At Kondana, we’ve been experimenting with AI across our workflows, and the shift has been significant. The way we build, and release products looks very different today compared to even a year ago.
Shipping faster with leaner teams
The most obvious change is speed. UI updates that used to take weeks now move to production in a matter of days. Turning an idea on a whiteboard into a working proof of concept is no longer a long cycle. What stands out is that we’re able to achieve this pace with a lean team. AI reduces the manual lift, which means the team can focus on the parts of the product that really matter.
The changing role of developers
For developers, AI has changed the nature of the work. Less time is spent writing repetitive code. More time goes into what we call second order thinking: deciding the right architecture, shaping the roadmap, improving user experience, and optimizing resources.
The boundaries of a developer’s role are shifting. A developer today is not only coding but also thinking like a product manager and an architect. With AI, it’s possible to pick up new technologies quickly. You don’t need to master a programming language before using it effectively. Instead, you choose the right tool for the job and let AI accelerate the execution.
Shifting customer expectations
We’ve also noticed a change on the customer side. There’s growing interest in AI-driven solutions, and more conversations are moving toward outcome-based pricing. The understanding is that small teams can now deliver faster with AI, and ongoing support can in some cases be handled by AI agents.
But there’s also work to do in terms of customer education. AI is not a magic shortcut. It has strengths and limitations, and setting the right expectations is essential for adoption.
AI is evolving rapidly
Finally, the technology itself is improving at an incredible pace. The quality of AI-generated code is better, and developers spend less time cleaning it up. At Kondana, we built a reporting chatbot for Yali in a very short time, something that would have required more resources not long ago. (You can read more about how we built it [here].) Projects like this highlight how quickly the possibilities are expanding.
Looking ahead
For us, the takeaway is straightforward. AI is not only about efficiency. It’s changing how teams are structured, how developers approach their work, and how customers think about value. In the near term, the most effective approach will be AI working alongside people. AI can handle speed and scale, while people bring context and direction. The combination creates results that are both faster and more relevant. The shift is already here, and at Kondana we’re adapting by building products and processes around this new reality.