name: ai-initiative-diagnostic description: Use whenever evaluating an AI initiative, AI investment thesis, AI pilot proposal, or proposed AI deployment. Diagnoses using a five-role framework — Investigator, Devil's Advocate, Long-term Strategist, Realist, Senior Advisor — built around four questions: Real Friction, Right Solution Mode, Value Accumulates, Right Capability. Trigger this skill any time someone is considering whether to build, buy, fund, or kill an AI initiative, even if they don't explicitly ask for a diagnostic.

AI Initiative Diagnostic

Diagnose AI initiatives in five sequential roles. Maintain all prior reasoning as state — each role builds on the previous role's output.

After each role, output a clearly labeled section, then proceed to the next role. Do not stop until all five are complete.

Role 1: Investigator (Q1 — Real Friction?)

NAME WHO FEELS THE PAIN. Who specifically experiences the problem? What does it cost them — in time, money, quality, or risk?

CLASSIFY THE STARTING POINT.

Friction-first: "Our customers / teams struggle with [specific thing]"
Tech-first: "We should use AI for [task]"

State which — and quote the language that signals it.

FRICTION STATEMENT. If friction-first: state the pain in one sentence. If tech-first: flag this as a warning sign and identify the real friction before proceeding.

Output: WHO FEELS THE PAIN | WHAT IT COSTS | FRICTION-FIRST OR TECH-FIRST | PAIN STATEMENT

Role 2: Devil's Advocate (Q2 — Right Solution Mode?)

Your job is to find where this breaks, not where it succeeds.

RELIABILITY TEST. "Would I be comfortable if this output reached the end consequence — the customer, the regulator, the judge — without human review?" Yes or no. Name the consequence of an error.

OPERATIONAL-MODE CHECK. Strip out the human-in-loop language from the pitch. In the moment the output reaches the end party, is a human actually between the AI and them? If no, the initiative is operationally Replace regardless of how it is described.

CONSEQUENCE LEVEL CHECK. Does this application handle tasks or queries of different consequence levels? If yes, the most consequential type sets the mode for the whole application.

ERROR LOOP.

No one catches errors → Replace mode. Name the risk.
Human in loop by design → Augment mode. Name their role.
AI enables what structurally couldn't exist before → Create mode.

MODE VERDICT. State: Replace / Augment / Create. State the single condition that must hold. Flag if it is not yet met.

Role 3: Long-term Strategist (Q3 — Value Accumulates?)

WHAT ACCUMULATES? Assess all three dimensions. A gap on any one produces Fund-with-condition, not Fund.

(a) Gets better — does the solution improve as it is used, through data accumulation, model learning, or network effects? A solution that plateaus on day one is a productivity tool. (b) Switching costs — how costly is it for a user or organisation to leave? High accumulation with low switching costs is still vulnerable. (c) Competitive preference — do users actively choose this over alternatives, or do they tolerate it because leaving is expensive? Locked-in users who route around the tool in practice produce low actual adoption despite high nominal retention.

Name which dimensions pass and which do not. Specify what accumulates and why it is hard to reconstruct.

MEASUREMENT CHECK — THE KLARNA WARNING. Name three metrics that prove this is working. Are these the metrics that would naturally get tracked? Flag any gap between what matters and what is easy to measure.

BLAST-RADIUS CHECK. If this fails on day one, who sees it — internal users, paying customers, regulators, or the public? Pick the worst plausible. Adjust the reliability bar accordingly.

Output: WHAT ACCUMULATES | THREE METRICS | MEASUREMENT GAP | BLAST RADIUS

Role 4: Realist (Q4 — Right Capability?)

Your job is to identify the execution gaps that would prevent this initiative from working in practice, regardless of how sound the concept is.

DATA. Is the data AI-ready? Does the organisation have confirmed legal rights to use it?

INTEGRATION. Is there a plan to connect the AI output to real operational workflows — including what happens when the AI is wrong?

Output: DATA | INTEGRATION | Q4 VERDICT (Pass / Gaps / Fail)

Role 5: Senior Advisor (Synthesis)

Read the outputs of Roles 1–4. Produce the verdict. Do not introduce new assessment here.

Write for a board audience. Be direct.

VERDICT: [Fund / Fund-with-condition / Reframe / Kill] MODE: [Replace / Augment / Create]

Q1 — REAL FRICTION? (2 sentences) Q2 — RIGHT SOLUTION MODE? (2 sentences) Q3 — VALUE ACCUMULATES? (2 sentences) Q4 — RIGHT CAPABILITY? (2 sentences)

STRONGEST LINK: Where this idea is most solid. WEAKEST LINK: Where this idea is most at risk of failing silently. ONE CHANGE: Specific action — not a general recommendation.

CLOSEST REFERENCE CASE: Match against the cases in cases/ and name the parallel explicitly.

Reference Cases

See cases/ for diagnosed examples. When diagnosing a new initiative, compare against the closest reference case and note the parallel explicitly.

name: ai-initiative-diagnostic description: Use whenever evaluating an AI initiative, AI investment thesis, AI pilot proposal, or proposed AI deployment. Diagnoses using a five-role framework — Investigator, Devil's Advocate, Long-term Strategist, Realist, Senior Advisor — built around four questions: Real Friction, Right Solution Mode, Value Accumulates, Right Capability. Trigger this skill any time someone is considering whether to build, buy, fund, or kill an AI initiative, even if they don't explicitly ask for a diagnostic.