product-management
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ChineseProduct Management (Jan 2026)
产品管理（2026年1月）
This skill turns the assistant into an operator, not a lecturer.
Everything here is:
- Executable: templates, checklists, decision flows
- Decision-first: measurable outcomes, explicit trade-offs, clear ownership
- Organized: resources for depth; templates for immediate copy-paste
Modern Best Practices (Jan 2026):
- Evidence quality beats confidence: label signals strong/medium/weak; write what would change your mind.
- Outcomes > output: roadmaps are bets with measurable impact and guardrails, not feature inventories.
- Metrics must be defined (formula + timeframe + data source) to be actionable.
- Privacy, security, and accessibility are requirements, not afterthoughts.
- Hybrid decision loops: AI surfaces anomalies, patterns, and forecasts; humans apply context, ethics, and long-term strategy.
- Accountability: product is often held responsible for business outcomes; confirm the operating model in your org and validate benchmarks with current sources.
- Portfolio diversification: a common heuristic is 70% core, 20% adjacent, 10% transformational; adapt to strategy and constraints.
该技能可将助手转变为实操执行者，而非讲师。
这里的所有内容均具备以下特点：
- 可落地执行：模板、清单、决策流程
- 决策导向：可衡量的成果、明确的取舍、清晰的责任人
- 结构清晰：深度资源参考；可直接复制粘贴使用的模板
2026年1月现代最佳实践:
- 证据质量胜于主观信心：标记信号为强/中/弱；记录会改变你决策的因素。
- 成果优先于产出：路线图是带有可衡量影响和约束条件的赌注，而非功能清单。
- 指标必须明确定义（公式+时间范围+数据源）才能具备可操作性。
- 隐私、安全和可访问性是必备要求，而非事后补充项。
- 混合决策循环：AI识别异常、模式和预测；人类结合上下文、伦理和长期战略做决策。
- 问责制：产品团队通常需要为业务成果负责；确认你所在组织的运作模式，并通过当前数据源验证基准。
- 产品组合多元化：常见的启发式比例为70%核心业务、20%相邻业务、10%转型业务；可根据战略和约束条件调整。
When to Use This Skill
何时使用该技能
Use this skill when the user asks to do real product work, such as:
- “Create / refine a PRD / spec / business case / 1-pager”
- “Turn this idea into a roadmap” / “Outcome roadmap for X”
- “Design a discovery plan / interview script / experiment plan”
- “Define success metrics / OKRs / metric tree”
- “Position this product against competitors”
- “Run a difficult conversation / feedback / 1:1 / negotiation”
- “Plan a product strategy / vision / opportunity assessment”
Do not use this skill for:
- Book summaries, philosophy, or general education
- Long case studies or storytelling
当用户需要完成实际产品工作时使用该技能，例如：
- “创建/完善PRD/规格文档/商业案例/单页摘要”
- “将这个想法转化为路线图” / “针对X的成果导向路线图”
- “设计发现计划/访谈脚本/实验计划”
- “定义成功指标/OKR/指标树”
- “针对竞争对手定位该产品”
- “开展困难对话/反馈/一对一沟通/谈判”
- “规划产品战略/愿景/机会评估”
以下情况请勿使用该技能：
- 书籍摘要、哲学探讨或通识教育
- 长篇案例研究或故事讲述
Quick Reference
快速参考
| Task | Template | Domain | Output |
|---|---|---|---|
| Discovery interview | | Discovery | Interview script with Mom Test patterns |
| Opportunity mapping | | Discovery | OST with outcomes, problems, solutions |
| Outcome roadmap | | Roadmap | Now/Next/Later with outcomes and themes |
| OKR definition | | Metrics | 1-3 objectives with 2-4 key results each |
| Product positioning | | Strategy | Competitive alternatives -> value -> segment |
| Product vision | | Strategy | From→To narrative with 3-5 year horizon |
| 1:1 meeting | | Leadership | Check-in, progress, blockers, growth |
| Post-incident debrief | | Leadership | Intent vs actual, root cause, action items |
| 任务 | 模板 | 领域 | 输出 |
|---|---|---|---|
| 用户发现访谈 | | 发现 | 包含Mom Test模式的访谈脚本 |
| 机会映射 | | 发现 | 包含成果、问题、解决方案的OST |
| 成果导向路线图 | | 路线图 | 包含成果和主题的“现在/下一步/未来”路线图 |
| OKR定义 | | 指标 | 1-3个目标，每个目标对应2-4个关键结果 |
| 产品定位 | | 战略 | 竞品替代方案→价值主张→目标细分群体 |
| 产品愿景 | | 战略 | 包含3-5年时间跨度的“从→到”叙事 |
| 一对一会议 | | 领导力 | 进度跟进、工作进展、障碍排查、个人成长 |
| 事后复盘 | | 领导力 | 预期与实际对比、根本原因、行动项 |
Decision Tree: Choosing the Right Workflow
决策树：选择合适的工作流程
text
User needs: [Product Work Type]
├─ Discovery / Validation?
│ ├─ Customer insights? → Customer interview template
│ ├─ Hypothesis testing? → Assumption test template
│ └─ Opportunity mapping? → Opportunity Solution Tree
│
├─ Strategy / Vision?
│ ├─ Long-term direction? → Product vision template
│ ├─ Market positioning? → Positioning template (Dunford)
│ ├─ Big opportunity? → Opportunity assessment
│ └─ Amazon-style spec? → PR/FAQ template
│
├─ Planning / Roadmap?
│ ├─ Outcome-driven? → Outcome roadmap (Now/Next/Later)
│ ├─ Theme-based? → Theme roadmap
│ └─ Metrics / OKRs? → Metric tree + OKR template
│
└─ Leadership / Team Ops?
├─ 1:1 meeting? → 1-1 template
├─ Giving feedback? → Feedback template (SBI model)
├─ Post-incident? → A3 debrief
└─ Negotiation? → Negotiation one-sheet (Voss)text
用户需求：[产品工作类型]
├─ 发现/验证？
│ ├─ 客户洞察？ → 客户访谈模板
│ ├─ 假设测试？ → 假设验证模板
│ └─ 机会映射？ → 机会解决方案树（OST）
│
├─ 战略/愿景？
│ ├─ 长期方向？ → 产品愿景模板
│ ├─ 市场定位？ → 定位模板（Dunford模型）
│ ├─ 重大机会？ → 机会评估
│ └─ 亚马逊风格规格？ → PR/FAQ模板
│
├─ 规划/路线图？
│ ├─ 成果驱动型？ → 成果导向路线图（现在/下一步/未来）
│ ├─ 主题型？ → 主题路线图
│ └─ 指标/OKR？ → 指标树 + OKR模板
│
└─ 领导力/团队运营？
├─ 一对一会议？ → 1对1模板
├─ 反馈沟通？ → 反馈模板（SBI模型）
├─ 事后复盘？ → A3复盘模板
└─ 谈判？ → 谈判单页（Voss模型）Do / Avoid (Jan 2026)
应做/不应做（2026年1月）
Do
应做
- Start from the decision: what are we deciding, by when, and with what evidence.
- Define metrics precisely (formula + timeframe + data source) and add guardrails.
- Use discovery to de-risk value before building; prioritize by evidence, not opinions.
- Write “match vs ignore” competitive decisions, not feature grids.
- 从决策出发：我们要做什么决策、截止时间、依据什么证据。
- 精确定义指标（公式+时间范围+数据源）并添加约束条件。
- 在开发前通过发现环节降低价值风险；根据证据优先级排序，而非主观意见。
- 记录“匹配/忽略”竞品的决策，而非功能对比表格。
Avoid
不应做
- Roadmap theater (shipping lists) without outcomes and learning loops.
- Vanity KPIs (raw signups, impressions) without activation/retention definitions.
- “Build-first validation” (shipping MVPs without falsifiable hypotheses).
- Collecting customer data without purpose limitation, retention, and access controls.
- 无成果和学习循环的“路线图表演”（仅罗列待发布功能）。
- 虚荣指标（原始注册量、曝光量），未定义激活/留存标准。
- “先开发后验证”（发布MVP但无可证伪假设）。
- 无目的限制、留存规则和访问控制地收集客户数据。
What Good Looks Like
优秀标准
- Evidence: 5–10 real user touchpoints or equivalent primary data for material bets.
- Scope: clear non-goals and acceptance criteria that can be tested.
- Learning: post-launch review with metric deltas, guardrail impact, and next decision.
- 证据：重大决策需具备5-10次真实用户接触或等效的一手数据。
- 范围：明确的非目标和可测试的验收标准。
- 学习：发布后复盘需包含指标变化、约束影响和后续决策。
PRDs and Specs
PRD与规格文档
For PRDs/specs and writing-quality requirements, use the templates in :
../docs-ai-prd/- PRD templates: ../docs-ai-prd/assets/prd/prd-template.md and ../docs-ai-prd/assets/prd/ai-prd-template.md
如需PRD/规格文档及高质量写作要求，请使用中的模板：
../docs-ai-prd/- PRD模板：../docs-ai-prd/assets/prd/prd-template.md 和 ../docs-ai-prd/assets/prd/ai-prd-template.md
Optional: AI / Automation
可选：AI/自动化
Use only when explicitly requested and policy-compliant.
- AI system lifecycle: assets/ai/ai-lifecycle-template.md
- Agentic workflow docs: assets/ai/agentic-ai-orchestration.md
- AI product patterns: references/ai-product-patterns.md
仅在明确请求且符合政策时使用。
- AI系统生命周期：assets/ai/ai-lifecycle-template.md
- 智能代理工作流文档：assets/ai/agentic-ai-orchestration.md
- AI产品模式：references/ai-product-patterns.md
Navigation
导航
Resources
- references/discovery-best-practices.md
- references/roadmap-patterns.md
- references/delivery-best-practices.md
- references/strategy-patterns.md
- references/positioning-patterns.md
- references/data-product-best-practices.md
- references/interviewing-patterns.md
- references/metrics-best-practices.md
- references/leadership-decision-frameworks.md
- references/operational-guide.md
- data/sources.json
Templates
- Discovery: assets/discovery/customer-interview-template.md, assets/discovery/assumption-test-template.md, assets/discovery/opportunity-solution-tree.md
- Strategy/Vision: assets/strategy/product-vision-template.md, assets/strategy/opportunity-assessment.md, assets/strategy/positioning-template.md, assets/strategy/PRFAQ-template.md
- Data: assets/data/data-product-canvas.md
- Roadmaps: assets/roadmap/outcome-roadmap.md, assets/roadmap/theme-roadmap.md
- Metrics: assets/metrics/metric-tree.md, assets/metrics/okr-template.md
- Ops/Leadership: assets/ops/1-1-template.md, assets/ops/feedback-template.md, assets/ops/a3-debrief.md, assets/ops/negotiation-one-sheet.md
Related Skills
- ../docs-ai-prd/SKILL.md — PRD, stories, and prompt/playbook templates
- ../software-architecture-design/SKILL.md — System design guidance for specs and PRDs
- ../software-frontend/SKILL.md — UI implementation considerations for product specs
- ../software-backend/SKILL.md — Backend/API implications of product decisions
资源
- references/discovery-best-practices.md
- references/roadmap-patterns.md
- references/delivery-best-practices.md
- references/strategy-patterns.md
- references/positioning-patterns.md
- references/data-product-best-practices.md
- references/interviewing-patterns.md
- references/metrics-best-practices.md
- references/leadership-decision-frameworks.md
- references/operational-guide.md
- data/sources.json
模板
- 发现：assets/discovery/customer-interview-template.md, assets/discovery/assumption-test-template.md, assets/discovery/opportunity-solution-tree.md
- 战略/愿景：assets/strategy/product-vision-template.md, assets/strategy/opportunity-assessment.md, assets/strategy/positioning-template.md, assets/strategy/PRFAQ-template.md
- 数据：assets/data/data-product-canvas.md
- 路线图：assets/roadmap/outcome-roadmap.md, assets/roadmap/theme-roadmap.md
- 指标：assets/metrics/metric-tree.md, assets/metrics/okr-template.md
- 运营/领导力：assets/ops/1-1-template.md, assets/ops/feedback-template.md, assets/ops/a3-debrief.md, assets/ops/negotiation-one-sheet.md
相关技能
- ../docs-ai-prd/SKILL.md — PRD、用户故事及提示词/剧本模板
- ../software-architecture-design/SKILL.md — 规格文档和PRD的系统设计指导
- ../software-frontend/SKILL.md — 产品规格的UI实现考量
- ../software-backend/SKILL.md — 产品决策对后端/API的影响
Operational Guide
实操指南
See references/operational-guide.md for detailed patterns, template walkthroughs, example flows, and execution checklists. Keep SKILL.md as the navigation hub; use assets/ when producing artifacts.
如需详细模式、模板演练、示例流程和执行清单，请查看references/operational-guide.md。请将SKILL.md作为导航枢纽；在生成交付物时使用assets/下的内容。
External Resources
外部资源
See data/sources.json for official frameworks (Lean Startup, OST, PR/FAQ, OKRs) and AI/LLM safety references.
Use the quick reference and decision tree above to choose a template, then follow the operational guide for depth.
如需官方框架（精益创业、OST、PR/FAQ、OKRs）及AI/LLM安全参考，请查看data/sources.json。
使用上述快速参考和决策树选择合适的模板，然后参考实操指南获取详细内容。
Trend Awareness Protocol
趋势感知协议
IMPORTANT: When users ask recommendation questions about product management tools, frameworks, or practices, use a web search tool to check current trends before answering. If web search is unavailable, use and state clearly what you verified vs assumed.
data/sources.json重要提示：当用户询问产品管理工具、框架或实践的推荐时，请先使用网络搜索工具查看当前趋势再作答。若无法进行网络搜索，请使用中的内容，并明确说明哪些内容是已验证的、哪些是假设的。
data/sources.jsonTrigger Conditions
触发条件
- "What's the best tool for [roadmapping/product analytics/discovery]?"
- "What should I use for [OKRs/metrics/customer feedback]?"
- "What's the latest in product management?"
- "Current best practices for [discovery/roadmaps/prioritization]?"
- "Is [framework/tool] still relevant in 2026?"
- "[Linear] vs [Jira] vs [other]?" or "[Amplitude] vs [Mixpanel]?"
- "Best approach for [AI product management/agentic products]?"
- “[路线图/产品分析/发现]的最佳工具是什么？”
- “[OKRs/指标/客户反馈]应该用什么工具？”
- “产品管理的最新趋势是什么？”
- “[发现/路线图/优先级排序]的当前最佳实践是什么？”
- “[框架/工具]在2026年还适用吗？”
- “[Linear] vs [Jira] vs [其他工具]？” 或 “[Amplitude] vs [Mixpanel]？”
- “[AI产品管理/智能代理产品]的最佳方法是什么？”
Required Searches
必做搜索
- Search:
"product management best practices 2026" - Search:
"[specific tool] vs alternatives 2026" - Search:
"product management trends January 2026" - Search:
"[discovery/roadmap/OKR] frameworks 2026"
- 搜索：
"product management best practices 2026" - 搜索：
"[特定工具] vs alternatives 2026" - 搜索：
"product management trends January 2026" - 搜索：
"[discovery/roadmap/OKR] frameworks 2026"
What to Report
需汇报内容
After searching, provide:
- Current landscape: What PM tools/frameworks are popular NOW
- Emerging trends: New tools, methods, or patterns gaining traction
- Deprecated/declining: Frameworks/tools losing relevance
- Recommendation: Based on fresh data, not just static knowledge
搜索完成后，提供以下信息：
- 当前格局：目前流行的PM工具/框架有哪些
- 新兴趋势：正在兴起的新工具、方法或模式
- 已淘汰/衰退：正在失去相关性的框架/工具
- 推荐建议：基于最新数据，而非仅依赖静态知识
Example Topics (verify with fresh search)
示例主题（需通过最新搜索验证）
- Product management tools (Linear, Productboard, Notion, Coda)
- Analytics platforms (Amplitude, Mixpanel, PostHog)
- Discovery and research tools (Maze, UserTesting, Dovetail)
- Roadmapping approaches (outcome-based, theme-based, now/next/later)
- AI product management patterns
- Prioritization frameworks (RICE, ICE, opportunity scoring)
- OKR and metrics tools
- 产品管理工具（Linear, Productboard, Notion, Coda）
- 分析平台（Amplitude, Mixpanel, PostHog）
- 发现与研究工具（Maze, UserTesting, Dovetail）
- 路线图方法（成果导向、主题导向、现在/下一步/未来）
- AI产品管理模式
- 优先级排序框架（RICE, ICE,机会评分）
- OKR和指标工具",