Agent plan preview
An AI agent or automation can show a proposed multi-step plan before execution.
- Type
- UI-UX
- Sources
- 6
- Trail checked
AI capability boundaries, agent control, source grounding, uncertainty, approval, and safe fallback.
Browse all problem familiesOpen an entry for its decision rule, states, implementation contract, and source trail.
An AI agent or automation can show a proposed multi-step plan before execution.
An agent or automation run has started and spans multiple steps, tools, gates, or side effects.
An AI agent or automation can create side effects that affect customers, money, access, production systems, legal status, public content, sensitive data, or external recipients.
A generated answer makes source-dependent claims but no source route is visible.
An AI product displays model certainty, extraction confidence, recommendation score, classifier probability, generated-answer confidence, retrieval rank, or risk score with precision the system cannot justify.
A user is introduced to an AI feature whose abilities, limits, data scope, uncertainty, or review needs are not obvious from the normal interface.
A generated AI output can influence compliance, customer communication, security, legal, finance, operations, code, policy, or other high-trust work.
Users need to create or edit automations that run later based on events, conditions, schedules, or record changes.
The user needs a back-and-forth assistant conversation with follow-up questions and answer refinement.
Users need to verify generated claims, summaries, recommendations, or extracted facts against source material.
Users must judge whether an AI prediction, classification, recommendation, extraction, risk score, or generated answer is reliable enough to use.
Users can identify wrong, unsupported, stale, unsafe, biased, irrelevant, or wrongly sourced AI output after it is generated.
Generated content is expected to be revised before it is copied, saved, sent, published, or applied.
Users need a person because AI, automation, self-service, or scripted support cannot resolve the situation safely or acceptably.
An AI agent, workflow, deployment, or automation is ready to perform a high-impact step and must pause for human authorization.
A model version, provider, lifecycle stage, availability, behavior, or replacement plan changes in a way users may need to understand or act on.
Users must write or revise an AI request before generation, analysis, transformation, or automation begins.
The AI surface supports open-ended requests and users need examples of useful, supported tasks.
A user needs another AI-generated answer for the same request or a visible recovery path after response failure.
A user's AI request has missing object, audience, timeframe, source, workspace, permission, output-depth, or action-target boundaries.
Users need answer-wide evidence coverage before trusting generated content.
Generated text or structured content can be read or monitored before completion.
An AI agent or automation calls tools, functions, APIs, retrieval systems, commands, or integrations.
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