Hey, I’m Matt. I’m a former Bloomberg News reporter, and you’re reading AI Street, where I report on how Wall Street uses AI. Every Thursday, I cover the week’s biggest AI-in-finance stories, plus original reporting and analysis.
AI Twins Take on Routine Work at Millennium
The hedge fund decided to offer digital colleagues to all employees after building the first twin for Chief Information Officer Vlad Torgovnik, on the idea that if it worked for him, it would work across the firm, according to a company blog post. Millennium then scaled the program to more than 150 twins, with 97% of the first user group interacting with their twin daily.
The twin is available to any employee who wants one and doesn’t impersonate the employee. It has its own identity, email address, permissions and audit trail. Employees email their twins to help with routine tasks such as research, project management and preparing meeting materials.
Next up: AI teammates, which are built for teams and, like twins, have their own identities and learn the teams’ working styles.
TL;DR
This is more evidence that hedge funds are tailoring models and AI systems to their own processes. See earlier coverage here:
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After Earnings, Heron’s AI Interviews Former Executives for Their Take
Many AI tools for investors sift through information that already exists. Heron Intelligence is using AI to create something new: interviewing former executives just after companies report earnings to get their view on the quarter.
Heron says it aims to deliver the interviews, transcripts and analysis within hours. It uses AI to review what management said, flag questions executives may not have answered and process the interviews. Human researchers can do additional digging when needed.
Investors can access the research through Heron, platforms including Daloopa and Carbon Arc, or plug it into their own systems through an API or MCP, according to the announcement.
TL;DR
While AI models have hoovered up the Internet, there’s still lots of knowledge rolling around in humans’ heads. Heron is trying to take advantage of that — with the help of AI.
Citadel Looks to AI Labs for Quant Talent
As we discussed last week in an interview with Jump Trading’s Lucas Baker, the skill sets needed to work at a quant firm or a frontier AI lab have converged.
That means there are more firms competing for the same talent. Citadel is looking to boost its 180-person Global Quantitative Strategies team at a double-digit percentage rate over the next year, according to Bloomberg. The firm is looking for researchers from AI labs such as Google DeepMind to develop investment ideas.
TL;DR
As quant and AI skill sets converge, the firms that employ them will likely start to look more alike too.
Robinhood Brings AI Trading Agents Into Its App
Robinhood announced that investors will be able to build their own AI agents in the company’s app to create a trading strategy, conduct research and execute trades.
In about four months, Robinhood had more than 150,000 customers sign up for an agent account through an earlier beta that required them to connect their own AI agents, which compares to about 28.6 million funded customers at the end of August.
Robinhood said agents were using its tools almost 30 million times a day. Trade approvals are on by default for the new built-in agents, though customers can switch them off. Robinhood also announced subscriptions to data and tools from 11 providers with plans for more.
TL;DR
Agentic trading is picking up. It may seem novel now, but at one point, driverless cars did too.
QUOTABLE:
“One of the questions we're working through is the distinction between an agent carrying out a customer's instruction and an agent making an investment decision itself,” said Anthony Denier, Webull's group president and U.S. CEO, on AI-driven trading.
“Those are very different scenarios from a regulatory standpoint, and we want to make sure we're moving forward cautiously.”
From: Webull working with regulators as AI trading evolves
SEC Makes Its Rules Easier for AI to Read
The SEC is changing how it writes rulemaking releases so AI tools can read them more easily, said Brian Daly, who leads its investment management division. It is using more tables and bullet points and has reduced substantive discussions in footnotes by “something like 95%,” Daly said in an interview with Paul Weiss.
What Else I’m Reading
Who Runs Jane Street? | BBG
ExodusPoint Joins Hedge Funds Partnering With Anthropic Over AI | BBG
College Students Flex Their Power in A.I. Investment Frenzy | NYT
Robinhood Debuts Weekend Trading, Perpetual Futures in US | BBG
Polymarket Hires Ex-Goldman Sachs Partner as Institutional Head | BBG
Working at the frontier: How Balyasny Asset Management evaluates and governs Claude Fable 5 | Anthropic
Delaware Chancery Decision Highlights Risks of AI-Generated Transcripts of Board Meetings | Debevoise
This Week in AI Street
How Agents Learn to Manipulate Markets: Study
AI agents learned to create and exploit price bubbles without being instructed to break the rules, according to an academic study.
I recently spoke with Wharton professors Itay Goldstein and Winston Dou, who, along with Yan Ji at the Hong Kong University of Science and Technology, have been studying how common AI training methods impact markets, specifically reinforcement learning.
The researchers built a simulated stock market where two AI traders competed alongside three groups of investors following preset trading rules. Some chased rising prices.
The AI traders got information about changes in the stock’s value before everyone else.
Each time through the simulation, the AI traders could trade twice. That gave them a chance to learn how an initial purchase could move the price and make a later sale more profitable. They couldn’t exchange messages. But they could see price changes.
“They just find, over time, through repeated interactions, that collaborating, acting not competitively and creating bubbles are in their best interest,” Goldstein said.
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Millennium’s AI twins
Heron’s AI-led interviews
Citadel recruiting from AI labs
Robinhood’s AI trading agents
The SEC writing rules for AI