The Federal Reserve’s monetary policy decisions have a huge impact on the market. I decided to use AI to analyze the Fed’s statements and press conferences to see if I could predict their next move. The results are intriguing. Here’s what the AI is forecasting.
The Counterintuitive Truth
In monetary policy, the best practitioners often do less, not more.
The lesson: customer feedback is the only metric that matters. It sounds simple. It's incredibly hard to execute.
The Framework That Actually Works
Here is a simple framework for evaluating monetary policy. It's not complicated, but it requires discipline.
Step 1: the market doesn't care about your roadmap
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: timing is everything in this game
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get monetary policy right treat it as an ongoing process, not a one-time project.
The AI Angle
Any discussion of monetary policy in 2026 has to include AI. As someone who's invested in Anthropic, OpenAI, Scale AI, and Hugging Face, I have a front-row seat to how AI is transforming this space.
The short version: AI makes good practitioners better and bad practitioners worse. It's an amplifier, not a replacement.
Some teams use AI to get far more out of monetary policy. Others spend heavily on AI that solves the wrong problem. The difference comes down to understanding what you're actually trying to achieve.
This connects to broader themes around algorithmic trading, AI trading, AI risk management that I've been thinking about a lot lately.
What's Next
Best practice in monetary policy is changing fast. What worked last year might not work next year. That's both the challenge and the opportunity.
My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.
If you're building in this space, the best time to get monetary policy right is before you need to. Don't wait for a crisis to force your hand.
I'll keep sharing what I learn. This stuff matters too much to keep to myself.
Frequently Asked Questions
Q:What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
Q:How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
Q:How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.