I asked Claude and ChatGPT the same architecture question. Only one told me I was wrong.

I asked Claude and ChatGPT the same architecture question. Only one told me I was wrong. Last month I was designing a caching layer for a high-traffic API. I had a plan. I thought it was solid. I asked ChatGPT: "Is this a good caching strategy?" ChatGPT said: "That looks like a solid approach! Your use of Redis with TTL-based expiration is a great choice for this use case." I felt good. I shipped it. Two weeks later: cache stampede. 3am incident. Everything down. The second opinion that would have saved me After the incident, I described the same architecture to Claude. Claude said: "I see a potential issue here. With TTL-based expiration across multiple instances, you're at risk of a cache stampede when keys expire simultaneously under high load. Have you considered probabilistic early expiration or a mutex-based approach?" That's the answer I needed at 2pm on a Tuesday, not at 3am on a Thursday. Why this happens: sycophancy is a training artifact This isn't a dig at OpenAI — it's a k