Deep Research and Development

 Introduction In the previous article , we explored how to build a financial agent using OpenClaw as a foundation for real-world automation. That implementation demonstrated an important principle: modern AI systems become useful not when they generate text, but when they interact with structured tools and data pipelines . This article extends that idea toward a more ambitious goal: Building a Damodaran-style valuation bot (DBOT)  - a system that performs structured equity valuation using established financial methodologies. The objective is not to invent a new valuation framework. Instead, the goal is to: reuse well-known financial models (DCF, comparables, sensitivity analysis) integrate them with LLM-based reasoning orchestrate everything through a multi-agent system use OpenClaw as the execution and interaction layer This first part focuses on system design and conceptual architecture. Later parts would move into implementation details. DBot Why Build a Damodaran Bot? Equi...