It’s match day, and sports fans expect instant tactical insights. ⚽ But what if your AI analysis app takes over 90 seconds to answer? 📉 Join Google Cloud expert Luis Sala and developer Sami Maghnaoui in the latest AI Agent Clinic as they diagnose a fatal latency flaw in Playback IQ before peak traffic hits. Built on the Gemini Enterprise Agent Platform, watch them dive into the Antigravity IDE to: 🔍 Spot sequential bottlenecks using OpenTelemetry and Cloud Trace ⚡ Parallelize the workflow to cut agent execution time by 80% 💰 Monitor token consumption to optimize runtime costs Is your AI agent actually production-ready? Watch the full teardown and learn how to optimize your own builds → https://goo.gle/4oZAomX

This is the reality of AI in production: building the agent is only the beginning. The real challenge starts when performance, reliability, latency, and cost have to work together under real-world demand. Anyone can demo an agent. Few can optimize one when customers are waiting and milliseconds matter. The future belongs to builders who can prove their solutions work at scale—not just in development, but in production. If your organization wants to identify talent through real-world challenges and demonstrated outcomes, explore https://basestudy.app/ and discover how proof-based evaluation reveals who can actually deliver when it counts

Informative 👍

Like
Reply

Speed is the need nowadays 🙂

Like
Reply

Very relevant for anyone building AI agents at scale

Like
Reply

Great example of why latency matters just as much as accuracy in AI applications.

Like
Reply

Speed is a feature⚡ Fast, reliable AI creates better user experiences every time

See more comments

To view or add a comment, sign in

Explore content categories