The amount of analysis available to you right now is greater than at any other time in human history.
And yet, most people have less clarity about what is really happening than they did five years ago.
What changed is the scale. When analytics were expensive to produce, there was a natural filter. The people who produced it had to know something because the cost of being wrong was financial and reputational. Now that cost is basically zero. Anyone can generate a macro shot that looks like it came from a Goldman desk in five minutes. The noise grows exponentially while the actual signal remains approximately constant.
The insidious thing is that the noise no longer seems like noise. It seems like a sign. Bad analysis used to be obviously bad. It is now polished, structured, uses the correct terminology and cites the correct data. The tools most people use to produce it are optimized to make it sound good. Whether the result is actually correct is a completely different question.
Distinguishing the two is the whole game now. To overcome it, the same systems that flood the markets with noise can be used. That’s what I’ve spent the last two years demonstrating: publicly, on X, with every call time-stamped and nothing removed, in geopolitics, energy, macro, crypto and broader markets simultaneously.
The account grew from nothing to over 140,000 followers organically, with no paid promotion or name attached. Signal Core on Substack, the home of the full forecasting operation, became the third best-selling crypto post on the platform in nine months. In a market flooded with noise, the signal alone was enough.
the moment
The signal versus noise problem has arrived at the worst possible time.
The next twelve months will reshape the financial, technological and geopolitical order more than the last decade combined. Digital assets are integrating with the traditional financial system at a pace that would have seemed impossible eighteen months ago. Regulatory frameworks stagnant for years are being rewritten in real time. AI is transforming the way capital is allocated. Geopolitical orders are realigning. Monetary policy is at an inflection point. The labor market is restructuring in front of us.
These are fundamental changes that arrive simultaneously and combine with each other. And this is exactly the moment when the ability to see clearly has collapsed. The stakes have never been higher and there has never been less clarity about what is really happening.
The convergence problem
It’s actually worse than a noise problem.
The AI is making everyone converge toward the same wrong answers simultaneously. When a thousand people use these tools to analyze the same event, they don’t get a thousand different perspectives. They get minor variations from the same predetermined result. The tools not only fail to produce signals, but fabricate false agreements.
Before AI, if five analysts said the same thing, that meant something. Now, if five hundred accounts say the same thing, it could mean that they all used the same tool.
What this looks like in practice
In January of this year, the prevailing view was that a direct confrontation between the United States and Iran was unlikely. Diplomatic channels were still open. The market was not pricing in a significant conflict risk. Oil was priced as if nothing was happening.
The structural picture told a different story.
More than a month before the strikes began, indicators were already pointing to a confrontation that was more likely than unlikely. We pointed this out publicly in X on January 13, while the crowd was still dismissing the risk. When strikes hit and oil nearly doubled, the move caught most of the market by surprise. The sign was there. The crowd just wasn’t looking at him.
The contributions we were observing were not exotic. Public statements, internal economic pressure within Iran and absence of certain de-escalation patterns. Anyone with open Internet access could see the same things. The advantage was in the synthesis: reading those entries as a single convergent system rather than as separate news streams. That synthesis is the difficult part. The tickets are just the tickets. The bottleneck has never been technology. This has been how technology is used.
This is the pattern. The information was available. The tools to process it were available. What was missing was the ability to read the sign before the crowd formed around the wrong interpretation.
The scarce resource
Most people use AI to generate. Very few use it to see.
The signal is when you can look at a situation that confuses the entire market and see the underlying structure. It’s when you can hold a position that every feed tells you to abandon, and hold it anyway, because you can see something they can’t see.
The challenge for most people is not generating the signal themselves. It’s recognizing who really has it. Most analyzes are limited to the point of meaninglessness: strategies to avoid accountability disguised as analysis.
The old filter to overcome this was credentials. It no longer predicts who sees clearly. Many of the most important calls of recent years have been ignored by traditional institutions and answered by people working outside them. What matters now is whether someone is really seeing what’s happening: recognizing patterns that the crowd misses, naming what’s real before it’s obvious, and being right often enough to hold up over time. Once you can see clearly, you will start trading on a different timeline than the rest of the market.
What comes next?
We are entering an era where signal is the most valuable and least understood asset in the market. Investors, builders and allocators who realize this first will have a structural advantage that will accumulate over the years. Those who continue to consume the flood without questioning it will continue to agree with the crowd. And the crowd will continue to get it wrong in the most important moments.
Finding rooms where the actual signal still appears is becoming increasingly difficult. Most places that claim to add market intelligence are simply amplifying what the models already spit out.
The 2026 Consensus in Miami is one of the few that still functions as a filter rather than an amplifier. The people who appear have skin in the game. Your disagreements are real. Their agreements were not made by the same five models that everyone else uses. That type of room is increasingly difficult to find anywhere else. That’s why I’ll be there, hosting a small invite-only session on what signal mining at scale is really like.
The advantage will not belong to whoever has the most information, the fastest tools, or the noisiest platform.
It will belong to the one who can see clearly when everyone else is drowned in the noise.
That is the scarcest resource in the markets right now.
And it is becoming increasingly scarce.
