Plain-language explainer
AI agents in search
AI agents are AI tools that carry out tasks on a user’s behalf, such as researching, comparing or booking. They rely on clear, structured information on websites.
The work to plan together
A scope shaped around this requirement.
- Agents read pages and data, not justScope
- Structured data and clear policies helpReview
- Booking and checkout steps should be simpleCheck
The useful starting point
An AI agent can break a task into steps and use tools, such as search, to gather information or take an action. The word agent does not establish how autonomous or reliable the system is.
What to review
- Agents read pages and data, not just headlines
- Structured data and clear policies help
- Booking and checkout steps should be simple
- Expect gradual adoption
A practical example
A shopping assistant might compare product attributes and then request confirmation before a purchase. Accurate prices, stock and policies help it evaluate the options.
The numbers or scenarios in this guide are illustrative. They are not claimed Tangensys client results.
What to avoid or interpret carefully
Tool use can fail and generated reasoning can be wrong. Business integrations need access limits and approval for consequential actions.
Turn the guide into a small action plan
Record the starting point
Use the example above to identify what is happening in your own website, campaign or process. Save the evidence before changing it.
Choose the first check
Start with the relevant items in the review list. Assign an owner, identify required access and write down what you expect to learn.
Review before expanding
Compare the result with the original evidence. Keep useful changes, explain uncertainty and investigate problems before increasing scope.
Distinguish information assistance from system action
An agent-like search experience may help interpret a question, explore sources or perform a supported task. Those behaviours should be named separately. A useful source page does not automatically grant an application authority to act for a business or customer.
Information task
Maintain accurate explanations and relevant source links. A generated summary can be checked against those facts. Do not assume every experience uses the same sources.
Tool task
Identify the supported integration and permission boundary. Reading availability differs from changing a booking. Current capabilities need an official technical review.
Evidence task
Record the actual interface, action and result when testing. A demonstration should include unsupported and failed cases, not only a successful curated example.
How to interpret this guidance
Focus on useful source information and clear operating boundaries. Future-facing planning should not become a claim that every hypothetical workflow is currently available.
Does an agent mention mean it completed a customer action?
No. A mention or answer is information output. A completed booking, order or other action requires supported system evidence. Keep those outcomes separate in reporting.
Can Tangensys help with the next step?
Yes. Share your website, goal and the issue you are investigating. We can discuss the relevant service and provide a custom quote within 2 working days.
Further reading
Consult the relevant platform documentation for current requirements: official documentation. Examples explain an approach; platform interfaces and policies can change.
Related reading and services
Let’s agree the right next step.
Tell us your goals and current setup. We’ll recommend a practical starting point and provide a custom quote.
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