Explore the dynamic software development landscape through four compelling scenarios that envision the industry's future. This talk delves into emerging technologies, evolving methodologies, and the shifting demands of the digital age, aiming to spark a thought-provoking discussion on navigating and shaping tomorrow's software world.
Speakers
Marko Klemetti
AI
CTO of Eficode
Marko leads Eficode’s technical direction, helping organizations turn AI from isolated experimentation into a scalable software delivery capability. As CTO, he has shaped the company’s engineering approach from its earliest days and developed the framework Eficode uses to guide AI-native transformation. He writes and speaks regularly on the future of software development, with a focus on the practices that enable faster, more effective delivery.
Henri Hämäläinen
Henri brings extensive C-level leadership to the software business. As the Chief Product Officer at Eficode, he leads global strategy and connects technology with concrete business value. Recognized as an industry thought leader, he created the AI maturity model and the three-portfolio model. Drawing on his background in coaching winning product organizations, Henri implements straightforward processes and structures to help companies build better software.
Transcript
[Marko:] Once again, thank you for being here, also from my behalf, and then... - [Henri:] Thank you from my behalf also. Perfect. Today, we've decided also to go the direction of AI-generated imagery. And the first one to show is generated... Just kidding. So, it's funny that Bill Gates, when he released his book in 1996, he wrote there that we overestimate the change that will occur in the next two years, but always underestimate the change that will occur in 10. And today, we are trying to give some ideas and visions of the future of software development combined with the explanations from me and Henkka. But also, I'm going to try to live code some. We'll see how far that takes us. Would you like to..? - [Henri:] Yes, thank you. So, the idea that we had is actually to walk you through four different steps to the scenario, which we see as a thing that will happen, in, let's say, around 10 years all in all. So, the first scenario is something that is happening already. You most probably know, actually taking AI-assisted software into use. Then, the second scenario will be around putting the things together, actually using AI for legacy things. Then, the third is about using AI for business requirements, and then generating software based on these. And then, the fourth one, which we will discuss a bit more later, is about self-developing software. So, how do you actually maybe take the step towards that customers can develop the software themselves with certain limitations. But we'll come back to that one, we'll build the storyline, we'll show some Marko's magic here in the way. So, please be actively participating here. [Marko:] Okay, let's start with the first one. So, AI-assisted software development, where we are currently. And I actually would like to include every one of you into this. So, please take out your phones and type in, you can either type in future.hopefully.works, or you can scan the QR code. There will be a yes-or-no question. The question is, we already deploy AI generated code to production regularly. To production. Not only just using AI, but actually going to production. We're going to wait for a few minutes. [Henri:] So, it seems that there are quite a few people who are already deploying AI-generated code to production, which is a surprise. I hope you are actually doing it and not just stating. But it's nice to see so many of you actually using it already. [Marko:] More than half. - More than half. [Marko:] And I would say that Finland works as a prime example of this, because... - Yeah, I think what always happens on technology adaptations like this, if you ask developers, 97% of developers say they are using AI, they've actually used AI for development. Then, when you ask managers, managers say 42% of companies actually use AI for their software development. Then, when we go to the actual value streams or workflows, there's 11% who genuinely use it for their software development. So, it showcases the complexity of things, but also, how it normally goes. There are these individuals who take it into use, and it's so cool that we definitely want to say we are using, but then the reality is something different. And if we go to the next slide, so technology adaptation curve, most of you know this, innovators, early adapters, those are the ones that are actually the easy parts, and then, there are the early maturity, late maturity and laggards, like with every technology, the same happens with AI and generative AI tools. And what we have seen with organisations, it is really easy to get for innovators and early adopters the tools into use, because you just give it to them, and they [chuckles] start to use it. Then, when we get to the majority, late majority or even laggards, you have to do real transformation programs to get them to use the AI properly. So, this is a learning which I hope you will get from this today, even though...
- DevOps
- Product development
- AI
- Conference talks
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