Agentic AI systems don't just respond → they act. They execute multi-step workflows, make decisions that affect real people, and operate autonomously on behalf of organizations. That shift demands a new kind of design infrastructure.
Most AI interfaces are built to make systems feel capable and confident. They are not built to make those systems legible, interruptible, or accountable. RAD exists for the gap between what AI does and what humans need to understand, control, and trust.
RAD provides standardized, reusable UI components and interaction patterns for agentic experiences. These are surfaces that disclose AI involvement, support human oversight, and make autonomous behavior understandable at the moment it matters.
Every AI action is attributable. Systems surface what they did, on what basis, and under whose authority.
Human oversight is preserved. Consequential decisions require explicit human approval before execution.
AI involvement is never hidden. Systems identify themselves, their data sources, and their confidence levels.
Disclosure alerts, transparency popovers, bias check prompts, uncertainty indicators, confidence threshold warnings, algorithmic nudge disclosure.
7 componentsHuman-in-the-loop controls, impact assessment, agent state indicators, consent & scope gates, agent attention triggers, recovery & override controls, feedback & correction.
2 componentsAudit trail widgets and environmental impact indicators. Every agent run must produce a traceable, exportable log.
7 componentsEssential AI UI infrastructure: streaming text, loading states, error states, session management, prompt input, empty states, AI artifacts. Required plumbing for any AI interface.
4 componentsSuggested prompts, suggested next actions, prompt enhancement, task builder. Helps users understand what the interface can do.
4 componentsAgent activity timeline, tool execution log, collapsible agent steps, process vs result layout. Makes multi-step agent execution legible.
4 componentsContext sources, context pills, active memory panel, context scope selector. Surfaces and controls what information the AI has access to.
RAD is the original work of Jackie Curry. All rights reserved. No portion may be reproduced, adapted, or incorporated into any product or system without express written permission.
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© 2025 Jackie Curry. All rights reserved. Publication date: 2025.
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