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Informational Fresh jira_story: GOV-132

Lesson 3 of 7 — Task detail with activity and evidence

Governance Workspace Core · Source: Jira Story GOV-132 (5 pts) · Authority: Informational (the Jira story is authoritative).

Purpose

Capture evidence and activity against a task with integrity.

Why it matters

Evidence hashing makes the trail tamper-evident and audit-ready.

Where this lives

Runs in the Customer AI Governance platform (components: workspace). Uploads are hashed (sha256) and recorded; status advances to Evidence Submitted; comments are append-only. Learn teaches this read-only.

Workflow

  1. Given an open task
  2. When evidence is uploaded
  3. Then its sha256 is recorded, status becomes Evidence Submitted, and comments append

Worked example

Evidence is uploaded but no hash is stored. Why is that a problem?

Without the sha256 the evidence isn't tamper-evident, so it can't be defended in audit.

Acceptance criteria (authoritative — GOV-132)

Given an open task, when evidence is uploaded, then its sha256 is recorded, status becomes Evidence Submitted, and comments append.

Common pitfalls

  • Storing evidence without hashing, losing integrity and defensibility.

Knowledge check

  • Scenario: Evidence is uploaded but no hash is stored. Why is that a problem?
  • Look for: Without the sha256 the evidence isn't tamper-evident, so it can't be defended in audit.

Key concepts

  • sha256 evidence
  • Evidence Submitted
  • append-only comments

For the AI Tutor

  • Summary: Capture evidence and activity against a task with integrity.
  • When to use: teaching or answering questions about "task detail with activity and evidence".
  • When NOT to use: the SoD rule that governs who may validate (that is GOV-133).
  • Key concepts: sha256 evidence, Evidence Submitted, append-only comments.

Completion criteria

Learner passes the scenario knowledge check and can point to the system state that satisfies GOV-132's acceptance criterion.

  • Module: LEARN-MOD-003 (Governance Workspace Core)
  • Provenance: LEARN-MAP-001 · Generation standard: LEARN-STD-002
  • Next: LEARN-LSN-018
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