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How I AIClaude Code + 15 repos: how a non-engineer answers every customer question | Al Chen
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At a glance
WHAT IT’S REALLY ABOUT
Using Claude Code across repos to deliver precise customer support
- Public documentation and generic AI answers often fail for enterprise customers who need precise, step-by-step explanations tied to how services actually interact in production.
- By cloning ~15 service repos into one VS Code workspace, Al uses Claude Code to query the living source of truth (main branches) and generate accurate, code-referenced answers faster than pinging engineers.
- A lightweight automation script (written by Claude) keeps every repo updated, making it feasible to rely on code even as multiple releases ship daily.
- Al augments code context with Confluence and Slack via MCP integrations, including a “customer quirks” page that tailors deployment guidance to each customer’s unique security and infrastructure constraints.
- Reactive Slack support is turned into a virtuous loop by summarizing threads into reusable knowledge-base articles (via Pylon), improving future support, internal enablement, and potentially product roadmap inputs.
IDEAS WORTH REMEMBERING
5 ideasEnterprise customers don’t want “the docs answer”; they want the system walkthrough.
In complex architectures, customers ask how services cascade together (deployment, caching, auth, callbacks), so answers must reflect real interactions—not just product narratives.
Open your IDE at the right “scope” to make AI useful across services.
Loading a multi-repo workspace lets Claude traverse dependencies across repos; you can also narrow or widen the directory level depending on the question to manage context bloat.
Treat main-branch code as the most current documentation—then keep it current automatically.
Because code changes daily, Al uses a simple Claude-generated script to git-pull main across all repos, avoiding tedious manual pulls and reducing stale answers.
Blend code with internal knowledge sources to answer what code alone can’t.
Using Confluence and Slack MCPs, Claude can incorporate deployment runbooks, prior Slack resolutions, and customer-specific constraints to produce responses that match real environments.
Maintain a “customer quirks” page to unlock truly tailored guidance.
Capturing items like secret managers, namespace rules, air-gapped constraints, CRD limitations, and encryption requirements allows Claude to produce deployment steps that feel bespoke and build trust.
WORDS WORTH SAVING
5 quotesI can actually pull all of these repos into my VS Code, and I can now use Claude Code to ask our entire codebase questions.
— Al Chen
They don't want the docs answer. They want the step-by-step answer of how all these services cascade together.
— Claire Vo
The reality is we can now all live in a little bit more chaos because the AI navigates all that information for us across systems.
— Claire Vo
I treat it like my entry level analyst… I’m very relentless when it comes to getting the right answer from Claude or from AI.
— Al Chen
Throw it into Confluence, throw it into Notion, throw it into Slack, wherever.
— Al Chen
SPEAKERS
Al Chen
guestField engineering team member at Galileo who uses AI coding tools (e.g., Claude Code) to support enterprise customer deployments and troubleshoot across multiple repositories.
Claire Vo
hostProduct leader and host of How I AI who interviews practitioners about applying modern AI tools at work.
High quality AI-generated summary created from speaker-labeled transcript.
