We stopped reading the news. We built an AI to read it for us. (Meet Pulitzer v2)
Last week, we open-sourced our editorial team:
Read the original post: “Meet Pulitzer”
Today, I want to talk about why we handed the keys to an AI named Pulitzer, and why we believe Responsible AI is the only way to survive the modern market.
The Problem: Analysis Paralysis
If you are a developer or a retail investor, your enemy is not the market.
Your enemy is noise.
There are 58,000 public assets and thousands of news articles published every minute.
- The developer’s dilemma: You want to build fintech tools, but normalizing data from 50 sources is a full-time job.
- The investor’s dilemma: You want to buy NVDA, but you do not have four hours to read the 10-K and cross-reference insider trading filings.
We realized we could not hire enough analysts to cover the long tail.
So we built one.
Pulitzer is not a content generator.
It is a synthesis engine.
Every day at 18:00, it ingests thousands of data points:
- Price action
- Valuation metrics
- Sentiment signals
- Market news
Then it does the one thing humans struggle to do at scale: find the signal.
- For developers: Pulitzer turns unstructured chaos into structured JSON. You can import a market narrative just like you import a price feed.
- For investors: It delivers a 30-second brief. It does not tell you what to buy. It tells you what happened so you can decide with intent.
Under the Hood: Responsible AI in Finance
Pulitzer was built with a strict do-no-harm architecture.
In finance, an AI hallucination is not funny. It is expensive.
Grounded generation
Pulitzer will not cite a fact it cannot verify directly from its source data.
Transparent logic
Every insight is tagged with its source. If sentiment is bullish, it points to the data that explains why.
Human in the loop (initially)
We trained Pulitzer using our own editorial standards, teaching it to avoid hype and focus on structure.
Why This Matters
We believe the future of finance is not bank versus bitcoin.
It is you versus the noise.
By automating the grunt work of research, we free people to do the high-value work: thinking.
We are not building a black box.
We are building a glass house.
