Enhancing AI Apps with Smart Caching for Better UX
Wanted to bump this thread from Aparna D. about making AI apps feel magical through smart caching (Thread here: https://x.com/aparnadhinak/status/1851683922255712588). She breaks down how Cursor AI achieves their super-fast response times using cache pre-warming - they actually start caching relevant file contents the moment a user starts typing.. 👀 The thread dives into OpenAI vs Anthropic caching tech, with some interesting performance differences:
OpenAI shines with shorter prompts (0-25k words), auto-caching messages/tools/schemas
Anthropic pulls ahead with longer prompts (50k+), offering more granular control
Cache hits = major cost savings (50% OpenAI, 90% Anthropic)
A key takeaway: intentional prompt structuring + smart cache management = that "magical" UX we're all chasing. (Props to Harrison Chu for the benchmarking data backing this up!) Some questions I'm curious about:
- 1.
How are folks deciding what to pre-warm in their cache? Cursor's approach of using typing as a signal is interesting, but what other user behaviors are you watching?
- 2.
For those working with longer prompts, are you seeing similar performance gains with Anthropic's caching?
If anything here jumps out at you let me know in the replies. Would love to hear about what's working (and what isn't)!