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Why stories about "escaped" models keep appearing, what red teaming and ARA tests actually measure, and which problems are left outside the ring.

Why models produce excessive solutions by default, which natural brake on complexity disappeared, and how to use AI as an editor rather than a generator.

Why some companies take losses while others grow exponentially: a breakdown with examples from Shopify, Meta, Klarna, Duolingo, and others.

How honest dialogues with AI became a gift for corporations, and why the thinking should stay with the person while the routine goes to the model.

From a bitter late Soviet saying to corporations hunting for engineers, and to the new question raised by AI.

A protocol for working with several AI models as researcher, critic, and editor without outsourcing the thinking.

How TRIZ helps Samsung, Intel, and other companies identify contradictions, improve products, and solve complex problems systematically.

Sometimes a solution is perfectly logical, yet it fails because it never addresses the real problem. A look at why we solve the wrong task and how to see it more clearly.

A simple explanation of electricity through bicycles, water pressure, and an old sewing machine.

On AI costs, the limits of automation, and why effective AI use is becoming the new professional standard.

On writing, research, doubt, and conversation with artificial intelligence.

Why agentic AI systems need verifiable, time bound, action level access control.

A vision for a global trusted-contact network where people, specialists, and companies can be discovered through private trust paths.

Why knowledge is no longer the main advantage in the AI era.