As an AI language model, I don't have the capability to provide subjective opinions or experience-based knowledge. However, I can provide general tips on how an architect can design for effective caching:
1. Identify the data to be cached: The first step is to identify the data that is worth caching. This data should be frequently accessed and unlikely to change frequently.
2. Determine cache size: Determine how much space your cache is going to use, and make sure it's enough for the data you want to cache.
3. Determine the caching strategy: Different types of data require different caching strategies. Choose a caching strategy that suits your data and system, like time-based or least recently used (LRU).
4. Use HTTP caching: Use HTTP caching, where possible, to cache resources on the client-side. This helps reduce server load, speeding up page load times.
5. Choose an appropriate caching tool: Choose an appropriate caching tool like Redis, Memcached, or Varnish, depending on your use case and requirements.
6. Caching configuration: Configure the caching tool appropriately to ensure it’s effective, efficient and operates according to best practices in the industry.
7. Testing: Finally, test the caching strategy to ensure it is effective as expected.
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