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Brendan Li – AI Pathways (September 2026)
Artificial intelligence is changing how traders and investors research markets, process information, monitor positions,
and build repeatable investment workflows.
But knowing how to use ChatGPT or another AI model is very different from actually building systems that can support a trading or investing process.
Brendan Li – AI Pathways is a specialized AI education and community platform built around that intersection.
Created by Brendan Li, an ex-technology investment banker and UCLA graduate,
AI Pathways focuses specifically on applying AI models, AI agents, automation, templates, and analytical systems to financial markets.
Rather than treating AI as a generic productivity tool,
the program explores how traders and investors can incorporate AI into research, analysis, monitoring, strategy development,
and performance improvement.

Building AI Trading Agents Without Traditional Coding
One of the central components of AI Pathways is the creation of AI trading agents without requiring traditional programming skills.
The official community currently includes step-by-step guides for creating AI trading agents without code.
This makes the concept accessible to market participants who may understand trading and investing but do not have a software engineering background.
The underlying idea is to turn a financial workflow into a system that AI can assist with.
Depending on the use case, an agent-based workflow might help with tasks such as:
Collecting information
Organizing market research
Monitoring selected assets
Processing financial data
Evaluating predefined criteria
Generating research summaries
Tracking investment-related information
Automating repetitive analytical tasks
The emphasis is on building systems rather than simply asking an AI chatbot isolated questions.
Building A Personal AI Trading Stack
A useful AI workflow rarely consists of one tool.
Different tasks may require different models, data sources, prompts, scripts, automations, or agent configurations.
Brendan Li – AI Pathways provides a framework for thinking about these components as a connected system.
Instead of asking which AI tool is currently the most popular, learners can focus on questions such as:
What information does the strategy require?
Where does that information come from?
Which tasks are repetitive?
Which tasks can be automated?
Where should human judgment remain involved?
How should outputs be reviewed?
How can the system be improved over time?
This systems-oriented perspective makes AI more useful than simply experimenting with individual prompts.





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