Can use problem-statement authorship with a defined task, suitable inputs, and a basic validation check.
traditional skill · Stage 03
Problem-statement authorship
Anchor skill
Problem-statement authorship is an established design capability used to convert evidence into a specific, falsifiable problem worth solving. In TADF it remains a human foundation for evaluating, correcting, and contextualising AI output.
Why it matters
This is an anchor skill. Weakness here limits maturity for the entire Insight Generation stage because it protects the non-negotiable human checkpoint.
Stage outcome
Convert the Stage 02 fact base into a defined, ownable problem statement. Promoted to its own stage because problem framing is the highest-leverage human-judgment step in the process and was previously buried as a sub-bullet
What good looks like
01
Frames problem-statement authorship against a clear goal, relevant evidence, and the stage quality gate.
02
Applies the craft independently, then uses it to challenge or refine AI-generated work.
03
Documents the decision, trade-off, correction, or override so another designer can follow the reasoning.
Checkpoint application
Apply this skill before the Stage 03 gate is approved. The accountable designer must be able to explain how it changed the work, what evidence was considered, and why the result is safe to advance.
Common failure patterns
- Selecting the most polished framing rather than the one best supported by evidence.
- Allowing AI convenience to weaken an established craft practice that is still necessary for independent judgment.
- Recording the final artefact while omitting the rejected option, correction, trade-off, or override that explains the decision.
Five-minute practice
Use it on the work you already have.
Take one current insight generation artifact. Apply problem-statement authorship for five minutes, then record one AI contribution, one human correction, and the evidence that justified the final decision.
Evidence of capability
- A reviewed problem statement, framing rationale, or evidence trace showing the skill in use.
- A short rationale linking the decision to evidence, risk, and intended outcome.
- An example of an AI suggestion that was corrected, rejected, or deliberately accepted.
Leadership assessment questions
01
Can the designer demonstrate problem-statement authorship on a real insight generation decision?
02
What observable evidence distinguishes competent performance from confident explanation?
03
Would weakness in this skill make the human checkpoint ceremonial rather than protective?
Maturity ladder
Can diagnose weak output, redirect the work, combine sources, and explain the resulting trade-off.
Can decide when not to delegate, own the human checkpoint, and remain accountable for the outcome.
Backlinks and relationships