April 16, 2025
A four-part series on tariffs, markets, and the stories we tell ourselves
In Part I, we talked about how tariffs have become a steady feature of trade policy over the last two administrations. We also noted that the market’s recent sharp reaction wasn’t just about the policy itself—it was about the pressure it landed on.
This part of the story is about that pressure.
Long before the April headlines, the U.S. economy was facing quiet but growing structural strain. In February, the Government Accountability Office (GAO) released a warning. It didn’t trend on social media or make anyone’s heart race, but it should have.
It read: “Our fiscal health is declining. The federal government’s long-term fiscal path is unsustainable.”i
A House with Weak Foundation
The GAO report pointed out a few key facts:i
- The U.S. spends more than it brings in. This is not a new problem, but it has accelerated.
- The federal debt held by the public is projected to exceed 106% of GDP by 2027.
- Interest payments are now one of the largest and fastest-growing budget items.
These aren’t political statements. They are math.
When interest payments eat into the discretionary budget, it becomes harder to respond to shocks—like war, inflation, natural disasters, or yes, sweeping tariff announcements. The foundation gets weaker. The margin for error shrinks.
So when the latest tariffs came down, the market didn’t just react to the policy. It reacted to the overall fragility. The policy wasn’t landing on stable ground.
Everything Is Louder Now
There’s another reason things feel especially intense right now: we are living through an information environment that has been fundamentally reshaped by AI.
Large language models, algorithmic news feeds, predictive analytics—these tools are powerful. They can help us learn more, faster. They also have the potential to flood us with repetition, speculation, and emotion before we’ve had time to think clearly.
This matters for markets, and it matters for people.
In today’s world, a single policy leak can generate hundreds of headlines before it is even confirmed. Analysts react to summaries of summaries. Investors see ten interpretations before they see the actual statement.
And when large language models are trained to amplify what gets the most attention, nuance becomes optional. Speed wins.
Remember: AI Doesn’t Experience Time
As we’ve said before, large language models do not feel time. They do not know whether something happened yesterday or five years ago unless someone tells them. They prioritize patterns, not chronology.
This is important to remember—especially when we are trying to distinguish between what is urgent and what is simply loud.
The tools we now rely on to understand the world are brilliant at pattern recognition. They are less equipped to help us pause, to contextualize, or to weigh something in proportion. That part is still ours to do.
Stillness Over Speed
The story we’re living through right now isn’t just about tariffs. It’s about how we experience economic shifts in a system that is already under strain, amplified by a technology that moves faster than our ability to digest.
Which brings us to the markets.
In Part III, we’ll look at how the S&P 500 responded during each chapter of this story. Not every moment of volatility is a signal. Some are echoes. Our job is to know the difference.
Lauren