deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Assign human decision rights, accountability, review, contribution, escalation, and evidence duties for a material AI product or recurring operating decision.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Measure whether AI operating practices change behavior, decisions, workflows, reuse, outcomes, burden, and risk rather than merely increasing activity.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Define evidence-based boundaries for what an AI system may do independently, with human approval, or never. Use before launch, scaling, or increasing AI authority.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Define expected, acceptable, and prohibited AI behavior with representative cases, thresholds, escalation, and consequences. Use before evaluation, launch, or autonomy decisions.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Turn an AI idea into an owned investment hypothesis with outcomes, economics, constraints, evidence, and a next learning test. Use before funding or expanding an initiative.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Diagnose role capability, applied learning, workflow adoption, stewardship, and outcome evidence; recommend the next capability-building motion rather than more generic training.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Design how AI context is created, retrieved, refreshed, versioned, reconciled, retained, expired, excluded, and retired for a recurring purpose.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Assemble a bounded, reusable context package with purpose, authoritative sources, constraints, decisions, examples, exclusions, and refresh rules. Use for recurring AI-assisted work.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Diagnose missing, stale, conflicting, inaccessible, excessive, sensitive, or untrusted context and recommend the next source, package, data, or lifecycle intervention.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Assess whether data is fit for a specific AI product decision across provenance, quality, access, representativeness, consent, privacy, freshness, and operations.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Redesign a recurring product decision cycle around evidence, context, human judgment, AI assistance, authority, feedback, and measurable learning.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Build an evidence-aware economic case for an AI investment across value, full lifecycle cost, uncertainty, alternatives, risk, and decision thresholds.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Define calibrated AI evaluation metrics, rubrics, judges, thresholds, sampling, uncertainty, ownership, and decision rules tied to behavior and consequences.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Recommend the product, model, workflow, human, and production evaluations needed for an AI decision, based on behavior, consequences, evidence gaps, and lifecycle stage.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Build a governed, representative AI evaluation set with provenance, expected behavior, edge cases, affected groups, adjudication, versioning, and limits.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Review one AI initiative across value, economics, dependencies, workflow, context, evaluation, governance, controls, capability, and recovery before a material decision.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Define evidence-based entry, continuation, pivot, scale, pause, and stop decisions for AI investments without turning gates into document approval theater.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Design a role-based applied learning system with real work, practice, coaching, peer feedback, progression, reinforcement, stewardship, and outcome evidence.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Assess AI product operating-model maturity across seven categories using evidence, disagreement, and critical-gap logic. Use to identify consequential gaps and next interventions.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Design and test a bounded AI product operating-model change across decisions, workflows, context, evidence, governance, capability, ownership, and adoption.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Review whether the AI product operating model improves decisions and outcomes, identify systemic friction and performative activity, and choose the next changes.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Convert evidence-based operating-model findings into an owned 30-, 90-, 180-, and 365-day sequence of interventions, learning milestones, dependencies, and decisions.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Frame an AI product opportunity around an evidenced condition, affected actors, consequences, alternatives, and the uncertainty that should be tested next.
deanpeters/ai-product-operating-model-skills
Skill Claude CodeCodex
Map how AI behavior may change user behavior, product outcomes, economic value, and risk while exposing causal assumptions and countermeasures.