Building the Damodaran Financial Bot with OpenClaw — From Architecture to a Tested Mock POC
In the previous article, we moved from the idea of a Damodaran-style financial bot toward a practical multi-agent architecture: a system where different agents are responsible for data retrieval, assumptions, valuation, supervision, and report writing. That architecture gave us the direction of travel. The next question is more concrete: how do we turn that architecture into a project that can be tested, evolved, and eventually connected to real financial data sources? ( Medium ) This article continues from that point by focusing on the proof-of-concept implementation. The goal is not to build a production-grade valuation platform in one jump. The goal is to build a small, deterministic, testable version of the system that proves the shape of the application before we introduce live data, complex assumptions, model drift, flaky APIs, or LLM variability. That distinction matters. A financial agent system can become difficult to debug very quickly. If an answer is wrong, the source of th...