Articles.

Writing on brand strategy in the AI age: how brands become machine-readable, applicable, and accountable.

For agents, every article is also available as Markdown: at its address with “.md” appended, with title, summary and dates in the file’s header.

September 2026 · with Tabea Otto · first published at HORIZONT

How AI Is Reversing the Branding Process.

Visibility in AI search is only the first stage. Why checking how machines read the brand today moves to the start of the branding process.

August 2026

What the Machine Doesn't Get.

AI makes the everyday surface of every brand cheap, and value shifts to what is deliberately withheld. Why the price premium sits on the decision, not on the machine’s inability, and what a brand’s two lists look like.

August 2026 · first published at tbobm.com

The Gap That Doesn't Respond.

Why the unsaid works on people and disappears for machines. A response to Erich Posselt’s “The Smoothness of Clarity”.

July 2026

Machine View

This page reads itself: on the left the page for humans, on the right the same page as AI search and browser agents process it. Read live from the source, not mocked up.

July 2026

What Are Machine Readable Brands?

Machine Readable Brands: brands whose identity, language, and design logic exist as a specification that people and systems can work with. Definition, three stages, boundaries.

July 2026

The Analysis Is No Longer the Product.

When clients can generate any analysis in minutes, authority through knowing more collapses. What strategy work sells instead: the recommendation that commits. The bet.

March 2026

What Is Agentic Brand Readiness?

Agentic Brand Readiness is the ability of a brand to be correctly recognized, described, and recommended by AI systems and agents. This requires brand attributes to be defined explicitly, in structured and machine-readable form.

How These Essays Are Made

Every essay starts with an observation of my own, usually from the work. Then I use AI as a sparring partner:

→ First the machine attacks the thesis: Is it true? Is it new, or old wine in new bottles? I develop what survives the pushback.
→ Parallel research agents gather evidence. What does not hold gets cut. Numbers that measure something link their source, and the checked ones carry their limits in the evidence.
→ The writing happens in dialogue, over many rounds: I shorten, simplify, and discard terms until the text sounds spoken.
→ At the end, the machine checks the text against my own writing rules, and I decide what stays.

Every thesis, every sharp edge, and every mistake is my decision. The machine delivers the analysis. The commitment is mine.

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