentation or did you do it by hand?
• 37:54
  SPEAKER_01: Uh no, it it depends uh what I'm doing.
• 37:57
  SPEAKER_01: For instance, uh a website like AZ here is done with the Astro framework on one side.
• 38:02
  SPEAKER_01: So what I've done manually is establish all uh this framework stuff, Astro, Astro configuration, uh Tailwind, CSS selection, all this stuff.
• 38:11
  SPEAKER_01: But uh the particular content also came from me.
• 38:14
  SPEAKER_01: But uh all the fiddling on the website with all uh the tailwind uh uh CSS classes is done by the AI at the end.
• 38:21
  SPEAKER_01: So I I select uh the technology stack, I give the content, and the AI creates uh the particular layout here because uh, well, the last website I created myself was uh two or three years already ago, and I no longer have fun to do this stuff myself, even I'm as a web veteran can do it, obviously, but it's uh not necessary.
• 38:41
  SPEAKER_01: On the other hand, uh AZ functionalities below are partly hard-coded, partly uh through the eye, but it's not really by coding, just uh to give you here an understanding from my side.
• 38:51
  SPEAKER_01: Wipe coding means I tell with the prompt what I want, and I do not care about anything, how it actually looks, and I if it doesn't like uh what the result is I do another prompt.
• 39:00
  SPEAKER_01: Uh but I do more as brief engineering through AZ.
• 39:02
  SPEAKER_01: So I do a lot of initial thought uh together with the eye to brief the eye.
• 39:07
  SPEAKER_01: And so at the end, it's not really an arbitrary code which comes out, it's exactly the code.
• 39:13
  SPEAKER_01: It even is the code is exactly formatted uh as the other stuff.
• 39:17
  SPEAKER_01: So it's a lot of restrictions what I apply with AZ.
• 39:21
  SPEAKER_01: Uh so from I I do not call it wipe coding at the end, what I'm doing.
• 39:24
  SPEAKER_01: I do a lot of brief engineering, give a lot of constraints to the AI.
• 39:28
  SPEAKER_01: But yes, the AI creates a lot of code, obviously, because that's what I also want to leverage from uh agent myself.
• 39:37
  SPEAKER_00: So AC AZ is on uh GitHub.
• 39:40
  SPEAKER_00: Uh, do you have contributors from the outside already, or is it mostly people that you bugged in the office to help you out?
• 39:46
  SPEAKER_01: Yeah, currently, well, it's uh as for most open source projects, they are around uh from the personal field of the primary author.
• 39:52
  SPEAKER_01: This was already at Apache Foundation and others.
• 39:55
  SPEAKER_01: This is a classical thing.
• 39:56
  SPEAKER_01: Yeah, the the contributors of AZ are currently around my CTO organization at the MSG, uh, because they are employees, uh friends of me.
• 40:04
  SPEAKER_01: So this is well, as in all open source projects, there's one uh primary key figure that's this is me, and people in the personal or uh business uh uh yes circle or onion around this person.
• 40:16
  SPEAKER_01: So very similar also on this project because it's a rather new project, it's just uh half a year uh old.
• 40:24
  SPEAKER_00: But you do welcome pull requests and comments and yeah, sure.
• 40:27
  SPEAKER_01: It's it's fully open source, Apache licensed.
• 40:30
  SPEAKER_01: So, yes, obviously, it's fully open source.
• 40:32
  SPEAKER_01: Everything is here available, it's not uh open weight or something like this, uh, as we talked before.
• 40:38
  SPEAKER_01: It's a really a true open source project, yes.
• 40:41
  SPEAKER_00: Well, very, very cool.
• 40:42
  SPEAKER_00: Thank you so much.
• 40:43
  SPEAKER_00: This was uh insightful.
• 40:45
  SPEAKER_00: I think there's a lot of stuff that we can cover.
• 40:47
  SPEAKER_00: Uh, might be inviting you back on the live show or something, so we can talk more about how it goes, how it went.
• 40:52
  SPEAKER_00: Now, my last question when I go to the author page and I see you here, do you moonlight as a magician?
• 41:00
  SPEAKER_00: As a magician, because it does look like a picture that you actually see it in in Las Vegas somewhere where it's like tonight, it's gonna be Ralph.
• 41:10
  SPEAKER_01: Well, uh, I'm I'm actually not just an open source hacker, I'm also uh uh a guy standing on stage.
• 41:16
  SPEAKER_01: So even the picture is something like this.
• 41:19
  SPEAKER_01: Uh but and uh when it comes to software, well, perhaps it's uh magic.
• 41:22
  SPEAKER_01: I don't know.
• 41:24
  SPEAKER_01: You know, this has to be decided by others whether this is really artistic stuff I'm doing.
• 41:29
  SPEAKER_01: Uh at least uh I hope I I've contributed a lot in the open source field for the last uh well over three decades now, and perhaps something is also magic.
• 41:37
  SPEAKER_01: I don't know.
• 41:38
  SPEAKER_00: Well, talking of which image magic just had a security flaw as well that needs fixing, so that's something we need to go for now as well.
• 41:46
  SPEAKER_00: Well, this was this was delightful.
• 41:48
  SPEAKER_00: It's great to have you on board, and it's great to have you uh at the are you gonna be at the event in Berlin again as well this year, or no, I was not participating, no.
• 41:57
  SPEAKER_01: Will you come next year then?
• 41:59
  SPEAKER_01: Perhaps.
• 42:00
  SPEAKER_01: If I'm allowed it.
• 42:02
  SPEAKER_01: The problem is in the industry, your time is immediate dramatically thin what is available to go to conferences and other things because you are such uh well drawn away with customer projects and and other things.
• 42:15
  SPEAKER_01: So this is really I would like to enjoy to more get in contact with people.
• 42:19
  SPEAKER_01: So I enjoyed even the invitation here.
• 42:21
  SPEAKER_01: And if it time allows it, I can.
• 42:25
  SPEAKER_00: Well, thanks very much.
• 42:26
  SPEAKER_00: This was Dr.
• 42:26
  SPEAKER_00: Ralph Engelschall, uh S.
• 42:28
  SPEAKER_00: Engelshall, whatever that is, and uh that's my second first name, Sasha from MSG Group.
• 42:35
  SPEAKER_00: And uh, we learned today about how you can actually merge the whole idea of uh uh agentic vibe coding and really, really boring old things.
• 42:43
  SPEAKER_00: Oh, one last thing, uh OpenAI just announced that the new model that they're hiring is actually focused on uh on COBOL and Fortran to help with like fixing old banking environments.
• 42:54
  SPEAKER_00: Is this something that you face where you have like really old languages that you have to support?
• 42:59
  SPEAKER_01: We have definitely customers uh which have those old pieces in the banking and insurance field.
• 43:04
  SPEAKER_01: Yes, definitely.
• 43:05
  SPEAKER_01: So I can uh understand that OpenAI offers this particular model because uh there's certainly a large market uh to transform and migrate those old pieces of software into new eras.
• 43:16
  SPEAKER_01: And it was rather hard in the past to do it without AI.
• 43:19
  SPEAKER_01: So I even enjoyed that such specialized models came out, which can help here.
• 43:24
  SPEAKER_01: Yeah.
• 43:25
  SPEAKER_00: Yeah, because I mean freelancers that know COBOL can actually dictate their prices by now.
• 43:30
  SPEAKER_00: Like, because if something that is broken, then it's something that is very vital for the bank or for an insurance company.
• 43:36
  SPEAKER_01: Yeah, we had even people which were already retired and came back because they have this knowledge still available in their brain.
• 43:44
  SPEAKER_01: Wow.
• 43:45
  SPEAKER_00: But it was never fun to write COBOL, that was the issue with it.
• 43:48
  SPEAKER_00: But like, and on the other hand, like I mean, what's your favorite language?
• 43:53
  SPEAKER_01: My favorite language is actually TypeScript because it's uh a fantastic fusion of JavaScript and all the possibilities on the web, plus the static typing.
• 44:02
  SPEAKER_01: And uh Anders Heilsberg, which we who invented this language, has really done a great job when it comes to the typing system.
• 44:09
  SPEAKER_01: I really enjoy this typing system, the possibilities.
• 44:12
  SPEAKER_01: So TypeScript is my personal preference, and that's the reason why my open source project for the last, I don't know, five or more years are only TypeScript in Node.js based.
• 44:21
  SPEAKER_00: He does he did C sharp as well, and he was one of those people that in Microsoft I met in the cafe at Cafeteria from time to time, and I'm like, oh god, he's the guy that broke.
• 44:29
  SPEAKER_00: And he's one of the nicest people in the planet.
• 44:32
  SPEAKER_00: It's just like a really down-to-earth guy, and he's just a coder that wants to write things, and it's just wonderful to see that kind of stuff.
• 44:38
  SPEAKER_00: I was choking the other.
• 44:41
  SPEAKER_01: His results are wonderful, be it C sharp, is a great language, and the TypeScript also.
• 44:46
  SPEAKER_01: It's uh a great fusion of the world of web with JavaScript and the classical statically typed languages.
• 44:53
  SPEAKER_01: Yeah, really great.
• 44:54
  SPEAKER_00: I was jokingly saying I'm going back to Perl, so nobody can actually read my code, neither agents nor humans.
• 45:00
  SPEAKER_00: So uh we'll see how that works out.
• 45:02
  SPEAKER_01: But yeah, the good old Pearl joke, exactly.
• 45:05
  SPEAKER_01: You can what was it?
• 45:07
  SPEAKER_01: Uh you can uh base a 64 it and not recognize on the other hand.
• 45:12
  SPEAKER_01: Look like this.
• 45:14
  SPEAKER_00: Same thing, like reverse, yeah, reverse engineering is gonna be tricky.
• 45:18
  SPEAKER_00: Well, thanks very much.
• 45:20
  SPEAKER_00: Uh this was Coffee with Developers.
• 45:22
  SPEAKER_00: So uh we're gonna be on the platform soon.
• 45:24
  SPEAKER_00: And uh, if you want to learn more about it, go to the GitHub, uh, try it out, try Ace and see if it actually works for your environment.
• 45:30
  SPEAKER_00: I love that you also have a like why is it for you and why is it not for you?
• 45:34
  SPEAKER_00: This is also a very good thing to get people to filter them out without uh so they're not uh actually disappointed by it.
• 45:40
  SPEAKER_00: So that's a wonderful thing.
• 45:42
  SPEAKER_00: So go and try it out, and that was it from us.
• 45:44
  SPEAKER_00: Thanks very much.
• 45:46
  SPEAKER_00: Thanks for the invitation.