「ai-era」の検索結果

Playbook for designing SaaS and startup products that convert, retain, and monetize — landing pages & CRO, checkout & forms, onboarding/activation, churn reduction, pricing psychology, dashboards, behavioral-science tactics, feature discipline, positioning/ICP, go-to-market, and AI-era differentiation. Use when advising on product design, UX, conversion, landing pages, checkout, onboarding, trials, pricing, retention/churn, growth, or positioning for a startup or SaaS. Distilled from product designer Richard (@richardrx). Not for use on gambling, betting, or casino products.

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Revenue-Centric Design (RCD) — evidence-backed principles for making a SaaS or startup product convert, retain, and monetize. Use when the user works on a landing page or CRO ("my page isn't converting"), onboarding/activation ("users sign up but don't stick"), churn/retention ("customers keep canceling"), pricing/monetization ("how should I price this"), checkout/forms ("dropdowns kill conversion", "annotated checkout"), dashboards/data viz ("cognitive load", "KPI shortlists"), positioning/ICP/go-to-market, feature scope, A/B-test rigor, or AI-era differentiation — or asks for the behavioral-science mechanism behind a design choice. Also use when another skill needs the principle or evidence behind a conversion/retention/pricing/checkout move. Never apply to gambling, betting, or casino products.

日本語の概要は準備中です。原文の説明を表示しています。

Operating doctrine for AI-era enterprise sales. Use when an agent works on accounts, deals, outreach, coaching, or pipeline — any revenue-affecting decision.

日本語の概要は準備中です。原文の説明を表示しています。

Research UI component patterns across the component.gallery corpus — 60 canonical component types, ~95 production design systems, 2,600+ examples — plus an AI-era overlay (prompt inputs, tool-call cards, streaming status, citations) and composite patterns (command palette, app shell, agent console). Compare implementations, find alternative component names, ground frontend decisions in real-world precedent. Pairs with minoan-frontend-design for research-then-build workflows. Triggers on component patterns, how do others implement X, design system research, component comparison, AI chat components, agent UI patterns.

日本語の概要は準備中です。原文の説明を表示しています。

专为追求倍速增长的初建学校设计的教师选、育、用、留四环节体系。基于科德高中融合部真实管理经验，结合十部AI Agent架构，将人才管理从校长个人经验升级为可继承、可协同、可沉淀的组织能力。

日本語の概要は準備中です。原文の説明を表示しています。