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AI is becoming a familiar tool for marketing teams, but the real challenge is not just “being able to use AI” — it is “using AI in the right way for yourself.” For Vietnamese marketers, preserving brand voice, hands-on experience, and a distinct line of reasoning is the deciding factor in ensuring AI-assisted content still delivers real value.
The article below summarizes new guidance from Social Media Examiner on how to turn meeting transcripts, interviews, and everyday conversations into a “cognitive profile” that helps AI learn how you think, write, and work.
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Key points:
- Instead of only answering an interview about working style, use real conversation data so AI can better understand how you think.
- “Cognitive fingerprint” emphasizes extracting patterns of reasoning, priorities, and reactions in real situations, not just surface-level descriptions.
- The goal is not to replace experts, but to replicate expert voice in order to scale content production and decision-making.
- This approach is especially useful for marketers, creative professionals, and leaders who want AI to accurately reflect personal or brand identity.
Why old-style AI interviews are not enough to “learn” people
Social Media Examiner says the common way to personalize AI today is to ask the model to “interview” the user and then synthesize the answers into context. This works at a basic level, but it is easily limited because it only captures what users can consciously articulate within a predefined set of questions.
For marketers, that means AI may grasp a few principles such as the desired tone of voice or some preferences for article structure, but it can still miss how real people weigh data, handle contradictions, and make decisions under pressure. In other words, the “soul” of expertise often lies outside prepared answers.
According to the source, the new approach proposed by Max Bernstein is to view AI as a tool that can learn traces of thinking from real-world data rather than just hearing descriptions of the user. This is an important difference when businesses want AI not only to write with correct grammar, but also to reflect the way professionals actually think.
“Cognitive fingerprint”: capturing a thinking signature from real transcripts
The focus of the article is the concept of a “cognitive fingerprint” — a cognitive profile built from conversation snippets, internal meetings, project discussions, and everyday decision-making situations. Instead of asking “how do you like to write?”, this method tries to observe “how are you actually thinking while working?”
The value of transcripts is that they record how experts ask questions, how they challenge ideas, what they prioritize over alternatives, and how they explain complex ideas to others. This data is far richer in context than a short description of personal style.
The article emphasizes that AI will be more effective when “fed” with authentic conversational evidence, because the model can then recognize recurring thinking patterns. For marketers, that could be the way a marketing director evaluates campaign performance, how a copywriter chooses an angle, or how a social media specialist handles negative feedback.
From transcripts to an AI profile: the value lies in recreating how work gets done
Rather than stopping at creating a persona that “writes like you,” the approach in the source guides AI toward recreating the full thinking and operating process. This is especially important for complex work, where output quality depends not only on wording but also on the logic behind each decision.
For marketing teams, a properly trained AI system can support multiple layers of work: drafting content in the right brand voice, summarizing meetings, extracting insights from internal discussions, or suggesting execution directions that fit the way leaders and teams usually evaluate options.
Even so, the article also shows that the goal is not to create a perfect copy that replaces humans. On the contrary, AI should be seen as a layer that amplifies expertise, helping what you already do well become more consistent and scalable. This is something businesses should keep in mind when building AI workflows for content and operations.
A perspective for the Vietnamese market
For Vietnamese marketers, the idea of training AI from transcripts can be applied immediately to familiar tasks such as campaign meetings, content brainstorming, monthly reviews, or recorded conversations with clients. If stored and processed with discipline, these data points can become a valuable input source for building AI that “speaks like your team.”
What matters is that transcript quality, privacy, and content approval processes must be tightly controlled. Do not put all internal data into a model indiscriminately; instead, businesses should select passages that clearly reflect thinking, standardize how questions are asked, and define boundaries for sensitive information.
As many brands in Vietnam use AI to speed up content production, this method can help reduce the problem of “AI writing like a robot” or drifting away from brand voice. If implemented correctly, AI will not only create articles faster but also help preserve the team’s distinct identity — something that is increasingly important as social media content becomes more saturated.
Source: Social Media Examiner, article “How to Train AI to Think Like You” (14/07/2026).
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This article focuses on personalized AI training with a perspective for the Vietnamese market.
