Google Agent Development Kit

Sweet spot: a team on Google Cloud, using Gemini, who wants one framework that runs identically from laptop to Vertex. ADK removes the "which agent library should we bet on?" question if you already live in Google's ecosystem — the answer is ADK. Failure modes. Outside GCP / Gemini, ADK offers no real advantage over LangGraph, and picks up the cost of a thinner community. API churn is real — the 0.x release cadence means pinning versions and budgeting time for small migrations. Multi-agent patterns can be expressed, but the documentation leans heavily on Gemini examples; translating to Anthropic requires reading the LiteLLM adapter layer. What to pilot. Build one agent that uses two tools, evaluate it with the built-in harness, and deploy to Vertex. If that full loop (dev → eval → deploy) takes less than a day, ADK has delivered on its pitch; if any step fights you, LangGraph's mature ecosystem may be a better fit even at the cost of a little more deployment code.

The Agent Development Kit (ADK) is Google's open-source framework for building agent-based applications. It ships Python abstractions for agents, tools, multi-agent orchestration, session state, evaluation, and deployment — intended to be the Google-blessed way to build something Gemini-native, though it is model-agnostic in practice. Architecturally, ADK is close to LangGraph and AutoGen: you define agents with tools, compose them into pipelines or sequential / parallel / loop flows, and the framework handles the tool-use loop, state, and streaming. Where it differentiates: first-class Gemini support, tight integration with Vertex AI for deployment, a built-in evaluation harness, and a dev UI (adk web) for inspecting agent runs locally. Released in April 2025 and rapidly gaining traction — it is the framework Google points developers to for agent work on Gemini and Vertex. For teams already on Google Cloud, ADK is the least-friction path to production agents.