There is a particular kind of frustration that comes from reading about extraordinarily successful people. You finish the biography or the case study or the interview and you walk away with a vague sense of inspiration and almost no idea what to actually do differently on Monday morning. The gap between understanding what someone did and knowing how to replicate it has always been enormous.

John Chmela decided to close that gap. And the method he built to do it is changing how he thinks about AI, about business, and about what it actually means to learn from the people who came before us.

He calls it Applied AI. And Warren Buffett, one of the most studied investors in human history, is one of its most compelling demonstrations.

Why Buffett Is the Perfect Test Case

Warren Buffett is not secretive about how he operates. His letters to shareholders are public. His interviews are extensively documented. His investment philosophy has been analyzed, debated, and taught in business schools for decades. The methodology is not hidden. What has always been hidden is the time.

Buffett’s process for evaluating a company before investing is exhaustive by design. He wants to know everything. Leadership quality. Long term competitive positioning. Ethical track record. Financial stability across multiple market cycles. The checklist is long, detailed, and demanding. And Buffett has never been in a hurry. He has spent years, sometimes a decade, researching a single company before committing capital to it.

That patience is part of what made him. But it also meant that his methodology, while publicly available in theory, was practically inaccessible to anyone without his specific combination of time, experience, and temperament.

John Chmela looked at that and saw something different. He did not see an investment philosophy. He saw a problem that AI was built to solve.

The Two Questions That Drive the Method

Chmela’s approach to Applied AI runs on two questions asked in sequence. They sound simple. The implications are not.

The first question is this. What exactly did this person do, step by step, to build what they built? Not the highlight reel version. Not the inspirational summary. The actual blueprint. Every decision, every phase, every methodology they used from the beginning to where they ended up.

The second question follows immediately. Now take every single one of those steps and figure out how AI would handle it today. What becomes faster? What becomes cheaper? What becomes more accurate? What was previously impossible that is now straightforward?

What comes back from that process is not just a modernized version of the original blueprint. It is something genuinely new. A strategy that carries the proven logic of someone who already succeeded layered on top of the capabilities that only exist right now.

What Happens When You Run Buffett Through the Process

When Chmela ran Buffett’s investment methodology through this framework the results were striking. The evaluation criteria Buffett uses, his specific checklist for determining whether a company is worth a long term investment, can be fed directly into a large language model. The AI can then analyze stocks against every single one of those criteria and return results in seconds.

Not approximations. Not guesses based on surface level data. A genuine application of Buffett’s own framework applied at a speed and scale that would have been science fiction twenty years ago. What Buffett spent months or years doing per company, the AI completes across dozens of companies before you finish your morning coffee.

Chmela is clear about what this means and what it does not mean. It does not mean Buffett is obsolete. His wisdom, his judgment, his ability to think in decades rather than quarters, those things are not being replaced. What is being replaced is the bottleneck. The grinding, time intensive research process that made his methodology inaccessible to everyone except him is now available to anyone willing to ask the right questions.

That is the core insight. The wisdom travels forward. The friction gets eliminated.

It Is Not Just About Investing

The Buffett example is compelling because it is concrete and because Buffett’s methodology is so well documented. But Chmela is emphatic that the method works on anything. He has run it on Tony Robbins. On Elon Musk. On Jeff Bezos. On athletes, movie producers, influencers, and housewives who built seven figure businesses from their kitchen tables.

Every single time, the same pattern emerges. A proven blueprint exists. AI can identify every step in that blueprint. AI can then find the upgrade path for each step. And what comes out the other side is a strategy that would have taken years to develop through conventional means, compressed into something actionable.

He has now written over a hundred of these articles on LinkedIn, each one a different subject, each one a different application of the same methodology. And he makes the point with quiet confidence that he has not even scratched the surface. The pool of people who built extraordinary things before AI existed is essentially infinite. Each one is a new case study. Each one is a new blueprint waiting to be upgraded.

Why Most Businesses Are Missing This Entirely

Chmela spends a lot of time thinking about why companies are struggling to extract real value from AI despite the enormous amount of attention and money being poured into the space. His diagnosis is consistent. They are starting in the wrong place.

Most businesses approach AI by asking what the technology can do. They browse tools. They run experiments. They try to find use cases that fit the capabilities they have discovered. It is an exploration led by the technology rather than by the mission.

Chmela flips it entirely. Start with what you are trying to accomplish. Start with a proven model for accomplishing it. Then bring AI in to execute that model at a level no human team could match alone. The technology serves the strategy. Not the other way around.

This is why he believes that the companies who will win the next decade are not necessarily the ones with the biggest AI budgets or the most sophisticated tools. They are the ones who are most clear about where they are going and most disciplined about using AI to get there faster.

The Method Anyone Can Use Starting Today

The practical application of Chmela’s method does not require a team of engineers or a six figure software budget. It requires clarity and curiosity in equal measure.

Pick someone who built what you want to build. Find the most detailed account of how they did it that you can locate. Feed it into an AI system with one instruction. Give me the complete step by step blueprint this person used from the beginning. Then take that blueprint and run a second prompt. Take every step in this blueprint and identify how AI could execute it faster, cheaper, or more effectively today.

What you get back is not a guarantee. It is not a shortcut around the work. But it is a genuinely upgraded starting point. A map built on proven logic and modernized for the tools that exist right now.

John Chmela has been doing this every day for over a year. He has shared every single result publicly and for free. And his core argument has not changed since he started.

The blueprint already exists. Someone already figured out how to build what you are trying to build. Your only job is to find that blueprint, hand it to the most powerful analytical tools ever created, and then actually execute what comes back.

That is the whole method. And it works for anyone willing to ask the right questions.