Task framing

What exactly should AI do—and should it do it at all?

Decide whether AI belongs in the task, choose who controls each next step, then define behavior you can test with real inputs and a human fallback.

AI VISTA / DECISION01 / 03

WORKING DECISIONA good candidate has variable input, a checkable output, bounded stakes, and a fallback a person can use.

01INPUT

02CHECK

03BOUNDARY

RETURN TO THE REAL TASK✓

DECISION BRANCH

Answer the decision this topic actually owns.

ASK FIRST↓
Can the request become one action with real inputs, acceptable output, and a named owner?
IF↓
Inputs vary, results can be checked, and failure costs are bounded: test AI on a small set of real cases.
OTHERWISE✓
Use rules, retrieval, or the current human process first; do not hand an entire role to AI.

WORKED CASE

Which part of support triage should actually be automated?

A team receives about 900 messages a week and wants AI to identify intent, assign a queue, and send replies. Those three actions carry different consequences but appear in the brief as one task: ‘automate support email.’

WORKING ARTIFACTAn action-boundary sheet mapping every step to its input, consequence, authority, and fallback.

01WEAK SHORTCUT

Treat the entire workflow as suitable because it is repetitive and high-volume, with saved time as the only justification.

02BETTER JUDGMENT

Separate reading, judging, routing, drafting, and sending. Begin with reversible classification suggestions and drafts; keep mixed intent, sensitive data, and refund commitments with a person.

03ACCEPTANCE

Review 50 historical messages and 10 boundary cases. Mixed-intent cases never auto-send, sensitive fields stay out of the model, and reviewers can see the rationale and handoff route.

ENTRY & EXIT SIGNALS

Know when to enter—and when the decision is good enough to leave.

A topic is not an endless knowledge directory. Entry signals tell you whether the problem belongs at this layer. Exit signals decide whether to continue instead of substituting time spent reading for work completed.

AI VISTA / DECISION STATUSTask framing

01ENTER HERE

The request still says ‘use AI for efficiency’
Actions with different consequences are bundled into one task
Acceptable output and human handoff are missing

02LEAVE WHEN

The AI action can be named with one precise verb
Input, boundary, failure consequence, and owner are explicit
A small set of real cases can support continue or stop

4 PRACTICES

Build the judgment, make the artifact, then review it with real cases.

01 Should this task use AI at all?Judge a task by variation, verifiability, stakes, data boundaries, and fallback before choosing a model or building a workflow. Task framing 02 Turn an AI idea into a testable task briefReplace a vague AI feature request with a one-page brief that names the user, input, acceptable output, evidence, boundaries, and fallback. Task framing 03 Workflow or AI agent? Choose the control loop before buildingDecide when a fixed AI workflow is enough and when an agent needs bounded control, tool feedback, stop rules, and a human handoff. Task framing 04 Draw the data boundary before AI sees the inputRoute every field through allow, transform, isolate, or exclude so a useful workflow does not quietly become an uncontrolled data transfer. Task framing

BOUNDARY

What this topic page will not do

This topic scopes an AI-assisted step; it is not a compliance certification for legal, medical, employment, financial, or other high-stakes decisions.

01Keep deterministic rules for hard gates02Do not let a language model approve consequential actions alone03Do not scale without a human owner who can finish the case

When the action, boundary, owner, and fallback are explicit, carry the task brief into the context topic.

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