Google Agents CLI 统一 Agent 工程全生命周期

Karpathy's Agentic Engineering finally has proper tooling!

(built by Google)

Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight.

The problem is that production agents don't run on the agent code alone. They need a model provider, a retrieval layer, an eval system, a deployment target, and observability.

And normally, these are scattered across different dashboards, config files, and tools, each with its own setup and learning curve.

The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI.

It covers the entire lifecycle in a single interface, covering scaffolding, evaluating, and deploying ADK agents.

The setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language.

I mapped the whole thing end-to-end in the diagram below. Here is what each layer is doing:

> Agent Orchestration defines the agent using the ADK, and the A2A protocol handles coordination when one agent needs to invoke another. ADK is model-agnostic, so the models cover Gemini, Gemma, and third-party models like Claude, via Model Garden.

> The data layer handles retrieval. Vector Store stores the embeddings for RAG, and the ingestion pipeline loads and chunks docs into it. Monitoring and storage happen alongside it.

> The evaluation layer runs the agent against test scenarios with LLM-as judge scoring. It runs before deployment.

> For deployment, you can choose between Agent Runtime, Cloud Run, etc., depending on how much control you need. Agents CLI configures across all targets.

> Finally, teams that need staging and production environments, the IaC and CI/CD layer handles infrastructure as code and deployment pipelines.

Every one of these layers is a service that a dev would otherwise configure manually.

But Google's Agents CLI ties them together to make the full agentic engineering lifecycle practical.

The diagram below makes this clear, and I worked with the Google Cloud team to put this together.

Agents CLI GitHub repo → https://fandf.co/4eY1MgE

(don't forget to star it ⭐ )

Akshay wrote a hands-on article covering all six steps from install to enterprise registration.

It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end.

Read it below.