Use when evaluating an AI idea, AI concept, or early-stage AI proposal — before any pilot design or investment decision. Phrases like "should we pursue this AI idea?", "is this AI concept worth exploring?", "does this AI use case make sense?", "we're thinking about building AI for X — is it a good idea?" all trigger this skill. Diagnoses using a five-role framework — Investigator (real friction), Devil's Advocate (right solution mode), Long-term Strategist (value accumulates), Realist (right capability), Senior Advisor (synthesis verdict). Outputs Fund / Fund-with-condition / Reframe / Kill.
Use when approving or rejecting an AI investment proposal, greenlighting an AI program for funding, evaluating whether an AI initiative should proceed to production, or reviewing an AI business case before board or executive sign-off. Phrases like "should we fund this AI project?", "run the ROI gate on this", "is this AI investment justified?", "we're about to approve AI spending for X", "help me evaluate this AI business case" all trigger this skill. Runs PwC's 20-item Do's-and-Don'ts checklist plus a three-channel ROI model and objective-mode audit. Outputs an approval recommendation with named conditions and red flags.
Use when frontline experts — clinicians, investigators, lawyers, engineers, customer agents — fear AI replacement, deskilling, or accountability shift, and the rollout is stalling on resistance rather than tech. Phrases like "clinicians are afraid AI will replace them", "the team thinks this is automation in disguise", "senior staff are blocking the AI pilot", "we need buy-in from the frontline before we deploy", all trigger this skill. Runs a five-role engagement protocol — empathic listening, jagged-frontier task split, co-design workshop, psychological-safety contract, tradecraft protection — that turns the threatened expert into the co-author of the augmentation. Outputs an Engagement Plan, an AI-leads/Human-leads/Hybrid/Off-limits task split, and a written Safety Contract.
Use when assessing an organization's leadership readiness for AI transformation, surfacing where people and leadership gaps will block AI progress, preparing for a leadership team AI conversation, or diagnosing why AI investments aren't creating value despite good technology. Phrases like "is our leadership team ready for AI?", "surface AI readiness gaps in our leadership team", "help me understand where our people gaps are on AI", "prepare me for a leadership team AI conversation", "why aren't we getting value from AI despite our investment?", "assess AI readiness in our organization" all trigger this skill. Runs a four-role gap analysis (CEO / Manager / Employee / HR) with diagnostic questions for each role. Outputs a 4-role gap report with specific actions per gap.
Use when choosing which AI tool to put in front of a specific user group — a training cohort, a team, a school, a department — or deciding whether to teach deeper prompting, extend existing tools with agent skills, or introduce a new tool. Phrases like "which AI tool should I teach this group?", "choosing an AI tool for our teachers / nurses / analysts", "should I teach advanced prompting or a new tool?" all trigger this skill. Runs six roles — Audience Profiler, Constraint Mapper (hard eliminators before any capability comparison), Intervention-Mode Selector (Deepen / Extend / Introduce), Capability-Delta Assessor, First-Win Realist, Synthesis. Outputs Adopt-now / Adopt-with-scaffolding / Pilot-with-subgroup / Skip plus a growth path. For build/buy/partner sourcing of an AI capability use tech-buy-vs-build; for enterprise-wide curriculum design use people-literacy-curriculum.
Use when designing an AI pilot, structuring a proof-of-concept, or preparing to test an AI idea before full investment. Phrases like "how should we structure this pilot?", "what does a 90-day AI pilot look like?", "help me design the test for this AI initiative?", "we want to pilot AI for X — what do we need?", "what metrics should we track?" all trigger this skill. Runs a structured 7-question pilot design protocol: scope, problem, pre-deployment metrics, blast radius, stop conditions, workflow redesign, ownership. Outputs a one-page pilot brief ready for sponsor approval.
Use when an enterprise has shipped AI agents but cannot see usage, cost, or ROI at the portfolio level. Phrases like "we deployed agents but can't see them", "unclear ROI on our AI", "token spend is exploding", "governance dashboard for AI", "how do we track agent performance", "what's the net ROI after oversight" all trigger this skill. Builds a three-layer KPI tree, dashboard spec, and review cadence that subtracts human-oversight cost from gross gains — outputs a portfolio observability blueprint with sunset criteria and an Observable-and-governed / Partial-observability / Black-box verdict.
Use when deploying an AI agent, reviewing agentic AI governance, checking whether an AI agent deployment is safe and well-governed, or assessing whether an organization's oversight of autonomous AI systems is adequate. Phrases like "check the governance on this agent deployment", "is our agentic AI safe to deploy?", "review guardrails for this AI agent", "we're about to launch an AI agent — what do we need to have in place?", "help me assess our agentic AI oversight" all trigger this skill. Runs IMDA's four-dimension agentic governance check across risk bounding, human accountability, technical controls, and end-user responsibility. Outputs a governance readiness assessment with gaps and required actions.