I used an AI for 7 months to search for a Theory of Everything. I failed. And it’s the best thing that could have happened.

Reflections on a Seven-Month Journey with AI in the Quest for a Unified Theory

Over the past seven months, I embarked on an unconventional experiment: collaborating closely with artificial intelligence to hunt for a Theory of Everything. The outcome? I didn’t find the grand unifying principle I sought — and surprisingly, that turned out to be an invaluable success.

Rethinking AI’s Role in Scientific Discovery

In many online discussions, AI often gets depicted as a mere calculator or an equation-generator—something that helps crunch numbers or extend ideas. But from my experience, AI’s true potential lies in serving as an honest mirror for our reasoning, forcing us to confront our assumptions and biases.

The proliferation of AI-related posts in communities dedicated to fundamental physics underscores a common pattern: people tend to either seek validation or rely too heavily on AI to confirm their hypotheses. The key isn’t whether we use AI but how we use it. Framing prompts appropriately makes all the difference. Asking, “Show me how my theory holds up” invites confirmation, while instructing, “Find every flaw in my reasoning” drives critical evaluation. The AI responds accordingly—it’s a mirror, not a judge.

From Seeking Confirmation to Embracing Challenge

My approach was deliberately designed to challenge my ideas rather than bolster them. Initially, I was captivated by a compelling hypothesis—a dynamic “ether” that could unify disparate phenomena. Working with AI, early results appeared promising, almost too good to believe. It was tempting to cling to these validations, to feel intellectually triumphant.

However, I shifted gears and focused on conflict. I tasked the AI with rigorously testing my ideas, demanding transparency and precision. This process forever changed my relationship with knowledge. I learned to code in Python at a level I had never imagined, applying this skill to deepen my understanding and make my ideas tangible.

Failure as a Path to Genuine Understanding

Most profoundly, my core hypothesis—this elaborate notion of a dynamic ether—was conclusively discredited through data-driven analysis. It was not dismissed by a mere opinion but by concrete evidence: the data simply did not support it. That moment of failure was crucial. It exemplified a vital lesson: truth emerges when we allow ourselves to be proved wrong.

This experience reinforced an essential philosophical principle: when stuck, revisit your assumptions. Be willing to abandon what seems fundamental and accept uncertainty. This openness is where true discovery begins.

**Practical Advice for Collaborating with