Weekend 08: Using AI as Your Investment Partner

The rise of AI and Large Language Models (LLMs) is fundamentally changing the investing landscape.

Many people focus on whether AI can pick stocks. I think that is the wrong question.

The real question is: How can investors use AI to become better decision-makers?

For decades, one of the biggest advantages held by institutional investors was access to information, research teams, and analytical resources. Today, AI is dramatically reducing that gap.

Traditionally, if you wanted to understand a company, you had to spend hours reading annual reports, earnings transcripts, investor presentations, industry reports, and news articles.

Today, AI can summarize and organize information within minutes.

For example, you can ask:

Instead of spending hours gathering information, investors can spend more time evaluating and making decisions.

AI does not eliminate research.

It dramatically reduces the cost of research.

Quantitative investing used to require significant programming skills and access to expensive tools.

Today, investors can simply ask AI:

For many retail investors, AI effectively acts as a junior analyst available 24 hours a day.

The ability to generate analysis through natural language is one of the biggest changes brought by LLMs.

Personally, I use AI for much more than asking questions.

I use AI as a research partner.

Beyond investing itself, I spend a significant amount of time building my own tools and investment systems.

Examples include:

AI helps accelerate development dramatically.

Instead of spending days designing a model from scratch, I can discuss ideas with AI, challenge assumptions, test different approaches, and iterate much faster.

The process becomes: Idea → Discussion → Prototype → Backtest → Refine

AI shortens every step.

One area where I find AI particularly useful is model refinement.

Suppose I develop a stock scoring system.

I might score companies based on factors such as:

The first version is rarely perfect.

Instead of manually reviewing every assumption, I can discuss the model with AI:

AI becomes a sounding board that helps improve the framework.

Not because AI knows the future.

But because AI can help expose weaknesses in our thinking.

Many people think AI's biggest advantage is generating answers.

I think its biggest advantage is accelerating iteration.

Good investing is often about continuously refining a framework.

Previously, investors might test one or two ideas per month.

Today, AI allows investors to explore dozens of ideas, challenge assumptions, and improve models much faster.

The feedback loop becomes significantly shorter.

And shorter feedback loops often lead to better systems.

Perhaps the most exciting part is that AI is available to everyone.

You no longer need a team of analysts, expensive research subscriptions, or a large institution behind you.

An individual investor with:

can now perform research that was previously difficult or impossible for retail investors.

AI will not automatically make anyone a better investor.

Bad processes can still produce bad results.

However, AI gives individual investors a powerful new capability: The ability to find, analyze, and evaluate opportunities faster than ever before.

The winners of the AI era may not be those who blindly follow AI-generated answers.

They may be the investors who learn how to collaborate with AI, challenge it, and use it to continuously improve their own investment frameworks.