Between small gestures and large systems.

Kvantliblikas grew from the observation that work rarely changes because of one large reform. Change often begins with an almost invisible shift: one decision, one meeting, one differently worded task, or the first time someone asks an agent a better question.

That is why the butterfly effect matters to me: complex systems can be sensitive to small initial conditions. In organisations this is not poetic exaggeration but an everyday leadership question. When information moves differently, when responsibility shifts, when a tool starts participating in thought, tempo, quality, courage, and even people’s sense of what is possible begin to change.

Maria Kiisküla, founder of Mustkriit, brings service design and a careful reading of human experience into Kvantliblikas. Her work starts from what a person actually experiences: where a client, employee, or user gets stuck, which problem is still unnamed, and what should be tested at a smaller scale before a bigger development effort or change programme begins.

The quantum metaphors are not decoration here. Before a decision, work is often in a kind of superposition: the old routine still works, the new way of working is already pressing in, and neither state tells the whole truth on its own. The training task is to make that condition visible and choose the next experiment responsibly.

My background is in making sense of the future of work, AI agents, and organisational change; Maria’s strength is a slower and more precise reading of people, services, and experience. Together we design trainings where we do not jump straight to solutions. First we need to notice for whom the change is happening, what behaviour it really affects, and how to structure the first experiment so there is something real to learn from.

Working with agents amplifies that butterfly effect. A small prompt, a vague assumption, or thoughtless access can start replicating confusion; a well-framed task, a checkpoint, and good taste can give a team new working capacity. Kvantliblikas does not treat AI as a trick but as a new participant in the work process: the human keeps responsibility, direction, and meaning, while the agent helps explore, structure, and play scenarios through.

How we work

We start by mapping the situation: not only what is written on a process diagram, but where people actually hesitate, rush, stay silent, or invent side paths. From there grows a training or workshop that is clear enough for an enterprise leader and alive enough for a boutique team that values art, attention, and a slower pace of life.