No Contradictions
A text does not have to be perfect. It has to hold one line: it must not contradict itself, and it must not say anything untrue.
Research Journal
Field notes from ongoing work in semantic authenticity — human–algorithm and human–human alike.
#semantic-authenticity
#case-study
#life-prism
#platform-analysis
#algorithmic-communication
#methodology
Who Is Asking, Who Is Answering?
The company where I work has just launched a site for an American audience. On 4 November I opened it and stopped, within a minute, at the FAQ block. Six questions. The fourth one reads: "How fast will I see results?"
The Word That Stood Out
In one project where I work on content, the client chats in Telegram carry everything at once: edits to articles, questions about the client's website, access to accounts, call times.
What to Check After You Have Admired the Facade
I built a listings site in one day. Photos, several languages, a language switcher, a clean layout. It looked finished.
The Answer Was in the First Reply
A shop, mobile traffic, and customers who screenshot the product card and send it on WhatsApp instead of ordering. The question put to a model was how to stop the screenshots.
Where the Corrections Used to Go
A three-sentence advertisement for a restaurant, Russian into Turkish, December 2025. The Russian reads: we make any sushi cake you like, from 1500 lira a kilo, order 24 hours ahead. Eleven words in the professional Turkish version.
Two Ways to Stop Someone
Ran into both sides of the same interface pattern in one day, which is the only reason the comparison is worth writing down.
The Notes Field Nobody Reads
Tom yam is a hot soup. That is the dish, not a defect in it. Customers kept typing “not spicy” into the order notes anyway.
One Declaration, Two Readers
Structured data is a declaration: this is who we are, this is where, this is what we sell. The framework says to make it plainly and let the algorithm read it.
Naive Parsing, Human and Machine
A production incident and a content review landed in the same week, and they turned out to be the same bug wearing different clothes.
The Expert's Vocabulary Problem
Spent a month building content for a client who is, herself, an experienced marketer — reasonably assuming that her own vocabulary would transfer directly to content for her audience. It didn't.