What If Your AI Twin Thought in Your Mother Tongue?

*A cognitive twin trained on English conversation gets retrained to operate in N'Ko. This is what we're looking for.* A cognitive twin is a language model fine-tuned on a specific person's conversation history. Not a general assistant. A specific, personalized model that has seen your questions, your reasoning patterns, your way of framing problems. It learns to respond the way you think, not the way a generic chatbot does. The technical implementation involves collecting your conversation data as supervised fine-tuning (SFT) examples, message pairs where the user side is a question or prompt and the assistant side is the kind of response you'd actually want. You train a LoRA adapter on that data, a small set of weight updates that shift a base model's behavior toward your patterns without replacing everything the base model knows. The result is something that feels distinctly familiar. It has your vocabulary preferences. It matches your register. It picks up on the framing you use for certain kinds of problems. It's not magic. It's pattern matching over your actual language use. But pattern matching done well, at scale, on a model that already understands language deeply, produces something that feels personal in a way generic models don't. All of the existing cognitive twin work was done in English. Every training example was English. Every evaluation prompt was English. The model learned to reason in English because that's the language the training data was in.