The current era offers more analysis than any point in human history, yet most individuals have less understanding of what is happening than they did five years ago. The primary difference now is the sheer scale of available information, which has led to an explosion of noise. In the past, producing analysis was costly, and those who did had to be knowledgeable to avoid reputational and financial damage. Today, the cost of generating analysis is virtually zero, allowing anyone to create macro insights that resemble those from prominent institutions like Goldman in just a few minutes.
The real challenge now is distinguishing between genuine signal and cleverly disguised noise. The same systems that flood the market with noise can also be used to cut through it and uncover the truth.
Over the past two years, I have demonstrated this publicly on X, making accurate calls across various markets, including geopolitics, energy, and crypto, without any paid promotions or personal branding. My account grew organically to over 140,000 followers, and my Substack publication, Signal Core, became the third best-selling crypto publication within nine months. This success underscores the power of clear signal in a noisy market. The current moment is particularly critical, with the next twelve months poised to reshape the financial, technological, and geopolitical landscape more than the past decade combined.
Digital assets are integrating with traditional finance at an unprecedented pace, regulatory frameworks are being rewritten, AI is transforming capital allocation, and geopolitical orders are realigning. These foundational shifts are happening simultaneously, making it harder to see clearly despite the high stakes. The problem is worse than just noise; AI is converging everyone toward the same incorrect answers, manufacturing false agreement.
When multiple analysts use the same tools to analyze an event, they often produce similar, flawed perspectives rather than diverse insights. Before AI, consensus among analysts meant something, but now it may just indicate the use of the same tools. In practice, this means that even if many accounts agree on something, it does not necessarily reflect a well-informed consensus.
A recent example is the U.S.-Iran confrontation, where the prevailing view was that a direct conflict was unlikely, yet our analysis, based on public statements, economic pressure, and de-escalation patterns, indicated a confrontation was more likely. We flagged this publicly before the strikes began, and when they did, the market was caught off guard. The information was available, but the edge came from synthesizing it, not just generating more analysis. The scarce resource now is not the ability to generate signal but the ability to recognize and see it amidst the noise.
Most people use AI to generate, not to see, and the challenge is recognizing who truly has signal. The old filter of credentials no longer works; what matters is whether someone can see what is happening, recognize patterns the crowd misses, and be right often enough to be credible over time. Those who can see clearly operate on a different timeline than the rest of the market. We are entering an era where signal is the most valuable and least understood asset.
The first to figure this out will have a structural advantage that compounds over years. Finding genuine signal is getting harder, and most venues that claim to aggregate market intelligence are just amplifying existing models. Events like Consensus 2026 in Miami, where attendees have skin in the game and disagreements are real, are becoming rare. The edge will belong to those who can see clearly when everyone else is overwhelmed by noise, and this ability is becoming the scarcest resource in the market.