Create an AI That Writes Exactly Like You

You can now create an AI that writes exactly like you, and it’s more accessible than you might think.

I spend a ton of time trying to get AI to sound less, well, like an AI. You know the drill: you generate a draft, and then spend just as long editing out the corporate jargon and weirdly formal phrasing. But I just stumbled upon an incredible tutorial that lays out a full-proof method for cloning your writing style.

This AI professional, Matt Wolfe, posted a video that walks through the entire process of fine-tuning a large language model on your own content. I was blown away by how clearly the mind behind it explained everything. He’s essentially giving the AI “acting lessons” so it can mimic your unique voice, humor, and structure, instead of just spitting out generic text.

🎭 Fine-Tuning vs. Knowledge Dumps (RAG)

Before we dive in, the creator makes a super important distinction between two key AI concepts: fine-tuning and Retrieval-Augmented Generation (RAG). Understanding this is crucial.

• RAG (The Reference Manual): This is what most of us do already. When you upload a PDF or paste text into an AI chat and ask questions about it, you’re using RAG. The innovator explains this is like giving a writer a giant binder of facts. They’ll know the information, but their writing style won’t change. They’ll still sound like a generic assistant.
• Fine-Tuning (The Acting Lessons): This is totally different. Here, you’re not teaching the AI what to know, but how to sound. The creator’s analogy is perfect: it’s like giving a writer hundreds of your past articles, scripts, or posts and telling them, “Learn to write like this.” The AI internalizes your tone, your sentence structure, your jokes, and everything.

This is the key to creating an AI that genuinely sounds like you, and the expert’s guide makes it surprisingly straightforward.

📌 Your Secret Weapon for Data Prep

The most intimidating part of fine-tuning has always been preparing the data. You need to convert your raw writing into a special format called JSONL, which is a technical and tedious task. But this is where the creator’s method is pure genius. He uses ChatGPT as his personal data scientist. He simply dumps his raw text, like a giant file of all his YouTube transcripts or Twitter data, into ChatGPT and gives it a specific prompt. The AI does all the heavy lifting, converting the messy text into a perfectly formatted training file.

Here’s a simplified version of the prompt the one who posted it used:

“Attached is a file containing all my [tweets/transcripts]. I need you to convert this into the proper JSONL format for fine-tuning a model.

For each piece of text, please:
1. Think of a prompt that could have generated it (e.g., ‘Write a tweet about X in the style of Matt Wolfe’).
2. Create a ‘prompt’ and ‘completion’ pair.
3. Format the entire document into the JSONL structure required by Nebius.
4. Split the data into two files: a training set (90%) and a validation set (10%).”

This is an awesome hack that automates the most difficult step of the process.

✅ Your 4-Step Path to a Custom AI

This contributor breaks the entire workflow down into a clear, actionable playbook. I was taking notes the whole time because it felt so achievable.

1. Gather Your Content: First, you need a body of work. The author shows how to download your entire archive from X (formerly Twitter) or use a simple online tool to grab all your YouTube transcripts. The more of your own writing you can feed the model, the better it will learn your style.
2. Format with ChatGPT: Using the prompt above, you upload your raw text file and let ChatGPT create your JSONL training and validation files. A pro tip from the creator: be specific with your instructions. He initially had an issue where his model kept trying to @-reply people because his data included his Twitter replies. He fixed it by re-running the prompt and adding, “remove any replies and only use original posts.”
3. Train the Model: He uses a platform called Nebius for this part. You just create a new fine-tuning “job,” upload your two JSONL files, and choose a base model. The expert suggests Llama 3 8B for short-form content like tweets and Llama 3 70B for long-form content like scripts. He even provides the exact settings he uses for the training parameters, which takes out all the guesswork.
4. Deploy and Test: Once the training is complete, which took him just seven minutes for his tweet model, you can deploy it. The final step is to test it in the platform’s playground. The results the creator showed were amazing; the fine-tuned model’s output was leagues better than the generic base model.

💡 What to Expect: Cost, Quirks, and Payoffs

This savvy professional is very transparent about the whole process, including the realities of what to expect.

• Cost: This isn’t free, but it’s a one-time training cost that can be surprisingly affordable. The creator shared his exact numbers: fine-tuning the tweet model on Llama 3 8B cost him just $2.56. The much larger YouTube script model on Llama 3 70B was more of an investment at $75. This gives you a great idea of the potential budget.
• Quirks & Quality: He preaches the “garbage in, garbage out” principle. His first attempt with unformatted YouTube transcripts resulted in poorly formatted AI output. It’s a powerful reminder that the quality of your input data directly impacts the quality of your AI’s writing. Clean data is everything.
• The Payoff: The side-by-side comparisons in the video speak for themselves. The generic model wrote a tweet about tacos that was full of cringey hashtags and overly dramatic language like “gastronomic symphony.” His fine-tuned model just wrote, “Why are tacos the best food ever?” which is exactly how he’d actually tweet. It captured his voice perfectly.

This process is still a bit technical, but it’s the clearest and most accessible method I’ve seen for getting truly personalized AI outputs.

This is how power users are creating content that is practically indistinguishable from their own. For the full, detailed walkthrough and to see the side-by-side model comparisons for yourself, check out the original video from this talented creator.