Descriptions:
Al Chen, a field engineer at Galileo (an AI observability platform for enterprise applications), demonstrates how he uses Claude Code alongside 15 locally cloned repositories to answer deep technical questions from enterprise customers—despite not holding an engineering role. The interview, hosted on the “How I AI” channel, focuses on the practical gap between public documentation and the architecture-level answers enterprise developers actually need when deploying Galileo’s multi-service Kubernetes stack.
The workflow is straightforward: Chen uses a 16-line script (written by Claude Code itself) to sync the latest main branches of all 15 repos into VS Code, then queries across the full codebase in natural language. When a customer asks how specific backend services cascade together, Chen can pull the actual implementation rather than relying on documentation that often lacks that level of specificity. He draws a comparison to LangChain’s open-source support bot, which queries public repos directly, as a model for what self-serve technical support could eventually look like.
The conversation also covers the limits of the approach: Chen still manually proofreads every Claude Code response before sending it to customers, removing AI-sounding phrasing and trimming verbose summaries that land poorly in enterprise Slack threads. He discusses the longer-term question of whether customers could eventually query a sanitized version of Galileo’s codebase directly—and where the human field engineer adds value once AI can navigate technical documentation at this fidelity.
📺 Source: How I AI · Published April 06, 2026
🏷️ Format: Interview
