An agent’s behavior depends on more than the first prompt you write. Google’s Optimize Agent Behavior explores instructions, output structure, model configuration and planning as connected parts of an agent-development workflow.
This free introductory course is useful after a first agent setup. It gives you a more deliberate way to examine unpredictable behavior and integration requirements, while comparing model choices and constraints. The emphasis is on improving the specification and the development discussion, rather than promising perfect outputs from a few settings.
Course at a glance
| Provider | |
|---|---|
| Platform | Google Skills |
| Level | Beginner |
| Language | English |
| Estimated study time | 1 hour; official estimate, individual study time varies. |
| Format | Ten web lessons and four quizzes |
| Access | Free instruction; free Google Skills account required. Product and practical access are separate. |
| Recognition | Course completion badge advertised after required activities; no professional certification or academic credit. |
What you’ll learn
- Write structured, multi-section instructions with examples, personality and ethical boundaries.
- Explore structured output using the Pydantic topic in the curriculum.
- Compare model choices and configuration in relation to cost, speed, quality and safety settings.
- Study planning, multi-step tasks, realistic constraints and BuiltInPlanner.
Skills you’ll gain
- Structured instruction design
- Output-schema literacy
- Model-choice reasoning
- Constraint-aware planning
- Agent behavior analysis
Make the intended behavior easier to inspect
The sequence starts with vague instructions and introduces a more structured alternative. It then examines unpredictable output and structured output with Pydantic. These topics connect the behavior you want with the form an integration expects to receive.
Instruction examples, consistent personality and ethical boundaries are explicit learning objectives. Use them to describe a particular agent’s role more clearly, rather than assuming that a longer instruction is automatically a better one.
The next pair considers model configuration and the limits of a one-size-fits-all choice. The objectives include balancing cost, speed and quality, configuring safety thresholds and tuning parameters. No universal setting or guaranteed improvement is promised.
Connect planning with a bounded task
The final substantive pair moves from complex tasks to planning with BuiltInPlanner. This gives multi-step work a place in the course, alongside domain-specific planning and realistic constraints in the stated objectives.
For optional reflection, outline a fictional assistant that turns supplied public event details into a consistent summary. Specify the required output fields, the information it may use and a case where it should acknowledge missing information. This is independent study guidance, not an additional Google assignment or a runnable specification.
Now separate the instructions from the output format and the plan. Which requirement belongs in each part? That exercise can make the course’s structure easier to apply without requiring model calls, real organizational data or a hosted agent.
Google labels the course Introductory, shown as Beginner in WikiFree. The description assumes an earlier first-agent experience, so basic configuration familiarity is useful preparation. This article does not add a formal admission condition.
The public curriculum contains ten web lessons and four required quizzes. The one-hour estimate may increase if you investigate unfamiliar configuration terms or reproduce examples independently. Course completion supports learning; it does not guarantee reliable behavior in every new environment.
Free learning and practical access
Google Skills advertises the complete instruction as Free and uses a free learner account. The public curriculum lists web lessons and four required quizzes, without a separately listed provisioned cloud lab. Independent model calls, software setup, agent hosting and other services are separate and may involve costs. A course account does not imply unlimited model or runtime access. Google advertises a course completion badge after the required activities. It is not a professional certification or academic credit.
Explore more learning options in the free course catalogue.
Frequently asked questions
Does the course cover structured output?
Yes. Structured output with Pydantic is a named curriculum topic, alongside instructions, model configuration and planning.
Does Beginner mean there is no implementation terminology?
No. Google’s Introductory level maps to Beginner, but the material builds on a first agent and discusses configuration and planning concepts.
Will a configuration change guarantee correct answers?
No. The course explores development choices and trade-offs. It does not promise perfect outputs, a universal model setting or validated production behavior.
Questions & discussion
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