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CHU / CASE 001

FollowUp

A case study in making follow-up actions clearer and more consistent.

Case status
Recorded
Work type
MVP product build
Updated

Result boundary

The implementation establishes a clearer workflow boundary; business impact has not been measured.

System map

FollowUp state loop
01Lead
02Next action
03Reminder
04Complete
05Next action

Next action

A recorded follow-up workflow map: Lead → Next action → Reminder → Complete → Next action

Context

Follow-up work needed a focused product workflow that could be reviewed as it evolved.

Problem

Follow-up actions become inconsistent and leads can be lost.

Constraints

MVP discipline, shared action logic, and no unnecessary dependencies were required.

Decisions

Keep action logic shared and make each state transition explicit before adding more surface area.

Architecture or workflow

A focused workflow separates the follow-up state from surrounding product presentation.

What was built

FollowUp is documented as an evidence-led MVP case study. The emphasis is on making the next action understandable and reviewable while the product is still being shaped.

Verification

State-transition checks and automated tests provide reviewable evidence; no business benchmark is claimed.

Evidence artifacts

  • Evidence type: State transitions, automated tests, and product workflow.
  • Artifact type: Product workflow record
  • Implemented screens, state transitions, automated tests, and iterative product development are the available evidence sources.

What is not proven

No user, conversion, revenue, or lead-recovery outcome is claimed.

What changed / learned

Reliability and workflow clarity create more value than decorative AI features.

Next step

How I Validate AI Products Before Expanding Them