I Made ChatGPT and Claude Think The Same (Here's How)

21 Oct 2026 · 11 min
11:20

In this tutorial, Javier Torres explains why he built a persistent "second brain" to give large language models (LLMs) like Claude and ChatGPT a shared, reliable source of truth, and walks viewers through the practical setup. He begins by describing the problem of fragmented, "poisoned" AI context that arose when his AI Council started steering his business in unwanted directions, especially over‑emphasizing his Christian identity. To fix this, he created a structured knowledge base stored as Markdown files in Obsidian, with strict rules that only his own statements become truth, while AI suggestions are merely adopted after his approval. He outlines the key components of the system – a memory file, next‑session file, ideas inbox, core OS file, voice‑calibration snippets, locked decisions, frameworks/people, reference transcripts, and a quarantine folder – and explains how each AI reads or writes to them. He demonstrates how to seed a new chat in both Claude and ChatGPT by pasting the source‑of‑truth document, then giving them the same task, showing that while their outputs differ, they operate from the same context. He emphasizes using voice mode for faster, more natural input, performing a comprehensive brain dump, and iteratively refining the source‑of‑truth until it sounds exactly like the user. The video targets founders, coaches, consultants, creatives, and pastors, and offers a free tool to automate the basic setup, plus links to deeper walkthroughs and consulting services. The overall message is that a well‑curated, verified knowledge base prevents AI from hijacking one’s brand and ensures consistent, personalized assistance across multiple LLMs.

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