Ask Claude to Design a Redis Caching Strategy for Your App

Caching decisions — what to cache, for how long, and how to invalidate — are often made inconsistently across a codebase. Describe your access patterns and let Claude design it properly from the start.

Ask Claude: "Here are the most frequently called methods in my service layer: [paste code].
Which ones are good caching candidates? Suggest TTLs based on how often the data changes,
and write the actual caching implementation with proper invalidation."

For Laravel, Claude generates complete Cache facade calls with tag-based invalidation — so flushing a user's cache doesn't require knowing every individual key:

public function getUser(int $id): User
{
    return Cache::tags(['users', "user:{$id}"])
        ->remember("user:{$id}", now()->addMinutes(15), fn() =>
            User::with('roles')->findOrFail($id)
        );
}

// Invalidate on update — Claude writes this observer too
public function invalidateUser(int $id): void
{
    Cache::tags(["user:{$id}"])->flush();
}

Ask Claude to also write the model observers or event listeners that trigger cache invalidation automatically whenever the underlying data changes. It'll warn you about common pitfalls like caching user-specific data under a shared key.

The right caching strategy can cut your database load dramatically — and Claude can design one tailored to your actual data in minutes.