Google Cloud publishes 13 demos for building, scaling and governing Gemini agents

Google Cloud has published a new set of 13 hands-on demos for its Gemini Enterprise Agent Platform, turning a broad enterprise AI pitch into a more concrete developer playbook. The July 18 post says the demos cover the full agent lifecycle: building with Google's code-first Agent Development Kit, scaling workloads on Agent Runtime, governing access and tool calls, and optimizing agent quality after deployment.

The package is notable because it treats AI agents less like standalone chatbots and more like production software systems. Google says developers can install its Agents CLI into coding tools including Antigravity, Claude Code and Codex, then use seven bundled skills to scaffold, evaluate, deploy and monitor agents from inside their editor. That puts the emphasis on repeatable workflows rather than one-off prompts.

What the demos cover

• Basic Gemini-powered agents built with ADK and tested through a command line or web interface.
• A corporate expense agent using ADK 2.0 graph workflows, Pub/Sub events, a FastAPI service and human review for higher-risk approvals.
• Model Context Protocol examples for reusable tools that query BigQuery, search files and call APIs.
• Agent-to-UI and Agent-to-Agent patterns for visual interfaces and cross-language multi-agent systems.
• Governance examples using unique agent identities, mTLS, IAP, IAM, Model Armor, prompt-injection checks and data-leakage inspection.

For enterprise teams, the governance and operations examples may be the most important part. Google describes an Agent Gateway demo where a multi-tool ADK agent calls MCP servers on Cloud Run with identity, authentication and authorization controls on every outbound call. Another demo adds a security-focused development workflow with a STRIDE threat model, Semgrep pre-commit hook and a pre-tool-use gate intended to block risky actions before execution.

The release also reflects a broader shift among cloud providers: AI agent platforms are moving from model access and prototype builders toward lifecycle tooling. Google's demos repeatedly pair agent capabilities with familiar production concerns such as state, deployment previews, logging, tracing, analytics, persistent sessions and quality evaluation. One tutorial focuses on agents that can run for weeks by using durable state machines, event-driven idle handling and checkpoint-and-resume patterns.

Google's claims are developer-facing and should be read as an official product guide rather than independent benchmark evidence. Still, the publication gives teams a clearer view of how Google wants Gemini Enterprise Agent Platform to be used: as a governed application stack for agents that can connect to business data, call tools, coordinate across frameworks and stay observable after launch.

Sources

• cloud.google.com

Cover photo by Daniil Komov on Pexels, used under the Pexels License.