How to speed up AI agents by 80% on the Gemini Enterprise Agent Platform
Gemini enterprise agent platform Google cloud Ai agent optimization OpenTelemetry Cloud run Parallel processing Performance tuning Antigravity ide Ai development Token monitoring
This tutorial demonstrates how to optimize AI agents on the Gemini Enterprise Agent Platform to achieve 80% faster processing times. Developer Sami Maghnaoui works with AI expert Luis Sala to use the Antigravity IDE for diagnosing performance bottlenecks, implementing parallel processing for SDK outputs and voice synthesis, and deploying to Cloud Run. The video also covers integrating token consumption monitoring directly into telemetry tools for cost optimization in production.
Related videos
Gemma 4 production stack: Model Armor, ADK Agents, Tracing
Is your Kubernetes certification still worth it? | The Agent Factory
20 minutes to 2 minutes: How Home Depot automated incident responses with OpenTelemetry
How to deploy an AI agent to Cloud Run (step by step)
Intent-driven development with Claude Code & Fable 5
MCP vs API: The protocol every developer needs to know
How to build a continuous evaluation pipeline for multi-agent systems with Gemini
What's new with Gemini from Google DeepMind
Startups shipping at scale with Google DeepMind
Build AI agents on Cloud Run
How Model Context Protocol (MCP) actually works
