justin-sun-perspective
Provides a Justin Sun-inspired perspective for analyzing crypto industry trends, business decisions, competitive strategy, regulation, attention economics, and entrepreneurial cho…
Guides accountable technical leads through discovery, framing, implementation, deployment, adoption, measurement, and generalization for ambiguous stakeholder engagements.
Guide embedded technical engagements from ambiguous stakeholder need through discovery, framing, hypothesis, build, evaluation, deployment, adoption, measurement, and generalization while preserving evidence, decision rights, and field learning. Use when one accountable technical lead must carry continuity across customer or stakeholder discovery, implementation, production fit, adoption, and measurable outcomes. Do not use for a bounded repository change, product investment governance, ongoing reliability or platform ownership, an isolated specialist task, or advisory work that ends before implementation and adoption.
AGENTS.md
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evals/evals.json
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manifest.yaml
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README.md
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templates/adoption-scorecard.md
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templates/assumptions-decisions-risks-ledger.md
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templates/engagement-charter.md
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templates/engagement-status.md
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templates/evaluation-and-release-decision.md
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templates/field-learning-record.md
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templates/outcome-measurement-record.md
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templates/productization-record.md
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templates/stage-handoff-record.md
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templates/stakeholder-workflow-map.md
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Reference
references/adoption-and-measurement.md
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references/authority-and-escalation.md
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references/communication.md
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references/discovery-brief.md
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references/generalization-and-productization.md
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references/lifecycle-and-artifacts.md
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references/route-selection.md
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references/source-index.md
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references/worked-example-engagement.md
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SKILL.md
SKILL.md
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Provides a Justin Sun-inspired perspective for analyzing crypto industry trends, business decisions, competitive strategy, regulation, attention economics, and entrepreneurial cho…
Provides a methodology for designing and operating AI governance programs, including risk tiering, lifecycle controls, accountability, compliance mapping, agent reviews, GxP overl…
Helps agents design and run product governance through decision rights, review cadences, evidence standards, operating patterns, exception records, and escalation paths.
Helps evaluate whether AI-enabled workflows should be adopted, scaled, constrained, redesigned, or retired using outcome evidence, countermetrics, full operating costs, uncertaint…
Helps agents compare intended and observed product outcomes, update evidence-backed assumptions, assess feature health, choose lifecycle actions, and plan retirement with migratio…
Guides end-to-end product experiments by mapping assumptions, selecting appropriate test methods, defining guardrails and decision rules, and recording readouts that update produc…
Helps coordinate multi-project technical programs by defining mandates, aligning dependencies and capacity, governing risks and decisions, tracking benefits, managing adoption, an…
A platform-agnostic method for comparing evidence-based current and target states, explaining gaps and uncertainty, prioritizing interventions, and producing traceable registers, …