CrewAI and Google ADK
Words made simple
A few useful meanings before you read the explanation.
- API
- A way for one piece of software to ask another for data or an action. A claims API might return the current status of a claim.
- Agent
- An application that uses a model to choose its next action within defined limits. It can use tools and continue through several steps.
- Orchestration
- Coordinating tasks: deciding their order, passing data between them, and handling waiting or failures.
More words from this lesson
- State
- The data describing where a workflow is now, what it already knows, and what still needs to happen.
- Observability
- Being able to understand system behavior through records such as logs, measurements and traces.
- HTTP
- The request-and-response protocol used on the web. HTTPS adds encryption to protect information in transit.
- SDK
- A set of code tools provided to help an application use a service or framework.
Overview
- CrewAI organizes agent work around roles, tasks, and orchestration constructs such as flows.
- Google ADK is an agent development toolkit with agent and workflow-oriented components.
- Both provide reusable abstractions; neither makes a multi-agent design necessary.
Why this matters
Different teams prefer different ways to express roles, coordination, model integration, and deployment.
An everyday example
Teams can use different project-management systems while still following the same security and quality standards.
A technical example
CrewAI might express a research-and-review team; ADK might coordinate search, extraction, and response agents within a Google-centered deployment.
How it works
- Define scoped responsibilities
- Select supported orchestration
- Connect tools
- Manage run state
- Validate and evaluate outputs.
Architecture and flow
Application → framework roles/workflow → model + safe tools → evaluated output.
The insurance assistant example
A research agent compares public product documents, while private claim actions remain in the insurer's service boundary.
When to use it
After benchmarking a small proof of concept against a plain loop or LangGraph and confirming integration fit.
When to avoid it
Do not adopt a role-based team for one exact lookup or confuse Google integration with a requirement to use only one provider.
Interview answer
“I compare frameworks by state control, tool scopes, review, recovery, observability, and ecosystem fit, rather than memorizing their agent names.”
Benefits, trade-offs, and production considerations
- Compared with LangGraph, examine whether roles/workflow abstractions express your failure and approval paths clearly.
- Check framework versions, license, hosting, and run-state ownership.
- CrewAI docs, Google ADK docs.
| Framework | Core starting point | Useful enterprise fit | Key question before adoption |
|---|---|---|---|
| LangGraph | Explicit state, nodes, transitions | Stateful support and review flows | Can the team design recovery and state migrations? |
| OpenAI Agents SDK | Agents, runners, tools, handoffs | Agent-first assistants | Do its runtime/state features match the service requirements? |
| MAF | Agents plus explicit workflows | Microsoft-centered applications | Which language/version/hosting capabilities are actually supported? |
| Semantic Kernel | Model/function integration and agents | Existing Microsoft plugin applications | What remains maintained and what should migrate? |
| AutoGen | Agent coordination/conversation | Existing research or multi-agent applications | Does coordination justify cost and align with current support? |
| CrewAI | Roles, tasks, crews/flows | Structured specialist task teams | Are roles measurable or only cosmetic? |
| Google ADK | Agents and workflow tooling | Google-centered agent applications | Are deployment, model, and state contracts a good fit? |
You should be able to explain each framework's purpose, but hands-on depth in LangGraph plus one ecosystem SDK is more valuable than shallow API familiarity across all seven.
Can you explain it without the notes?
CrewAI and Google ADK
Use your own words. Explain an example and one limitation before checking the explanation.
Check your explanation
CrewAI organizes agent work around roles, tasks, and orchestration constructs such as flows. Google ADK is an agent development toolkit with agent and workflow-oriented components. Both provide reusable abstractions; neither makes a multi-agent design…
Turn this concept into a clear answer.
Practice this conceptAdapted from 13_AI.MD · “CrewAI and Google ADK”. Examples are study fragments; framework behavior can depend on your version.