The first real PLN 2
Twój Sklep PLAPP completed its first controlled end-to-end transaction in the live TwojButik store.
Lesson learned: Do not test only features. Test the whole business process.
Building PLAPP
The story of building PLAPP
We do not document every change. We keep the moments that changed the product, the process or the way we think about what we are building.
Automation is easier than trust
The more a system can do independently, the more important it becomes to define where it should stop.
Lesson learned: Mature automation includes knowing when the system should not act alone.
Humans should not be the transport layer
Automation should remove mechanical coordination work while keeping people at the points where judgment creates value.
Lesson learned: Remove coordination work, not responsibility.
The project should remember
As PLAPP projects grew, the memory of earlier decisions, failed attempts and lessons learned became increasingly important.
Lesson learned: Good human–AI collaboration needs a process that can use previous experience.
Fuller story on LinkedIn ↗A dashboard should tell you what to do
We decided that a small-business owner does not need ten more charts. The workspace should show what needs attention and why.
Lesson learned: A good dashboard supports a decision instead of creating another analytical task.
The first store backend goes live
The backend of the first PLAPP Commerce deployment started running in production.
Lesson learned: A demo proves possibility. Production starts answering whether the system can be relied upon.
Fuller story on LinkedIn ↗“Great tool.” And almost nobody used it.
One of our early AI agents received very positive beta feedback, but later barely entered the tester's normal workflow.
Lesson learned: Positive feedback is not the same as product adoption.
Fuller story on LinkedIn ↗PLAPP leaves the workshop
PLAPP started around a simple principle: technology should adapt to the needs of the business, not the other way around.
Lesson learned: Technology is useful when it removes work rather than displaying its own complexity.