Concepts
Each concept is one thought brought to understanding. No required order: you can start with any.
Surprise as the Detection of a Meaningful System Deviation
Surprise can be viewed as the ability to notice a meaningful deviation of a system's actual state from its expected state. Its strength depends not only on the magnitude of the change, but also on how this change affects the system itself.
Learning to read as restoring connections between known content and the written code
A testable theory of reading instruction: a child masters writing more easily when the written code is systematically connected to words, images, meanings, sounds, and language structures they already know.
The Known as a Tool for Investigating the Unknown
New understanding is not built from a vacuum: elements, connections, and abilities already familiar to a person can be used as tools to reconstruct and master the unknown.
Progress arises from the reuse of known connections
Progress occurs when already known connections, methods, and systems are transferred, inverted, combined, and applied outside their original context to create new opportunities.
Systems Thinking
In our concept, systems thinking is a way of viewing objects, knowledge, skills, and processes as systems: understanding their internal structure, capabilities, needs, boundaries of applicability, and interactions, and choosing a sufficient depth of analysis for a specific task.
Concept
A concept is a holistic information unit. It can be simple or complex, but it must always retain a single independent content that can be expanded through simpler concepts if necessary.
First learn to solve any problem, then learn to solve it faster
Learning often starts with names, special cases, and ready-made formulas. A student memorizes many efficient solutions, but remains helpless when faced with a problem that doesn't resemble the ones they've studied. It is more reliable to first master a minimal universal toolkit applicable to the entire class of objects, and then derive regularities, short formulas, and specialized methods from it as ways to speed up an already understood solution.
Polygons should be studied from general methods to specific names
School geometry often begins with the names of shapes and lists of their properties. A child learns to recognize a square, a rhombus, and a trapezoid, but may not realize that the name is merely a shorthand for already established constraints. One can start with an arbitrary polygon, learn to measure sides and angles, find the area, check for parallelism, and discover patterns—and only then introduce names and special formulas as convenient abbreviations.
In the world of AI, choosing the right profession matters less than learning how to constantly find yourself a new one
We are used to choosing a profession as if there is a place out there that suits us, which we just need to find and occupy one day. But AI is making learning, product creation, and idea testing cheaper, while economic opportunities themselves emerge and disappear faster than ever. Perhaps the main advantage is no longer a chosen specialty, but the ability to understand again and again where you can be useful, quickly build what is missing, and move on to the next opportunity.
The main mistake in communication is assuming understanding has been reached too early
People and AIs constantly reconstruct the meaning of what is said based on their own experience. Usually, this is useful—otherwise, any communication would take hours. But the less shared context there is between speakers, the higher the probability that one is already sure they understand everything, even though the other was talking about something completely different.
Learn to understand the world in your own words, not memorize others'
You can know all the right words and understand nothing at all. Or you can deeply understand something without even knowing what it's called. For the first time, modern AI allows us to learn without forcing our language to adapt beforehand to the language of textbooks, specialists, and search engines. It's enough to start with what you already see, understand, and want to know.
Humanity has learned to create knowledge, but has not learned to transmit understanding
The volume of human knowledge is growing faster than the individual's ability to master it. Every field compresses complex models into its own terms and assumes more and more background knowledge. As a result, information becomes more accessible, but understanding does not. For the first time, AI makes it possible to abandon the universal method of explanation: the exact same idea can be dynamically recoded through a specific person's existing concepts, filling in only the minimally necessary gaps.