02 / Agentic AI
Trading Agent
Together with a colleague, I co-built a research application that evaluates potential opportunities in the context of a user’s portfolio.
Co-built in under a month
- Contribution
- Product ideation, UX, implementation; co-built with a colleague
- Focus & technologies
- Python · LangGraph
Research with context
LangGraph-driven workflows bring together news, forums, company data, and portfolio context to develop an investment thesis, positives, negatives, and a risk profile. Daily research typically surfaces one to three opportunities when warranted.
From discovery to conversation
The app tracks holdings and trades alongside geographic, sector, and currency diversification. Discovery and watchlists help follow companies; contextual real-time LLM chat supports company-specific questions.
A shared build
We co-built the application in less than a month, using AI extensively across ideation, UX, implementation, testing, and review.