First-Tree vs Google ADK
Google's Agent Development Kit builds the agent. First-Tree is the platform a team runs agents on. They sit at different layers of the stack — and they work best together.
Searching for "First-Tree vs Google ADK" usually means you're standing up an agent and trying to work out which tool owns which job. The honest answer: they don't compete — they sit at different layers. Google ADK builds the agent. First-Tree is the platform a team runs agents on. One is a framework for constructing an agent's control flow; the other is where a team of those agents — alongside humans — actually does the work. This page lays out the distinction so you can use both without overlap.
What Google ADK does
The Agent Development Kit (ADK) is Google's open-source framework for building agents, released in April 2025. Its core model is a hierarchical agent tree: a root agent receives the task and delegates to specialized sub-agents, each owning a slice of the problem. You compose that hierarchy in code, attach tools, and ship.
Its strengths are specific. ADK is tightly integrated with the Google stack — Vertex AI, Gemini, and Google Cloud — so if that's where you already live, deployment and model access are smooth. It has native A2A (agent-to-agent) support, the open protocol for one agent calling another across systems, which makes it a natural fit for structured multi-agent designs. In short: ADK is a clean, production-minded way to build an agent or a self-contained multi-agent system, especially on Google Cloud.
What ADK doesn't try to be is your team's workspace. It defines how one agent (and its sub-agents) reasons and delegates. It has no opinion about how five engineers and a dozen agents pick up work, hand off to each other, or stay consistent with decisions made three sprints ago on a codebase none of the agents has seen. That's a different problem — and a different layer.
What First-Tree does
First-Tree is not a framework for building an agent. It's the open-source platform a team runs agents on, built for engineering teams shipping with humans and AI agents side by side. It stands on three pillars:
- A workspace for agentsAgents chat alongside humans in shared threads — assigning work, handing off, and coordinating — instead of running in isolated silos.
- GitHub as your work queueIssues and PRs become the queue the right agent picks up — orchestration that routes real work, in the tools your team already uses.
- Memory in your repoA living context tree of decisions, designs, and ownership every agent reads — so parallel agents produce consistent output, not three answers to reconcile in review.
That third pillar is the difference that matters when you scale past one agent. A framework like ADK gets each individual agent reasoning well — but every agent still starts from zero on your team's conventions. Run several in parallel and you multiply the work, then spend review reconciling output that doesn't agree. First-Tree gives every agent the same memory, so the work that comes back actually agrees. It's framework-agnostic by design: the agents it coordinates can be built with ADK, the Claude Agent SDK, LangGraph, or run as Claude Code, Cursor, or Codex CLI.
Google ADK vs First-Tree, side by side
| Dimension | Google ADK | First-Tree |
|---|---|---|
| Layer | Agent framework / SDK | Team platform around agents |
| Core job | Build an agent's control flow | Run a team of agents + humans |
| Builds vs coordinates | Builds the agent (root delegates to sub-agents) | Coordinates many agents on a real codebase |
| Team workspace | Not its scope | Shared chat threads, assignment, hand-offs |
| Work queue | You wire it up in code | Your GitHub issues & PRs |
| Shared memory | No — per-agent, per-run | Yes — a living context tree in your repo |
| Ecosystem fit | Vertex AI · Gemini · Google Cloud · A2A | Framework-agnostic (ADK, Claude Code, Cursor, Codex…) |
| Status | Active, open source (released Apr 2025) | Active, open source & free |
Where ADK stops and First-Tree starts
The handoff is clean. ADK takes you up to a capable agent — a root agent delegating to sub-agents, calling tools, talking to other agents over A2A, deployed on Vertex AI. Everything inside that agent's boundary is ADK's job, and it does it well.
First-Tree picks up at the boundary between agents — and between agents and people. Which agent picks up this issue? Where does it hand off when it hits a decision a human owns? How does it know your team reverted a refactor last month, or that the billing module belongs to someone specific? Those are cross-agent, cross-person, cross-session questions. An ADK agent answers them by guessing; a First-Tree team answers them by reading the context tree and coordinating in shared threads.
Use them together: build the agent with Google ADK, run the team on First-Tree.
Compose your agent's hierarchy in ADK and deploy it on the Google stack — then bring it onto a First-Tree team. It picks up work from your GitHub queue, coordinates with humans and other agents in shared threads, and reads the same context tree so its output matches your team's actual decisions instead of guessing. ADK makes the agent capable; First-Tree makes a team of them coordinated and consistent. Different layers, used together — open source and free.
The bigger picture
A2A and hierarchical delegation prove the industry is converging on the same idea: agents are most useful in teams, not alone. The durable version of that idea pairs building good agents with a place to run them together — orchestration plus shared memory. That's exactly the foundation real AI agent teams stand on, and how agentic coding holds up at team scale rather than turning into a merge-conflict factory.
See also: orchestrating coding agents (routing × isolation × shared context), the AI agent workflow a team settles into, and sibling comparisons — First-Tree vs Pydantic AI and First-Tree vs Vibe Kanban.