The Platform Already Has Your AI Twin

An advert scrolled past me last week for a platform called viaMe.ai. Upload your voice and your client work, it said, and an AI twin trained on you will answer enquiries while you sleep. JOBYAS.AI makes the same pitch under a different name. It markets itself as the first marketplace where professionals build a twin that sells their services around the clock. The categories run to a hundred, from accountant to architect. viame jobyas In both cases, the promise is the same. 2026 is finally the year you own your professional identity as a product you control.

LinkedIn and Meta already built that twin, in the same breath as the marketplace pitch. Not as a side project. As a billed feature, built from the posts, profiles, and comments members supplied under a setting almost nobody read. Outside a few designated privacy regions, that setting was switched on by default, months before either marketplace existed. A platform, in this sense, is the company that hosts your professional content. It decides the terms on which that content gets trained on, queried, or resold as a feature. An AI twin is a model built from a specific person's content and voice. That is exactly what LinkedIn's writing tools and hiring products already are. No marketplace matches that scale.

They Already Have the Corpus

The advice to post consistently and build your brand is not wrong. It is incomplete, in a way that benefits one side of the relationship far more than the other. LinkedIn's help pages describe a setting called Data for Generative AI Improvement. It is switched on by default for members outside the EU, EEA, Switzerland, and the UK. It trains generative models on your profile data and on the posts, comments, and articles you publish. You have to find the toggle yourself if you want it off. linkedin-help-gai USA Today reported the same mechanism within days of its 2024 rollout. LinkedIn opted members outside those designated regions in without asking them first. The fix was a setting buried under Data Privacy. Nobody had put the question to them first. usatoday-linkedin-ai

Meta runs the identical play at a larger scale. From April 2025, Meta began training its generative models on public posts, comments, and photo captions. Adults in the EU had already shared that material. meta-europeans Meta also used their conversations with Meta AI. It notified members afterwards and offered an objection form. It did not ask first. reuters-meta-eu It is the same loop I traced through the thumb-to-ledger economics of a feed. That feed predicts, ranks, and retrains on attention it did not have to bid for. The ledger there was your scroll time. The ledger here is your CV.

The Second Harvest

Open LinkedIn's Premium tier and click Write with AI on your own About section. The assistant drafts a personalised summary. LinkedIn says it incorporates insights from analysing millions of top LinkedIn profiles. linkedin-write-ai Your profile is one of the millions feeding someone else's suggested paragraph. Their profile is feeding yours. Nobody asked either of you a separate question before the pooling started. The tool does not tell you whose sentences it borrowed to write yours, and there is no way to ask it.

That pooled corpus is not a hobby project sitting quietly in a lab. In late April 2026, Reuters reported that LinkedIn's agentic AI hiring products were on track to generate $450 million in sales in the coming year. Reuters put the network at more than one billion members. reuters-linkedin-agents That is the same registry logic behind Meta buying the AI agent directory that mattered before most builders noticed the window had closed. There, the directory was agents. Here, the directory is every profile you have ever filled in. An assistant reads it for whoever pays the seat fee, not for you.

Answer Engines Do Not Send Invoices

I nearly used Write with AI on my own About section. I opened the tool and read the first draft it offered. Then I closed it, because the sentence it produced sounded like every other consultant's profile trained on the same millions, mine included. I still catch myself, most weeks, drafting a new idea as a LinkedIn carousel before I write the longform version on my own site. The carousel gets read that afternoon. The essay does not, and I know exactly why I reach for the faster feed when a deadline is close.

That habit has a cost I do not personally pay. Somewhere in LinkedIn's hiring pipeline is a candidate I will call Tunde. His profile was one of the 62 per cent fewer profiles a recruiter had to review by hand, after that recruiter switched on Hiring Assistant. LinkedIn says the same tool saves four hours per open role. It lifts InMail acceptance by 69 per cent. linkedin-hiring-assistant Tunde never sees the sub-agent's read of him. He never gets a citation for the paragraph it wrote about his fit for the role. He is not the customer LinkedIn is billing for that efficiency. The recruiter is. The recruiter's employer pays an invoice Tunde never even learns exists.

The Flat You Improved

Picture a flat you rent, not own. You spend a fortnight of evenings on it anyway. You fill the cracks, sand the skirting, paint the kitchen a colour the landlord would never have chosen for it. Your knuckles carry the small cuts from the Stanley knife for a week afterwards, a receipt for effort that nobody records anywhere official.

Then you move out. The landlord relists the flat as recently renovated and raises the rent by a fifth. Your fortnight of evenings became somebody else's asking price, and the new tenant will never learn your name. The receipts belong to the person who owned the walls, not the person who held the paintbrush. Caring about the paint job does not change whose name is on the deed.

The Strongest Case for Posting Where the Room Already Is

Give the objection its full weight before answering it. LinkedIn has more than one billion members. My own site runs a grounded answer surface, Ask. It sees roughly five hundred sessions a month by my own published account. Search Finds Pages. Chat Finds Answers. Reach is a genuine advantage, not a rhetorical one. An unread retrieval layer with perfect citations helps nobody at all. Posting where the room already holds a billion people in it is not vanity. For most careers, most of the time, it is close to the entire game.

That argument holds only as long as the room keeps sending the visitor to you. Agarwal and Sen ran a randomised field experiment, in an SSRN working paper revised in June 2026 and reported by PPC Land on 1 July. The result was stark. Google's AI Overviews cut organic publisher clicks by 39.8 per cent and lifted zero-click searches by 34.5 per cent. That 34.5 per cent figure had already been measured for clicks alone back in April 2025. It has kept climbing since. ppc-land-ai-overviews The same PPC Land piece reports that Cloudflare abandoned charging AI crawlers per crawl. It started paying publishers per citation instead, for the identical reason: the platform's own answer, not the underlying page, is what most visitors now see. Reach on somebody else's feed is not yours to keep. That changes the moment the feed's own AI answers first.

What I Ship Instead

I did not build an AI twin. Instead I built a small retrieval layer on gaganmalik.io. It has three parts: Ask, a public `llms.txt`, and a hand-written brief behind each essay. A language model can cite that brief rather than guess at the answer. That habit started with training a model on my own five years of writing instead of a generic one, and it has not stopped since. None of it has a billion members, and I have stopped pretending that it will. All of it has citations I can check myself. None of it sits on a domain LinkedIn can deprecate or Meta can fold into a training default I never separately agreed to.

LinkedIn and Meta already built that twin from member content supplied under a default we never read, and they bill other people to use it. Owning your identity now means a retrieval layer with citations on a domain you control, not a louder feed or a twin vendor. Tunde will never see the query that screened him out, or a penny of the $450 million LinkedIn aims to bill for profiles like his.