Feature Kibble

What this snack represents

Tiny request. Massive chew time. For requirements that arrive small and leave wearing platform shoes.

Plain English: Small feature requests often expand through edge cases, approvals, review loops, and unclear acceptance criteria.

Formula: 30m clarification + 3h build + 1h review + 1h QA + 30m rework

What this teaches: Scope Creep, Acceptance Criteria, Hidden Work.

Why teams underestimate it

The shelf label works because the cost is usually hidden across clarification, review, context switching, QA, and follow-up decisions. BarkBowl makes those ingredients visible before the work is treated as free.

Time formula

30m clarification + 3h build + 1h review + 1h QA + 30m rework

Worked example

One serving of Feature Kibble is currently modeled at 6 hours, or 6 person-hours. Multiply servings when the work repeats, spreads across more people, or needs another review cycle.

Warning label

May grow if left near executives.

Evidence needed

Before committing this snack, collect an owner, a reason, a time formula, a rollback or no-op alternative, and a short explanation of what the receipt does and does not prove.

How to reduce the cost

Decision Memo Patties

No-op alternative

If evidence, authority, or capacity is missing, the mature move may be to record a no-op decision and revisit when the missing ingredient exists.

What this teaches

• Scope Creep
• Acceptance Criteria
• Hidden Work

Related lesson

scope-creep

Related field report

scope-creep

Related glossary terms

Scope Creep, Acceptance Criteria, Hidden Work

Related blueprint

Decision record starter · Open Blueprint Gallery

Copy decision-record starter

Decision: Consider Feature KibbleTime formula: 30m clarification + 3h build + 1h review + 1h QA + 30m reworkEvidence: [link or owner]
No-op alternative: [what happens if we do not act]
Boundary: This is a draft for human review, not an approval.
Reviewed at UTC: [timestamp]

Boundary note

This snack produces draft learning and time-burn evidence only; it does not approve fixes, validate credentials, train models, or certify safety.

Dogfooding notes

Exercises product snapshotting, time totals, TTL refresh, telemetry, learning translation, and checkout record creation.