Toolkit

Design Debt Ledger

Name repeat drag as design debt before asking AI to accelerate it.

Design Debt Ledger

Capture observed drag as design debt before treating it as a tool request. The table stays in this browser until you export or clear it.

Sort ledger table

Debt type guide

Decision debt

Drag created when decision rights, decision criteria, or accountable owners are unclear.

A workflow stalls because teams know an approval is required but not who is empowered to make the decision.

Role debt

Drag created when roles, ownership, or accountability no longer match how work actually moves.

Managers absorb extra coordination labor because the process does not make ownership clear enough.

Process debt

Drag created by broken handoffs, unnecessary approvals, rework, escalation loops, or outdated process design.

Everyone is busy inside a process, but outcomes stay slow because work keeps looping back for clarification.

System debt

Drag created when systems record work without helping the work move reliably.

A system captures a transaction but teams still coordinate in side channels to make the work happen.

Data debt

Drag created by low data trust, weak lineage, inconsistent metrics, or manual reconciliation.

Three teams rebuild the same report because nobody trusts the official numbers.

Coordination debt

Drag created when teams need extra meetings, follow-up, escalation, or backchannels to compensate for unclear work design.

A manager maintains a shadow tracker because the formal workflow does not show what is really happening.

Incentive debt

Drag created when incentives reward local motion instead of system-level outcomes.

Teams optimize for ticket closure or launch activity while rework and downstream friction remain unresolved.

Trust debt

Drag created when people do not believe the process, data, tool, or decision enough to rely on it.

Employees use a side chat or spreadsheet because the official process is too slow or mistrusted.

Learning debt

Drag created when feedback, exceptions, patterns, and institutional knowledge are not captured for reuse.

The same issue repeats because the workflow has no feedback loop that improves the playbook.

AI-readiness debt

Drag created by workflow design gaps that make AI unsafe, unreliable, or low-value.

AI would help only after role clarity, process clarity, data trust, and human verification improve.

Decision debt: 0Role debt: 0Process debt: 0System debt: 0Data debt: 0Coordination debt: 0Incentive debt: 0Trust debt: 0Learning debt: 0AI-readiness debt: 0

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