AI That Works in Testing Doesn’t Always Hold in Production”

AI demos often look clean, fast, and reliable. But things change once those systems move into production.

In this clip from Tuesdays with Trailblazers, Vishnu Gatla from F5 explains why AI behaves differently in real-world environments compared to controlled demos.

When AI systems hit production, they face real traffic, edge cases, infrastructure constraints, and unpredictable workloads — all of which introduce new challenges that aren’t visible during testing.

💡 The key insight:
Building AI is one thing. Running it reliably in production is a completely different problem.

👉 Watch the full episode of Tuesdays with Trailblazers for more insights on AI, infrastructure, and enterprise systems

https://youtu.be/2c3FlEkx7-E?si=cl1MFSk2D-TmH8Il


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