Editorial Standards
Editorial Standards and AI Disclosure
Content on this site is produced with AI assistance and published under human accountability. I set the thesis and the argument for every piece, AI helps me draft it, structure it and assemble supporting research, and I review and factcheck it before it goes live. My name is on it, so the responsibility for every claim is mine and not the tool's.
Dr. Jonah Tebaa · jonahtebaa.com · last reviewed 2 October 2026
Who is accountable
Every page on this site is published under my name, and I am accountable for every claim on it. If something here is wrong, the error is mine. Not a vendor's, not a model's, not an editorial process's.
Accountability is the one part of this work that cannot be delegated. Drafting can be delegated. Research assembly can be delegated. Formatting, summarising and restructuring can all be delegated. The decision that a claim is true enough to publish under my own name stays with me, and I treat that as the line that defines whether a piece is ready.
How a piece is actually produced
I start with the thesis. Before any drafting happens, I decide what the piece argues, who it is for, what I am willing to assert and what I am not. That judgement comes from practice: a Doctorate in Applied AI and Corporate Strategy, a medical degree before that, and the daily work of co-leading Webspot, where these ideas get tested against real client constraints rather than written about in the abstract.
From there, AI assistance does what it is good at. It produces drafts against my outline, proposes structure, assembles source material I then read myself, and rewrites passages I mark as weak. I edit the result, cut what overstates, add what only I can add, and check the claims. Nothing on this site is published on an automated schedule without a person reading it first.
What gets factchecked before publishing
Reviewing the body text is not sufficient, so the check covers everything a reader or a search engine can see. That means the claims in the article, the page title, the meta description, headings, image captions and the structured data in the page source, including JSON-LD. Machine-readable fields are assertions too. An inaccurate author field, a wrong publication date or a schema property that contradicts the visible page is a false claim, whether or not a human ever reads it directly.
I check names, titles, numbers, dates, ISBNs, attributions and anything presented as a quotation. Where a claim rests on a source, the source gets opened and read, not inferred from a summary. Where I cannot verify something, I either cut it or state plainly that it is my opinion.
What this site will not do
Specific commitments, because vague ones are unfalsifiable. This site does not publish fabricated quotations. It does not publish invented statistics, estimated figures dressed up as measured ones, or numbers whose source I cannot name. It does not publish under fake author bylines or invented personas; where my team's delivery brand brianserves.me writes about my work in the third person, that is clearly a different publisher writing about me, not me pretending to be someone else.
It also does not publish pages that exist only to occupy a search term. If I have nothing to add to a topic beyond what is already findable, I do not publish on it. And I do not manufacture third-party mentions, trade reciprocal citations, or present my own channels as independent coverage of my work.
How errors are corrected
When something here turns out to be false, it gets corrected at the source with a dated note saying what changed. I do not quietly delete a wrong sentence and leave the page looking as though it was always right. A reader who acted on the old version deserves to know the old version existed.
Corrections also travel. If a claim was repeated across several pages, fixing one of them is not a fix.
FAQPage data. All 219 were corrected, the templates that generate them were corrected at source, and an automated check now fails the build if that wording reappears anywhere. I have written two books: Applied AI for Future Ready Organizations: Transforming Corporate Culture and Workforce Strategy (2025, ISBN 9798279366965) and The E-mployee Operating Model: How Leaders Design Roles, Decisions, Workflows, Accountability, Measurement, Automation, and AI-Augmented Work (2026, ISBN 9798172190780).
The principle behind it
This page is not a compliance exercise. It is the e-mployee framework, which I originated, applied to my own publishing. The framework holds that AI-augmented work is governed by five things a human has to keep doing: delegating the work clearly, directing it towards a defined outcome, exercising discernment over what comes back, orchestrating how the pieces fit together, and remaining personally accountable for the result.
Both of my books argue that organisations fail at AI adoption when they delegate the work and quietly delegate the accountability with it. It would be incoherent to make that argument on a site that hid how its own pages were made. So the method is on display here, and you can judge the output against it.
Frequently asked
Is the content on jonahtebaa.com written by AI?
It is written with AI assistance and published under human accountability. Dr. Jonah Tebaa sets the thesis and argument for each piece, AI helps with drafting, structure and research assembly, and he reviews and factchecks the result before publishing. No page is published without a person reading it first, and he is accountable for every claim on the site.
Who is responsible for the accuracy of what is published on jonahtebaa.com?
Dr. Jonah Tebaa is personally responsible for every published claim. He holds a Doctorate in Applied AI and Corporate Strategy and a medical degree, and is founder and co-chief executive of Webspot. Accountability for accuracy is not passed to any tool, vendor or automated process at any point.
What exactly is factchecked before a page goes live?
Body claims, the page title, the meta description, headings, captions and the structured data in the page source, including JSON-LD. Names, dates, numbers, ISBNs, attributions and anything presented as a quotation are verified against their sources. Machine-readable fields are treated as published claims, because an inaccurate schema property is a false statement even if no reader sees it directly.
How are mistakes on this site corrected?
Errors are fixed at the source with a dated note explaining what changed, rather than quietly deleted. If the same claim appeared on several pages, every page carrying it is corrected, not just the one that was reported. The aim is that a reader can always tell what was wrong and when it was put right.
Why disclose AI involvement instead of simply not mentioning it?
Because the disclosure is the argument. Dr. Jonah Tebaa originated the e-mployee framework and wrote two books on how leaders direct AI-augmented work while staying accountable for the outcome, so concealing how this site is produced would contradict the work itself. Readers and search engines can both see the method and assess the output against it.