On Building AI-Powered Products
When I started writing this post, I was on a sick leave and decided to write one post to make the most out of that time. Here I am after two weeks of delaying it, finally bringing it to an end. It is more of a generic and semi-unstructured collection of thoughts on my 2025 experience building AI-powered products and a few tangent thoughts.
AI Unlocks Orders of Magnitude
Any AI feature we developed increased the user productivity. It is the same efficiency increase when we got calculators for complex calculations, or the way Quantum Computers arguably will change the speed of computation radically.
AI is not just a new computer, new phone, or a new car. It is the first computer, the first phone or the very first car ever developed.
Intelligence and generative capability transforms how we approach the problems. Image generation is becoming so advanced that one does not need any photoshop skill, or someone with that skill. Code-writing is another example. My sales colleagues develop prototypes in a matter of an hour and showcase how they’d envision to see the product working. It was never ever possible before.
The AI Excitement Asymmetry
On the one side, there is a high visibility of AI everywhere. All platforms, news, websites, products bombard people with AI marketing. On the other hand, those ads do not turn into the actual value generation. We are trying to build it in-house, but it does not bring the same level of excitement. “But ChatGPT is faster” is what we got as a feedback.
AI as a Feature
In an enterprise setting, the most optimal usage of the AI product that we’d developed was not a standalone product. It was rather an integrated feature within workflows. In general my main product hack is to have it as part of my usual routine. Instead of opening another link to do the job, I’d rather want to have it as a tool within my current workflow. Our users also have this same expectation. Someone asked me one day, cannot we integrate the smart.AI into the excel? then I can give my prompt there and it’d do the job. Someone else mentioned it would be great if smart.AI can record my meetings (regardles online or onsite) and provide a summary to me, directly on my laptop. Another project I built for my own was an intelligent file manager. I developed a standalone user interface to talk to my files, organize them, and do some actions on them. I know that it’d be even better if Apple would’ve had it natively integrated as part of their “Apple Intelligence”, then I’d not need an extra application on Docker to manage my files. Here my main takeaway is that AI would work better as a feature within the product, and not just another standalone tool.
AI development at a lightning speed
It is crazy how fast the industry is moving. Every week there is a new model, new method, new tool, new idea made public that changes how we use AI. It signals how broad and robust the AI ecosystem will become. At the same time, many of the developments are half-baked, incomplete, dangerous to use, and before they can be matured the next hype begins and gets all the attention. I do not consider myself to be the most up-to-date person, neither do I want to be one. I adopted Claude Code very lately, and I am happy about it because the product feels very mature in comparison to what people were writing about it at the beginning. Now there are skills to learn. It can become very overwhelming if one digs deeper and faster. I take it steady and easy.
Even more AI in 2026
I am excited about the next year. As AI becomes a part of our daily tool stack, we will see even more applications for it. With the maturity of coding assistants (like Claude Code), we will be able to turn our ideas into actual products (check the ClaudeAI subreddit for the apps built with Claude Code).
