Google Cloud has delivered a substantial update to its Vertex AI Agent Builder, aiming to make the process of building and deploying AI agents more efficient. The revised Agent Development Kit now supports prebuilt plugins, including a new option that enables agents to recover from errors independently. This change gives developers a path to more autonomous behaviour without the overhead of writing recovery logic by hand.
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Expanded language support increases accessibility
Go has been added as a supported programming language, joining Python and Java. This addition broadens access for teams that use Go in backend environments and reduces the need for language-specific workarounds. Google positions this as a step toward making AI agent development accessible across a wider range of engineering teams.
One-command deployment simplifies production moves
Once an agent is ready, developers can deploy it with a single command through the ADK CLI. Product Management Director Mike Clark described the change as a major improvement that shortens the path from local testing to live production. The intention is to remove friction at the point where many teams hesitate to move beyond prototypes.
Better observability for debugging and refinement
Post-deployment, developers gain deeper visibility into agent behaviour. The updated dashboard presents token usage, latency, errors, and tool call patterns. A dedicated playground allows fast debugging, and a new traces tab helps developers track the sequence of actions taken by an agent. This is useful for diagnosing misalignment, unexpected tool calls, and branching logic errors.
PayPal Principal Engineer Nitin Sharma praised the improvements, noting that the toolset supports inspection of agent interactions, monitoring of state transitions, and management of multi-agent workflows.
Security receives equal attention
Faster deployment increases the risk of shipping flawed or exposed systems, and Google has attempted to address this. The new Model Armor feature screens both tool calls and agent responses for prompt injection and related threats. The Security Command Center serves as an inventory of agent components, helping teams track their assets and monitor risk.
Clark acknowledged that while many developers experiment with agents, achieving a secure production deployment is far more complex. The new safeguards are intended to lower that barrier without slowing down development.
