platform-guideline 2 linked patterns checked
Responsible AI for Agent Design
Documents responsible AI principles for agents, including transparency, making capabilities and limitations clear, safety filters, accountability, privacy, security, and informed user decisions.
Read with a purpose
What this source can teach
Use this source to understand a platform convention and the setting it was designed for.
- Start with the original. Open the source and find the guidance or example relevant to your task.
- Trace the connection. Use the claim notes below to see how this site applies the source to specific patterns.
- Check the setting. Compare the source's platform, people, and constraints with your own decision.
Pattern Decisions This Source Supports
| Pattern | Supported decision | Required contract | Claim note |
|---|---|---|---|
| AI agent acts without approval | Flag this anti-pattern when an AI agent or automation executes a high-impact side effect without showing and requiring approval for the exact action and payload first. | The agent distinguishes read-only steps, draft steps, reversible local changes, and external side-effect steps before execution. | Supports transparency, safety, accountability, informed decisions, security, and privacy requirements for agent design. |
| AI limitation onboarding | Choose AI limitation onboarding when the user needs first-use or changed-capability orientation about AI benefits, limits, data scope, uncertainty, feedback, human responsibility, and fallback. | The onboarding explains what the AI can help with and what it is not able to do before the first risky use. | Supports transparency, capability and limitation disclosure, safety filters, accountability, and informed user decisions. |
Evidence Role
This source is treated as platform-guideline evidence. Its value comes from the specific claims and setting described above.
Publisher: Microsoft Learn. Last checked: .