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How to Use AI to Answer Customer Questions from Your Entire Codebase

Open every service repository under one parent directory so Claude Code can trace a customer question across the whole product. Combine current code with product documentation and a customer quirks page to produce specific technical answers and deployment plans.

How to Use AI to Answer Customer Questions from Your Entire Codebase

Al shows fifteen service repositories opened under one VS Code workspace, then combines current code, Confluence documentation, and customer-specific deployment constraints in Claude Code.

Before you start

What you need

  • Local access to the relevant product repositories
  • Current product and deployment documentation
  • A customer quirks page containing environment and security constraints
  • The customer's exact technical question

What you’ll make

A customer-specific technical answer or deployment plan grounded in current code, documentation, and known environment constraints.

Tools used

Step by step

The workflow

Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.

5 steps

Step01

Consolidate All Repositories

Clone all of your company's individual code repositories into a single parent directory on your local machine. This setup allows an AI assistant to see the entire codebase at once, rather than being limited to a single service.

Step02

Open Parent Directory in VS Code

In VS Code, open the top-level parent directory that contains all the individual repositories. This is a key step that enables your AI assistant to search and understand connections across every service in the platform.

Step03

Automate Codebase Updates

Create one command that updates the expected main branch in every repository under the parent directory. Make it stop or report clearly when a repository has local changes, a missing remote, or a failed pull.

Example prompt
Create a script named pull-all that finds each Git repository directly under this directory and updates its main branch from origin. Do not discard local changes. For every repository, print the branch, whether it updated, and any error that needs attention. Exit nonzero if any repository could not be updated.

Save the generated script and run it daily to keep your local codebase in sync with the main branches.

Step04

Maintain a 'Customer Quirks' Document

Maintain one lightweight customer quirks page with the deployment, security, identity, networking, and data requirements that make each enterprise environment different.

Example prompt
I am creating a 'Customer Quirks' document to track unique requirements for our enterprise customers. Generate a template with sections for [Customer Name]. The template should include placeholders for key technical details like their security protocols, infrastructure specifics (e.g., secrets management, namespaces), and any environmental constraints we need to respect during deployment.
Step05

Query Across Code, Docs, and Notes

Ask Claude Code to answer the customer question using the current repositories first, then supporting documentation and the matching customer notes. Require code and document pointers so the result can be checked quickly.

Example prompt
Customer: [name]
Question: [exact technical question]
Desired result: [answer, deployment plan, or troubleshooting steps]

Use the current code in this workspace, our connected documentation, and the customer quirks page. Account for these known constraints: [constraints].

Return:
1. A direct answer
2. Step-by-step implementation or troubleshooting guidance
3. The relevant repositories, file paths, symbols, and documentation pages
4. Any assumptions, conflicts, or facts you could not confirm

Do not invent behavior that is not supported by the code or documentation.

Mentioning the customer's name in the prompt helps the AI cross-reference your 'customer quirks' page for a more tailored response.

What good looks like

  • Every repository is on the latest expected main branch before analysis begins.
  • The response names the relevant files, services, or documentation pages behind its answer.
  • Customer-specific constraints appear in the proposed steps.
  • Unknown or conflicting behavior is stated plainly instead of being filled in.

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After the steps

Runbook notes

How to recover when the loop fails and where human judgment helps.

Recover

If it goes sideways

The answer is based on stale local repositories.
Run the update script, report any repository that failed to pull, and rerun the question only after the expected branches are current.
The response gives a generic deployment answer and misses the customer's constraints.
Name the customer in the request, point Claude to the customer quirks page, and require a constraint-by-constraint deployment plan.
Claude returns a confident answer without showing where it found the behavior.
Ask it to cite file paths, symbols, and documentation pages for each important conclusion, then mark anything it cannot support as unknown.

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