In this talk, Marko Klemetti discusses the challenges organizations face when adopting AI-driven development and modern DevOps practices. He highlights why these transformations often struggle to scale and shares case studies that provide practical insights and a roadmap for successful integration of new technologies.
Speakers
Marko Klemetti
AI
CTO of Eficode
Marko is the CTO of Eficode, a European DevOps and Design house. He is also a founder and advisor in many tech startups. Marko is a passionate programmer who believes that design systems and continuous deployment are the enablers of a modern development organization.
Transcript
Thank you, thank you everybody. I'll start with a claim: I will claim that developer experience and AI-driven development are the two key initiatives for the future of software development. Currently, we are in a place where we try to push both from different directions. We have AI-driven development helping us with the development and then the developer experience platform engineering pushing from the operation side. We've gotten to a point where a dear colleague of mine, Yan, said, 'Why do we use AI-driven development to write code to tell stupid computers what they should be doing?' We already know that where we are at the point with development is indeed helping us write code for itself or stupid computers, and this is due to change in the future. AI-driven development will push us to automate beyond our current imagination, and I see that in the same way platform engineering and developer experience will do from the other direction.
Allow me to demonstrate. I always say when doing any live sessions or live coding, I fail alone, but today we can succeed together. I've created an application template; it was a super grim weekend in Finland, rainy and slushy. I had my morning coffee, and I hadn't been coding for a while, so I decided to code something for my presentation. I made a React application template to show what platform engineering could be and how AI-driven development helps there. The code itself is relatively simple; I've only used AI to generate it, and I'd love to walk you through more code live.
I borrowed from TV2; last spring in London, we were on stage with Emma talking about TV2's platform engineering. They made a CLI, and I also wrote a CLI called T do CLI. It creates a project, and I'm using the template React application. Let's create a project called Copenhagen T dock. It creates a repository based on the template, clones it, and creates a project in Vercel. If you haven't used Vercel, I encourage you to because it's showing the way where you should be going with developer platforms.
So it created Copenhagen T dock, and let's open the link. Oh no, deployment not found. This is the worst moment because currently, only I can fail. But let's refresh... I have a page! Using platform engineering, starting from a template, releasing an application to domain T do. Hopefully, that works now. You can scan the QR code or go to T do. Hopefully, it works. Amazing! You can already see I was trying to think which side it should be so that it would end up correctly.
For those who don't know, developer experience is the overall experience developers have about their work. There are four things I want to share with you. The first one is usually the benefits might be somewhere else than you thought. If you only send surveys, look at door metrics, or check the co-pilot API, you might not see the big picture of what these concepts of tooling bring.
The second key thing is to make these ways of working easier to use than the alternatives. Continuous integration is a super good example; once implemented, you never want to go back to manual building. The same kind of working applies here as well, whether it's AI development or platform engineering.
The third point is about the technology adoption curve. The innovators are easy; the bigger the organization, the more people have already solved these problems for themselves. Making it centralized only serves that group unless you make a big change within the organization. It's easier said than done, but you need to balance autonomy and standardization.
Lastly, if you're not making it mandatory for the organization, you have to find a way to make it mandatory. This change will not happen by itself. If you build AI-driven development and platform engineering within the organization in such a way that you're never surprised, then you've done something wrong. Thank you!
- DevOps
- Conference talks
- AI
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