docs: 新增附录「创意来源」章节并优化文档格式

docs/.vitepress/config.mjs

@@ -389,6 +389,10 @@ const productManagerSidebarEn = [
     text: 'Appendix: User Research and Validation',
     collapsed: false,
     items: [
+      {
+        text: 'Where to Find Ideas: 3 Beginner-Friendly Sources',
+        link: '/en/stage-1/appendix-idea-sources/'
+      },
       {
         text: 'Jobs to Be Done',
         link: '/en/stage-1/appendix-jobs-to-be-done/'

docs/en/stage-0/index.md

@@ -92,6 +92,11 @@ Master the Vibe Coding workflow, learn to deconstruct requirements, and independ
 - When you want to define the problem better before jumping into a solution
 
 <NavGrid>
+  <NavCard
+    href="/en/stage-1/appendix-idea-sources/"
+    title="Where to Find Ideas"
+    description="Use reference apps, trend sources, business signals, and VC lists to narrow down better product directions."
+  />
   <NavCard
     href="/en/stage-1/appendix-jobs-to-be-done/"
     title="Jobs to Be Done"

docs/en/stage-1/appendix-double-diamond/index.md

@@ -1,6 +1,6 @@
 ---
 title: 'Double Diamond: First Choose the Right Problem, Then Build the Right Solution'
-description: 'A beginner-friendly introduction to the Double Diamond. Learn when to explore the problem, when to narrow it down, and when to start comparing solutions and prototypes.'
+description: 'A beginner-friendly introduction to the Double Diamond. Understand Discover, Define, Develop, and Deliver so you do not rush into prototypes before the real problem is clear.'
 ---
 
 <script setup>
@@ -15,407 +15,535 @@ const duration = 'About <strong>1.5 hours</strong>'
 
 <ChapterIntroduction
   :duration="duration"
-  :tags="['Double Diamond', 'Design Thinking', 'Discovery', 'Problem Framing']"
+  :tags="['Double Diamond', 'Design Thinking', 'Demand Analysis', 'Solution Design']"
-  coreOutput="1 clearer problem definition and 1 better validation starting point"
+  coreOutput="1 clearer problem definition and 1 more reasonable validation entry point"
-  expectedOutput="Stop jumping straight into prototypes and learn to define the problem before comparing solutions"
+  expectedOutput="Stop rushing straight into prototypes and learn to think through the problem before comparing solutions"
 >
 
-One of the most common beginner mistakes is not a lack of effort. It is moving to solutions too fast.
+One of the most common beginner mistakes in product work is not "not trying hard enough." It is moving into solutions too fast.
 
-You get an idea, then immediately start sketching pages, features, AI integrations, buttons, and flows. Later you realize the real issue was never clear in the first place: is this even the right problem, and is it worth solving now?
+The moment an idea appears, people start thinking about screens, buttons, AI integrations, login flows, and prototype tools. Then after a lot of work, they realize the most basic question was never clear: does the user really have this pain point, and is it worth solving now? What feels like project progress is sometimes just accelerating very quickly in the wrong direction.
 
-That is exactly what the **Double Diamond** helps prevent.
+That is exactly what the **Double Diamond** is designed to prevent.
+
+Its most valuable reminder is this: **"choosing the right thing to do" and "doing the thing right" are two different stages.** If the problem is still unclear and you rush into prototyping, you usually just make the wrong direction more complete.
 
 </ChapterIntroduction>
 
 ::: info Minimal SOP
-**Goal**: After this, you should be better at knowing when to think about the problem first and when to start designing solutions.
+**Goal**: After this, you should be much clearer about when to think about the problem first and when to start designing solutions and prototypes.
 
-**Action**: Move through `Discover → Define → Develop → Deliver`, and only do the work that belongs to the current stage.
+**Action**: Move through `Discover → Define → Develop → Deliver`, and only do the kind of work that belongs to the current stage.
 
-**Result**: You will leave with a clearer problem definition, a few comparable solution directions, and a more realistic first validation cut.
+**Result**: You will leave with a clearer problem definition, several comparable solution directions, and one testable first version.
 
-**Quick links**: [What it is](#dd-what) · [The first diamond](#dd-first) · [How AI can help](#dd-ai)
+**Quick links**: [What the Double Diamond is](#dd-what) · [The first diamond](#dd-first) · [How AI can help](#dd-ai)
 :::
 
 ## What You Will Learn
 
-1. What the Double Diamond is and why it helps beginners
+1. What the Double Diamond is, and why it is especially useful for beginners
 2. What Discover, Define, Develop, and Deliver actually mean
-3. How to tell whether you should still be exploring or should start narrowing
+3. How to tell whether you should still be expanding or whether it is time to narrow down
-4. How to use the Double Diamond in AI products, prototyping, and validation
+4. How to use the Double Diamond in AI products, prototype design, and demand validation
 
 <a id="dd-what"></a>
-## 1. What the Double Diamond Is [↩ Back to top](#top-dd)
+## [1. What the Double Diamond Really Is](#top-dd)
 
-The Double Diamond is a design process framework popularized by the UK **Design Council**.
+The Double Diamond is a classic design process framework promoted by the UK **Design Council**. It represents a full design and innovation process as two connected diamond shapes.
 
-It divides the process into four stages:
+It is called a "diamond" because each diamond contains two opposite but equally important motions:
 
-1. **Discover**
+- **diverge**: open the view and look at more possibilities
-2. **Define**
+- **converge**: narrow the scope and make choices
-3. **Develop**
-4. **Deliver**
 
-It is called a “double diamond” because it includes two cycles of:
+The full process has four steps:
 
-- divergence: opening up possibilities
+1. **Discover**: broadly understand users, problems, context, and market
-- convergence: narrowing and choosing
+2. **Define**: extract the core problem that is actually worth solving
+3. **Develop**: explore multiple solution directions around that problem
+4. **Deliver**: choose, prototype, test, and deliver the more suitable solution
 
-In simple language:
+If you want the shortest way to remember it:
 
-- the first diamond is about choosing the right problem
+- **the first diamond**: first figure out what problem is really worth solving
-- the second diamond is about building the right solution
+- **the second diamond**: then decide what kind of solution should solve it
 
-## 2. Why It Matters for Beginners
+That is why a very accurate summary is:
 
-Beginners often do this:
+- **first diamond: choose the right thing to do**
+- **second diamond: do that thing right**
+
+## 2. Why the Double Diamond Is Especially Useful for Beginners
+
+The most common beginner rhythm looks like this:
 
 - get an idea
+- feel that the direction sounds exciting
 - start prototyping immediately
 - keep adding more features
-- lose track of the real problem
+- eventually lose track of the actual problem
 
-The Double Diamond helps by separating two very different questions:
+The value of the Double Diamond is not that it makes the process more complicated. It **forces you to separate "understanding the problem" from "designing the solution."**
 
-- What problem is worth solving?
+That sounds obvious, but it matters a lot. Many failed products were not badly executed. They failed because:
-- What solution is best for that problem?
 
-Many failed products are not weak because people did not work hard. They fail because they polished the wrong thing.
+- they chose the wrong problem
+- they misunderstood the user
+- they locked in a solution too early
+- they spent a lot of time polishing detail before validating direction
+
+The Double Diamond keeps reminding you:
+
+- do not assume a problem is real just because the idea is easy to imagine
+- do not assume something is worth building just because it is technically buildable
+- do not assume a prototype matters just because it looks complete
 
 <a id="dd-first"></a>
-## 3. The First Diamond: Choose the Right Problem [↩ Back to top](#top-dd)
+## [3. The First Diamond: Choose the Right Thing to Do](#top-dd)
 
-The first diamond is about the **problem space**, not the solution space.
+The first diamond is about the **problem itself**, not the solution.
 
-You can translate it as:
+You can translate it into one simple sentence:
 
-**before building, first make sure this is worth building.**
+**before building, first make sure this is worth building at all.**
 
-### 3.1 Discover
+### 3.1 Discover: Open up the problem space first
 
-This is the broad exploration stage.
+The core task in Discover is **broad research, not quick conclusions.**
 
-You look at:
+Typical work in this phase includes:
 
-- what users actually do
+- watching how users behave in real situations
-- when the pain shows up
+- interviewing potential users and asking when the problem last happened
-- what workarounds they use now
+- seeing how they currently patch the issue together
-- what other products or substitutes already exist
+- checking how competitors and substitutes handle it
-- what constraints, environments, or process details shape the problem
+- collecting context about market, workflow, constraints, and surrounding systems
 
-The goal is not to rush to a conclusion. The goal is to avoid acting as if you already know the answer.
+Many people think Discover just means "read more things." But the more important part is this: **you need to understand people and situations, not just collect information.**
 
-### 3.2 Define
+For example, imagine you want to build an AI tool for organizing meeting notes. In Discover, the better questions are:
 
-This is the narrowing stage.
+- what exactly feels painful after a meeting
+- is the hard part recording, organizing, or syncing
+- are people writing notes themselves, asking interns to do it, listening to recordings later, or simply skipping documentation
+- which meeting types really need notes, and which ones do not
 
-You turn a broad topic into a focused problem definition.
+The main goal in Discover is not to get the answer right away. It is to **avoid assuming too early that you already know the answer.**
 
-For example:
+### 3.2 Define: Extract the core problem from a pile of information
 
-- too broad: “I want to improve resume writing”
+If Discover opens the view, Define starts to narrow it.
-- more useful: “Students applying for internships often delay submitting because they are unsure whether their resume is good enough”
 
-Now the direction is more actionable:
+Define is not about preserving every observation. It is about asking:
+
+- which problem is most worth solving first
+- which problem shows up most often, hurts most, or matters most
+- which single situation version one should focus on
+
+The core of this phase is turning a broad topic into one clear problem definition.
+
+For example, maybe you start with:
+
+> I want to build an AI tool that improves meeting efficiency.
+
+By the time you reach Define, a much stronger version might be:
+
+> We will first solve the problem that project teams often cannot produce a shareable meeting note with action items, owners, and deadlines within 10 minutes after a 30-60 minute collaboration meeting.
+
+At that point, the problem is starting to become clear:
 
 - who the users are
-- in what situation the problem appears
+- what the situation is
-- where they get stuck
+- where the bottleneck is
 - what success would look like
 
-## 4. The Second Diamond: Build the Right Solution
+The essence of Define is this: **go from "there are many problems" to "this is the one problem we will solve first."**
 
-Once the first diamond is done, you can move into solutions without drifting as much.
+## 4. The Second Diamond: Do the Thing Right
 
-### 4.1 Develop
+Only after you complete the first diamond does it make sense to move fully into the second. By then, you are not solving a vague direction anymore. You are solving a specific problem that has already been narrowed down.
 
-Now you explore multiple solution directions:
+### 4.1 Develop: Explore multiple solutions around the same problem
 
-- checklist
+The focus in Develop is **to expand the solution space around one defined problem.**
-- AI rewrite tool
-- feedback tool
-- example library
-- role comparison view
 
-The goal here is not to fall in love with the first idea. It is to open the solution space while keeping the problem fixed.
+This kind of divergence is different from Discover:
 
-### 4.2 Deliver
+- Discover expands the problem space
+- Develop expands the solution space
 
-This is where you narrow again:
+Still using the meeting-note example, in Develop you can ask:
 
-- choose the most testable direction
+- should this be a web tool or a meeting plugin
-- build the smallest useful version
+- should it process recordings after the meeting or work in real time
-- test it with real people
+- should it focus only on summary, or mainly on extracting action items
+- should it optimize for personal productivity or team sync
+- should the user edit freely, or should the product output a structured template directly
 
-Deliver does not have to mean “launch the full product.” It can be:
+This is a good phase for brainstorming, comparison, and co-creation.
 
-- a flow sketch
+But there is an important precondition: **all of these solution directions must still serve the same defined problem.**  
-- a low-fidelity prototype
+If the problem is not clear, Develop quickly turns back into random feature sprawl.
-- a tiny MVP
+
+### 4.2 Deliver: Choose, prototype, test, and put the solution into reality
+
+Deliver is the convergence phase inside the second diamond.
+
+At this stage, you are no longer trying to imagine more possibilities. You are making choices:
+
+- which direction fits the current stage best
+- which version is smallest but still useful
+- which features are necessary first and which can wait
+- how to prototype, test, and validate with a smaller group
+
+Many people think Deliver means "launch." A more accurate way to understand it is this:
+
+**turn one solution into something testable, usable, and improvable.**
+
+That could be:
+
+- a low-fidelity flow diagram
+- a Figma prototype
+- a working MVP
 - a small user test
+- a revised version after one round of feedback
 
-What matters is that the solution becomes testable.
+The point of Deliver is not perfection. It is to **get the solution into a real environment quickly enough to validate it.**
 
-## 5. A Simple Comparison Table
+## 5. A Comparison Table That Is Easy to Remember
 
-| Stage | What you are doing | Keywords | Typical outputs |
+If you keep mixing up the four stages, this table is the easiest version to remember:
+
+| Stage | What you are doing | Keywords | Common outputs |
 | --- | --- | --- | --- |
-| Discover | Understanding the problem | research, observation, interviews | notes, patterns, pain points |
+| Discover | Understanding the problem | research, observation, interviews, collecting information | user insight, context notes, problem list |
-| Define | Narrowing the problem | synthesis, prioritization, framing | problem definition, target slice |
+| Define | Defining the problem | synthesis, focus, tradeoff, rewriting the problem | problem statement, priority, MVP cut |
-| Develop | Expanding solution directions | brainstorming, comparison, prototyping ideas | multiple concepts, rough flows |
+| Develop | Exploring solutions | brainstorming, comparison, co-creation, prototype directions | solution list, flow sketches, prototype directions |
-| Deliver | Narrowing and testing | prototype, test, iterate | prototype, user feedback, validation cut |
+| Deliver | Validating solutions | prototype, test, iteration, delivery | prototype, test feedback, improved version |
 
-If you want the shortest version:
+You can compress it even further:
 
-- **Discover / Define** = choose the right problem
+- **Discover / Define**: choose the right thing to do
-- **Develop / Deliver** = build the right solution
+- **Develop / Deliver**: do that thing right
 
 ## 6. Common Double Diamond Mistakes
 
-### 6.1 Jumping to Deliver before Discover
+### 6.1 Jumping into Deliver before doing Discover
 
-This is the classic one: people build screens and flows before they even know whether the problem deserves attention.
+This is the most common one. People get an idea and immediately start drawing screens, writing PRDs, integrating models, or building pages.
 
-### 6.2 Staying in Discover forever
+The problem is not that they are not serious. The problem is that they may not even know whether the problem is worth solving.
 
-The opposite mistake is endless research with no convergence. The Double Diamond is not “keep exploring forever.” It is “explore, then decide.”
+### 6.2 Staying in Discover for too long and never reaching Define
 
-### 6.3 Quietly changing the problem to fit a favorite solution
+The opposite mistake is endless research, endless reading, endless interviews, and no convergence.
 
-Sometimes teams define a problem, then later shift the problem statement just to justify the solution they already wanted to build.
+The Double Diamond is not telling you to expand forever. It is reminding you that after expansion, you must eventually make choices.
 
-That is dangerous because you may stop solving the real problem and start defending a favorite idea.
+### 6.3 Quietly changing the problem after Define
 
-### 6.4 Treating Deliver as “build everything”
+Some teams define a problem, but during Develop they discover that a certain solution is easier to build. Then they quietly rewrite the problem so it fits their preferred solution.
 
-Deliver does not mean a complete polished product. A useful prototype or a small validation test can already be a strong deliverable.
+That is dangerous. At that point, you may no longer be solving the real problem. You may be defending a favorite implementation.
 
-## 7. How This Helps in AI Products
+### 6.4 Treating Deliver as "build everything"
 
-AI products are especially vulnerable to “capability-first” thinking because the technology looks exciting.
+Deliver does not mean shipping a huge complete product. Often, a testable prototype or one round of real user testing is already a strong deliverable.
 
-It is easy to jump to:
+## 7. How to Use the Double Diamond in AI Products
 
-- Should we add multimodal support?
+AI products are especially likely to fall into capability-first thinking because model capabilities are so tempting. It is very easy to jump straight to:
-- Should we build an agent?
-- Should we connect a workflow engine?
-- Should we add voice, image, web search?
 
-The Double Diamond helps you ask first:
+- should we add multimodal input
+- should we build an agent
+- should we connect workflow automation
+- should we add voice, image, or web search
 
-- where are users genuinely stuck?
+The Double Diamond forces you to ask first:
-- is this a place where AI is actually necessary?
-- what is weak about the current workaround without AI?
-- what progress would AI make possible here?
 
-That protects you from a common failure mode:
+- where are users actually stuck
+- is this bottleneck something AI is truly needed for
+- without AI, what is so weak about the current method
+- if AI is added, what real progress does it create
+
+That helps you avoid a very common failure mode:
 
 **high capability, low value.**
 
-## 8. A Template You Can Use Right Away
+A practical sequence looks like this:
 
-If you are working on your own product, you can write through the stages like this.
+1. in Discover, observe how users currently handle the task
+2. in Define, write the most painful scenario as one clear problem statement
+3. in Develop, compare which AI capabilities best serve that problem
+4. in Deliver, build a small first version and test it with real users
+
+## 8. A Double Diamond Template You Can Reuse
+
+If you are working on your own product, you can write through the stages in this order:
 
 ### Discover
 
 - Who are the users I am observing?
 - When did they last experience this problem?
-- What do they do now?
+- How do they solve it now?
-- What feels slow, painful, or risky?
+- What feels most annoying, slow, or risky?
 
 ### Define
 
-- Which problem is most worth prioritizing?
+- Out of all these problems, which one is most worth solving first?
 - Which situation is most frequent or most important?
-- Who does version one serve, and what exactly does it solve?
+- Who exactly does version one serve, and what exactly does it solve?
-- What changes for the user if we solve it well?
+- If we solve it well, what change happens in the user's state?
 
 ### Develop
 
-- What solution directions are possible?
+- What solution directions are possible for this problem?
-- Which are the lightest, fastest, and easiest to validate?
+- Which directions are lightest, fastest, and easiest to validate?
-- What is essential now, and what can wait?
+- Which parts are essential now, and which can wait?
 
 ### Deliver
 
-- What is the smallest useful thing we can put in front of users?
+- What is the smallest thing we can deliver to validate this direction?
-- Is it a sketch, prototype, or MVP?
+- Is it a flow sketch, a prototype, or an MVP?
 - Who do we need to test with?
-- What would make us continue, change direction, or stop?
+- After testing, how will we decide whether to continue, change, or stop?
 
-## 9. A Beginner-Friendly Example
+## 9. A Full Example a Beginner Can Understand
 
-Suppose you want to build an AI tool that helps students prepare resumes for job applications.
+Suppose you want to build an AI tool that helps college students prepare job-application resumes.
 
-Many people would jump straight into the second diamond and start asking:
+Many people would immediately jump into the second diamond and start asking:
 
-- should there be one-click beautification?
+- should there be one-click beautification
-- should there be AI rewriting?
+- should there be smart rewriting
-- should it auto-match job descriptions?
+- should it auto-match the job description
-- should it generate self-introductions?
+- should it generate self-introductions
 
-The Double Diamond suggests a better process.
+But with the Double Diamond, a stronger process looks like this:
 
 ### First diamond
 
 **Discover**
 
-- talk to recent graduates about the last time they edited a resume
+- talk to recent graduates about the last time they revised a resume
-- watch how they move from an old resume to a new version
+- watch how they turn an old version into a new one
-- see whether their pain is “I can't write,” “I can't revise,” or “I can't judge quality”
+- figure out whether their biggest issue is "I cannot write," "I cannot revise," or "I cannot judge quality"
 
 **Define**
 
-- narrow down to something more concrete
+- narrow it into a more specific problem
-- not “students cannot make resumes”
+- not "students cannot make resumes"
-- but “students applying for internships for the first time struggle to turn existing experiences into role-fit wording, so they delay applying”
+- but "students applying for internships for the first time struggle to rewrite existing experiences into role-fit wording, so they delay applying"
 
 ### Second diamond
 
 **Develop**
 
-- compare directions: templates, AI rewriting, job comparison, resume scoring, examples
+- compare several directions: template library, AI rewriting, role comparison, resume scoring, example references
 
 **Deliver**
 
-- build only one narrow version first, such as “rewrite bullet points using a job description”
+- build only one narrow first version, such as "rewrite resume bullet points based on a job description"
-- test it with five students and see whether it helps them submit faster
+- let five students test it and see whether it helps them submit a first version faster
 
-When the first diamond is solid, the second diamond becomes much clearer.
+Once the first diamond is solid, the second diamond becomes much clearer.
 
 ## 10. Summary
 
-The real strength of the Double Diamond is that it breaks a messy process into four clearer moves:
+The strongest part of the Double Diamond is that it breaks one big messy process into four clearer moves:
 
-- first expand the problem space
+- first expand to understand the problem
-- then narrow the problem definition
+- then narrow to define the problem
-- then expand the solution space
+- then expand to explore solutions
-- finally narrow toward delivery
+- finally narrow to deliver the solution
 
-It does not make you slower. It helps you avoid spending a lot of energy on the wrong direction.
+It does not make you slower. It helps you **avoid many detours that look busy but are moving in the wrong direction.**
 
-This matters even more in the AI era, because building things is getting easier. When making becomes cheap, choosing the right problem becomes even more valuable.
+This matters even more in the AI era because building things is getting easier and faster. When "making something" becomes cheap, the scarcer skill becomes this: **are you solving a problem worth solving, and are you solving it in an appropriate way?**
+
+If you remember only one sentence, remember this:
+
+**first choose the right thing to do, then do that thing right.**
 
 <a id="dd-ai"></a>
-## 11. How AI Can Help You Use the Double Diamond [↩ Back to top](#top-dd)
+## [11. How AI Can Help You Run the Double Diamond](#top-dd)
 
-AI is useful here not as the decision-maker, but as a helper for research, synthesis, and comparison.
+The Double Diamond is not an AI tool, but AI works very well as an accelerator inside all four stages. The key is not to let AI decide for you. The key is to let it help you expand the view, organize information, compare directions, and generate validation material.
 
-### 11.1 Discover: Build a rough problem map
+### 11.1 In Discover, use AI to build a rough problem map first
 
-Before interviews and deeper research, AI can help you scan the problem space:
+Before formal interviews and deeper research, AI can help you do a lightweight scan of the space, for example:
 
-- common substitutes
+- what common substitutes already exist
-- frequent public complaints
+- what users complain about most in public communities
-- typical situations and user groups
+- which scenarios and user groups this problem shows up in
-- what current tools ignore
+- what current products often ignore
 
-Simple input:
+This cannot replace real research, but it is very useful for creating a first map of the space.
+
+A simple beginner prompt could be:
 
 ```text
-I want to build something that helps students improve resumes.
+I want to build a tool that helps college students improve resumes.
-Do not give me features yet.
+Do not help me think about features yet.
-First help me map the most common problems people seem to face.
+First help me figure out what problems people most often run into here.
 ```
 
 Possible AI output:
 
 ```text
 Initial problem map:
-1. Not knowing what to include
+
-2. Not knowing how to tailor for different roles
+1. They do not know what experiences to include
-3. Not knowing when the resume is good enough
+2. They do not know how to tailor the resume to different roles
-4. Depending on others for feedback
+3. They revise many times and still do not know if it is good enough
-5. Delaying applications because of uncertainty
+4. They need someone else to review it, but cannot always ask
+5. Because they feel unsure, they keep delaying applications
 ```
 
-This does not replace research, but it helps you enter Discover faster.
+That kind of output is not there to replace your judgment. It helps you enter Discover faster.
 
-### 11.2 Define: Narrow the problem
+### 11.2 In Define, use AI to narrow the problem statement
+
+After collecting a lot of information, one of the hardest things is turning it into one really clear problem statement. You can give research notes to AI and ask it to compress them into candidate definitions:
 
 ```text
-Here are the issues I collected:
+Below are user notes and research notes I collected during Discover:
-1. people don't know what to write
+[paste the content]
-2. people don't know how to revise
-3. people keep delaying because they are unsure it is good enough
 
-Help me decide which one is the best first problem to focus on.
+Please do 3 things:
+1. summarize the most common problem patterns
+2. based on frequency, pain, and ease of validation, suggest 3 problems worth prioritizing
+3. write each problem as one clear problem statement
+```
+
+You can keep the input very simple too:
+
+```text
+These are the issues I collected:
+1. people do not know what to write on the resume
+2. people do not know how to revise it
+3. people keep feeling it is not good enough, so they do not apply
+
+Please help me decide which problem is the best first one to solve.
 ```
 
 Possible AI output:
 
 ```text
 Recommended first problem:
-"Students applying for internships delay applications because they cannot tell when their resume is good enough to submit."
+
+"Students applying for internships for the first time are unsure whether their resume has reached a submit-ready level, so they keep revising and delay applying."
+
+Reasons:
+1. it is more concrete
+2. it explains the delay behavior
+3. it is easier to test with a smaller first version
 ```
 
-That kind of output is useful because it turns a pile of fuzzy issues into a more testable first problem.
+That is useful because it helps you narrow a fuzzy set of issues into something closer to an MVP starting point.
 
-### 11.3 Develop: Generate multiple directions
+### 11.3 In Develop, use AI to expand multiple solution directions
+
+Once people define a problem, they often fixate immediately on the first solution that comes to mind. AI is very useful here as a forced divergence tool:
 
 ```text
-My problem definition is:
+I have defined this core problem: [your problem statement]
-"Students delay applications because they are unsure whether their resume is ready."
+Please do not give me only one final answer.
+Instead, propose 2-3 solution directions from each of these angles:
+1. the lightest MVP
+2. the best option for validating demand
+3. the best option for improving user experience
+4. a non-AI solution
+5. an AI-based solution
 
-Please suggest 4 different solution directions.
+At the end, compare the strengths, risks, and validation cost of each direction.
+```
+
+That stops you from getting trapped by one favorite solution too early.
+
+A simpler prompt could be:
+
+```text
+My problem statement is:
+"Students delay applying because they are not sure whether their resume is ready."
+
+Please suggest 4 different solution directions, not just one.
 ```
 
 Possible AI output:
 
 ```text
-1. Resume readiness checklist
+Option 1: resume readiness checklist
-2. Role-specific rewrite assistant
+Option 2: job-description-based rewrite assistant
-3. Risk and gap detector
+Option 3: resume risk detector
-4. Example comparison library
+Option 4: example comparison library
 ```
 
-This helps you compare rather than overcommit too early.
+Now you are in comparison mode instead of only staring at one AI rewriting path.
 
-### 11.4 Deliver: Generate a lightweight test script
+### 11.4 In Deliver, use AI to generate prototype copy and testing material
+
+Once you reach Deliver, AI is very useful for speeding up work like:
+
+- writing copy for low-fidelity prototypes
+- organizing user test scripts
+- generating multiple versions of titles, buttons, and instructions
+- summarizing test feedback and issue lists
+
+For example, you can ask AI to generate a 20-minute user test script, or summarize five pieces of feedback into a decision frame like "continue / revise / pause."
+
+A very small input could be:
 
 ```text
-I built a simple prototype where users upload a resume and get "not ready yet" feedback.
+I made a very simple prototype:
+the user uploads a resume, and the system tells them which parts are not yet ready for submission.
+
 Please generate a 15-minute user testing script.
 ```
 
 Possible AI output:
 
 ```text
-15-minute test script:
+15-minute user testing script:
 
-1. Ask the user to describe their last resume-editing experience
+1. Ask the user to describe their most recent resume submission experience
-2. Let them upload a resume on their own
+2. Let them upload a resume independently
-3. Observe whether the feedback is understandable
+3. Observe whether they understand the feedback
-4. Ask which parts feel useful and which parts feel confusing
+4. Ask which parts feel helpful and which parts feel confusing
-5. Ask whether they would want to use this before their next application
+5. Ask whether they would want to use this again before the next application
 ```
 
-### 11.5 Use AI as a stage guard
+That is useful because it moves you from "I finished the prototype" to "how do I actually test this?"
 
-One of the biggest Double Diamond risks is jumping stages. AI can help by acting like a process coach:
+### 11.5 Let AI act as a stage guard
+
+One of the biggest risks in the Double Diamond is that people skip stages. You can directly ask AI to act like a process guard:
 
 ```text
-Act as a product process coach.
+Please act as a product process coach.
 Here is my current project state: [your description]
-Please tell me whether I am mainly in Discover, Define, Develop, or Deliver.
+Please judge whether I am mainly in Discover, Define, Develop, or Deliver.
-Also tell me:
+Then tell me:
-1. whether I am jumping too early
+1. whether I am jumping ahead too early
-2. what the most important action in this stage is
+2. what the most important action in the current stage is
 3. what I should not do yet
 ```
 
-That is especially useful for beginners who tend to prototype before the problem is clear.
+That is especially helpful for beginners because it is very easy to start prototyping before the problem is truly clear.
 
 ## Assignments
 
-1. Pick one product idea and map it into Discover, Define, Develop, Deliver
+1. Pick one product idea you have been thinking about and write a draft for its Discover, Define, Develop, and Deliver stages
-2. Write one clear problem definition
+2. In Define, force yourself to compress the problem into one concrete sentence
-3. Generate at least 3 different solution directions
+3. In Develop, list at least 3 different solution directions instead of clinging to the first one
-4. Define one small validation version you could test within a week
+4. In Deliver, write down one smallest validation version you could ship within a week
 
 ## Further Reading
 
+This article mainly draws on the Design Council's official material about the Double Diamond. These are good places to continue:
+
 - [Design Council: The Double Diamond](https://www.designcouncil.org.uk/our-resources/the-double-diamond/)
 - [Design Council: Framework for Innovation](https://www.designcouncil.org.uk/our-work/skills-learning/tools-frameworks/framework-for-innovation-design-councils-evolved-double-diamond/)
 - [Design Council: History of the Double Diamond](https://www.designcouncil.org.uk/our-resources/the-double-diamond/history-of-the-double-diamond/)

docs/en/stage-1/appendix-idea-sources/index.md

@@ -0,0 +1,301 @@
+---
+title: 'Where to Find Ideas: 3 Beginner-Friendly Sources'
+description: 'A beginner-friendly guide to product idea discovery. This appendix focuses on websites for browsing idea lists, trend sources, real business signals, and VC requests so you can find a more concrete direction faster.'
+---
+
+<script setup>
+const duration = 'About <strong>1.5 hours</strong>'
+</script>
+
+# Where to Find Ideas: 3 Beginner-Friendly Sources
+
+<a id="top-idea-sources"></a>
+
+## Introduction
+
+<ChapterIntroduction
+  :duration="duration"
+  :tags="['Idea Discovery', 'Product Direction', 'User Needs', 'Industry Signals']"
+  coreOutput="1 more concrete product direction worth investigating further"
+  expectedOutput="Know where to browse, what to look at first, and how to avoid getting stuck with vague labels like “AI + some industry”"
+>
+
+Many people do not get stuck because they have zero inspiration. They get stuck because after reading a lot of content, what remains in their head is still a big label:
+
+- AI for education
+- AI for healthcare
+- AI for finance
+- AI agent for business
+
+Those are not product ideas yet. They only say the direction is broad. They do not tell you:
+
+- who the user is
+- in what situation they need help
+- what they do today to hold the workflow together
+- which step is worth cutting into first
+
+This article does not spend time on abstract theory. It gives you a more practical set of sources.
+
+</ChapterIntroduction>
+
+::: info Minimal SOP
+**Goal**: After this, you should know where to browse when you have no clear idea yet, which links are better for concrete demand, which are better for trends, and which are closer to real business signals.
+
+**Action**: Browse one round of idea lists, one round of small profitable products, then a round of trend and business sources. Keep only one direction you still want to investigate.
+
+**Result**: You will leave with one more concrete direction worth validating instead of a broad category.
+
+**Quick links**: [Reference apps](#idea-apps) · [Trend sources](#idea-trends) · [Business signals](#idea-business) · [VC / accelerator sources](#idea-vc) · [Shortest path](#idea-path) · [How AI can help](#idea-ai)
+:::
+
+## What You Will Learn
+
+1. Which sites are best for directly browsing product ideas
+2. Which sites are useful for studying small products that already make money
+3. Which sources are better for spotting trends and industry movement
+4. Which sources are closer to real business demand and real budgets
+5. A shortest path that works well for beginners
+
+<a id="idea-apps"></a>
+## [1. Reference Apps: Start with Things People Are Already Building](#top-idea-sources)
+
+This is the best starting point for beginners because it is the most concrete.
+
+### Tier 1: Open the site and pick directly from idea lists
+
+- [Reddit — r/SomebodyMakeThis](https://www.reddit.com/r/SomebodyMakeThis/)
+  The core use of this subreddit is simple: real users post “I wish someone would build X.” Each post is usually one concrete product need, often with some situation context. A good way to browse is `Top -> Past Month` or `Top -> Past Year`.
+- [Reddit — r/AppIdeas](https://www.reddit.com/r/AppIdeas/)
+  Similar to the one above, but more focused on software and apps. A lot of posts are basically “I need an app that can do X,” which makes the granularity easier for beginners.
+- [Reddit — r/Startup_Ideas](https://www.reddit.com/r/Startup_Ideas/)
+  More complete than the first two. Many posts include not just the problem, but some quick market thinking or monetization logic.
+- [Unvalidated Ideas](https://unvalidatedideas.com/)
+  Publishes startup ideas that are still unvalidated. The structure is consistent: target user, monetization angle, and a rough validation path.
+- [IdeasAI](https://ideasai.com/)
+  AI-generated startup ideas you can browse endlessly. Quality is uneven, but it works well as a way to spark directions that you later narrow yourself.
+
+### Tier 2: Study small products that already make money and reverse-engineer the idea
+
+These platforms matter because they show you not just “someone wants this,” but “someone has already turned this into a product and maybe into revenue.”
+
+- [Starter Story](https://www.starterstory.com/)
+  Real small-business case studies with founder interviews, revenue data, and origin stories. The best entries to study are often not the giant successes, but the niche products making roughly $10k-$100k per month.
+- [Indie Hackers — Products](https://www.indiehackers.com/products)
+  A place where indie makers show products, growth, and often revenue. Sort by revenue and look at products making a few thousand to a few tens of thousands a month.
+- [MicroConf Blog](https://microconf.com/blog)
+  Strong for Micro SaaS. Useful if you want to learn what “small enough to build, but still worth paying for” looks like.
+- [1000 Tools](https://1000.tools/)
+  An AI tool directory. Useful for checking which categories already exist, which ones feel weak, and which niches are still under-served in your region or industry.
+- [Product Hunt](https://www.producthunt.com/)
+  Useful for watching what categories keep appearing repeatedly. Do not only watch the number one launch. Look for repeated product types with no clear dominant winner.
+- [BetaList](https://betalist.com/)
+  Good for early-stage products and teams still exploring direction.
+
+### Do not only study the product itself. Study reviews and “done-for-you” services too
+
+- [G2](https://www.g2.com/)
+  Look at 1-star and 2-star reviews. Negative reviews often tell you exactly which step current products still handle badly.
+- [Capterra](https://www.capterra.com/)
+  Similar use case to G2, especially for SaaS complaints and workflow friction.
+- Taobao / Xianyu / [Fiverr](https://www.fiverr.com/) / [Upwork](https://www.upwork.com/) / ZBJ
+  Search for services like “done for you,” “organized for you,” “data entry,” “transcription,” and “manual cleanup.” If people keep paying humans to do it, there is often a repeatable workflow behind it.
+
+The signal you want is simple:
+
+- users are already complaining about current tools
+- users are already paying someone to do the work manually
+- users are already spending a lot of time and labor on the workflow
+
+### Another useful format: watch videos where someone breaks down ideas for you
+
+If you do not like browsing lists and forums, video and podcast formats can work better.
+
+- Search `Greg Isenberg startup ideas`
+  Good when you want someone to break down 2 or 3 concrete startup ideas with market size, competition, and entry angle.
+- Search `My First Million podcast`
+  Strong for loose but high-density idea brainstorming. It often surfaces surprisingly specific niches.
+- Search `YC startup ideas` or `Michael Seibel startup ideas`
+  Good for beginners because the explanations are usually direct and practical.
+
+<a id="idea-trends"></a>
+## [2. Trend Sources: See Which Directions Are Rising](#top-idea-sources)
+
+Trend sites are not there to hand you a product idea. They help you judge whether a direction is heating up and worth a closer look.
+
+- [Exploding Topics](https://explodingtopics.com/)
+  Tracks fast-growing topics and product categories before they fully hit the mainstream. Good for spotting things that are rising but not yet too crowded.
+- [Google Trends](https://trends.google.com/)
+  Search a keyword, look at the trend line over the past year, then check the “related queries” section for breakout terms.
+- [Glimpse](https://meetglimpse.com/)
+  Similar in spirit to trend products, but more consumer-oriented. Useful for product categories, consumption patterns, and rising lifestyle signals.
+- Industry report summary pages
+  Useful when you already have a direction and want quick context on where it sits in the market.
+- McKinsey / BCG / Gartner trend content
+  Better for B2B, traditional industries, enterprise, and industrial settings.
+- [State of AI Report](https://www.stateof.ai/)
+  Useful when your direction is tightly tied to AI technology itself and you want a broader yearly map.
+
+When looking at trends, focus on only three things:
+
+- is the topic rising consistently
+- what concrete scenario it falls into
+- who would be the first to pay with time, switching cost, or budget
+
+<a id="idea-business"></a>
+## [3. Business Signals: See Who Is Paying, Complaining, and Selling Manual Services](#top-idea-sources)
+
+If you want something more grounded than “this sounds cool,” you need sources closer to real workflows.
+
+### See who is already paying for what
+
+- [China Government Procurement Network](https://www.ccgp.gov.cn/)
+  Search terms like “smart construction site,” “lab management system,” “data collection,” “clinic management,” or “quotation system.” Look at budget, technical requirements, and workflow details.
+- Provincial and municipal public resource trading centers
+  Useful for seeing what local governments and state-owned enterprises actually buy.
+- Bidding platforms such as Bibiaowang, Qianlima, and Zhaobiatong
+  Useful for enterprise-side procurement and repeated system demand.
+
+The reason these sources matter is simple: they are not discussing the future. They reveal what someone is already willing to spend money on today.
+
+### See who is really complaining
+
+- Manufacturing: machinery communities and industrial control forums
+- Healthcare: DXY, Yimatong
+- Construction / engineering: Tumu, Glodon communities
+- Finance / accounting: accounting forums
+- Foreign trade: trade communities and export forums
+- Retail / food service forums
+- [Reddit](https://www.reddit.com/) vertical communities such as `r/smallbusiness`, `r/Entrepreneur`, `r/SaaS`, `r/healthcare`, `r/manufacturing`
+- [V2EX](https://www.v2ex.com/)
+- Jike
+- Xiaohongshu
+
+Do not only search for terms like “AI” or “innovation.” Better searches are:
+
+- this is too annoying
+- is there a better way
+- recommend a tool
+- Excel is no longer enough
+- I wish there was
+- is there a tool for
+- I hate
+
+### See who is selling repeat manual labor
+
+- [Fiverr](https://www.fiverr.com/)
+- [Upwork](https://www.upwork.com/)
+- ZBJ
+- Taobao
+- Xianyu
+
+If you find these services selling well, it is usually worth looking deeper:
+
+- turning PDF quotations into Excel
+- cleaning customer data in bulk
+- editing resumes / copy / transcripts / archives
+
+These are rarely one-off needs. They are usually repeat workflows.
+
+### Study the full workflow, not just the idea list
+
+Sometimes the shortest path is to pick an industry, trace the workflow, and find the steps still running on WeChat, Excel, paper, or phone calls.
+
+- Foreign trade: finding suppliers, requesting quotes, price comparison, making quotations, sending them to clients, following up, inspections, booking shipment, customs.
+  A strong cut point: converting supplier quotes into customer-facing quotations.
+- Dental clinics: intake, scans, diagnosis, treatment plans, follow-up, treatment, revisit.
+  A strong cut point: explaining treatment plans clearly and following up afterward.
+- Construction sites: inspection, photos, chat groups, reports, delivery to the client.
+  A strong cut point: turning on-site photos into compliance reports.
+
+<a id="idea-vc"></a>
+## [4. VC / Accelerator Sources: See Where the Wave Is Moving](#top-idea-sources)
+
+These sources are useful for finding broader direction, but they do not replace validation.
+
+- [Y Combinator — Requests for Startups](https://www.ycombinator.com/rfs)
+  Good for concrete cuts because YC often says very directly: “we want to see someone build this.”
+- [a16z — Big Ideas](https://a16z.com/big-ideas-2025/)
+  More useful for broad trend and category judgment.
+- [NFX](https://www.nfx.com/)
+  Good for quickly scanning a set of startup directions.
+- [Sequoia Capital](https://www.sequoiacap.com/article/)
+  Not always a direct idea list, but often useful for platform shifts and new opportunity framing.
+- [First Round Review](https://review.firstround.com/)
+  Better for deeper thinking about a direction, not necessarily quick idea lists.
+
+The upside of these sources:
+
+- they tell you which directions may be worth watching
+- they tell you which categories may keep getting pushed forward
+- they help you enter the language of a category faster
+
+Their limitation:
+
+- they are usually investor-facing
+- they do not always tell you which exact role feels the pain most
+- they do not always tell you which workflow step is most broken
+- they do not always tell you who is already paying today
+
+A better use pattern is: use them to find a direction, then go back to reference products, industry communities, procurement signals, and real workflows.
+
+<a id="idea-path"></a>
+## [5. The Shortest Path for Someone Who Has No Clear Idea Yet and Only Knows How to Build "Assistants"](#top-idea-sources)
+
+If you only follow one path, make it this one:
+
+1. Step one, 30 minutes.
+   Open [r/SomebodyMakeThis](https://www.reddit.com/r/SomebodyMakeThis/), sort by `Top -> Past Year`, scan 50 posts, and save every direction that makes you think, “I might actually be able to build something here.”
+2. Step two, 30 minutes.
+   Open [Starter Story](https://www.starterstory.com/) or [Indie Hackers Products](https://www.indiehackers.com/products), sort by revenue, and study the middle-income products, not just the biggest wins. Find products related to your saved directions and note who they sell to and which step they solve.
+3. Step three, 20 minutes.
+   Use [Google Trends](https://trends.google.com/) to search the related keywords. Check whether the trend is rising and what the breakout related queries are.
+4. Step four, 20 minutes.
+   Go to G2 / Capterra / industry forums / bidding platforms / Fiverr-type sites and check what part of the workflow still feels painful and manual today.
+
+After that, being able to say this one sentence is enough:
+
+- A certain type of user, in a certain situation, is stuck on a certain workflow step and is currently holding it together with a clumsy workaround.
+
+<a id="idea-ai"></a>
+## [6. How AI Can Help](#top-idea-sources)
+
+AI is not the center of this article, but it is very useful for organizing what you find.
+
+The two most practical uses are:
+
+- paste links, post titles, and user quotes into AI, and ask it to sort them into user group / situation / pain point / workaround
+- ask AI to compress a pile of scattered notes into 3 candidate directions instead of expanding into 50 features
+
+You can ask like this:
+
+```text
+I recently browsed these sources:
+1. [paste title or quote]
+2. [paste title or quote]
+3. [paste title or quote]
+
+Please do not give me a feature list.
+Only do 3 things:
+1. group them by user type and situation
+2. identify the workflow steps that keep showing up as painful
+3. turn them into 3 more concrete candidate directions
+```
+
+## Further Reading
+
+- [Y Combinator - Requests for Startups](https://www.ycombinator.com/rfs)
+- [a16z - Big Ideas](https://a16z.com/big-ideas-2025/)
+- [NFX](https://www.nfx.com/)
+- [Reddit - r/SomebodyMakeThis](https://www.reddit.com/r/SomebodyMakeThis/)
+- [Reddit - r/AppIdeas](https://www.reddit.com/r/AppIdeas/)
+- [Reddit - r/Startup_Ideas](https://www.reddit.com/r/Startup_Ideas/)
+- [Starter Story](https://www.starterstory.com/)
+- [Indie Hackers - Products](https://www.indiehackers.com/products)
+- [Product Hunt](https://www.producthunt.com/)
+- [BetaList](https://betalist.com/)
+- [IdeasAI](https://ideasai.com/)
+- [Unvalidated Ideas](https://unvalidatedideas.com/)
+- [Google Trends](https://trends.google.com/)
+- [Exploding Topics](https://explodingtopics.com/)
+- [G2](https://www.g2.com/)
+- [Capterra](https://www.capterra.com/)

docs/en/stage-1/appendix-jobs-to-be-done/index.md

@@ -48,7 +48,7 @@ This article explains JTBD in plain language and turns it into something you can
 4. How JTBD connects to AI product thinking, interviews, and prompt-based analysis
 
 <a id="jtbd-what"></a>
-## 1. What Jobs to Be Done Means [↩ Back to top](#top-jtbd)
+## [1. What Jobs to Be Done Means](#top-jtbd)
 
 Jobs to Be Done, often shortened to **JTBD**, is built around a simple idea: users “hire” a product to get something done.
 
@@ -99,7 +99,7 @@ On the surface, they are buying breakfast. In JTBD terms, they may really be try
 - avoid being hungry before arriving at work
 - keep their morning routine moving without disruption
 
-The product they “hire” is not really a sandwich. It is a reliable way to keep the morning moving.
+The thing they "hire" is not really one specific sandwich brand. It is a reliable way to keep the morning moving.
 
 The same logic applies to AI products. If you want to build an AI meeting summary tool, JTBD helps you step back from feature brainstorming and ask:
 
@@ -178,7 +178,7 @@ What would make the user say this was truly helpful?
 If you cannot say what “useful enough” means, the direction is probably still not focused enough.
 
 <a id="jtbd-formula"></a>
-## 5. A One-Sentence Formula You Can Reuse [↩ Back to top](#top-jtbd)
+## [5. A One-Sentence Formula You Can Reuse](#top-jtbd)
 
 Use this sentence pattern:
 
@@ -337,7 +337,7 @@ your idea usually becomes much sharper.
 It also helps you avoid one of the biggest mistakes in AI products: falling in love with capability demos instead of user progress.
 
 <a id="jtbd-ai"></a>
-## 12. How AI Can Help You Practice JTBD [↩ Back to top](#top-jtbd)
+## [12. How AI Can Help You Practice JTBD](#top-jtbd)
 
 JTBD is not an AI invention, but AI can be a very helpful research assistant, organizer, and challenger. The key is this:
 

docs/en/stage-1/appendix-mom-test/index.md

@@ -1,6 +1,6 @@
 ---
 title: 'The Mom Test: How to Validate Demand Through User Interviews'
-description: 'A beginner-friendly introduction to The Mom Test. Learn how to stop collecting polite praise and start getting evidence from real behavior, real costs, and real user situations.'
+description: 'A beginner-friendly introduction to The Mom Test. Learn how to avoid polite feedback, ask about real behavior and real costs, and turn “sounds good” into more reliable demand evidence.'
 ---
 
 <script setup>
@@ -15,248 +15,293 @@ const duration = 'About <strong>1.5 hours</strong>'
 
 <ChapterIntroduction
   :duration="duration"
-  :tags="['User Interviews', 'Validation', 'Research', 'Product Discovery']"
+  :tags="['User Interviews', 'Demand Validation', 'User Research', 'Product Discovery']"
   coreOutput="1 set of interview questions more likely to reveal real user information"
   expectedOutput="Stop treating polite encouragement as validation and start judging direction through real behavior"
 >
 
-When beginners start product research, they often ask questions like:
+When many beginners do product research for the first time, they assume the important thing is simply to "talk to some people." So they ask friends, classmates, coworkers, or family:
 
 - What do you think of this idea?
 - Would you use this if I built it?
 - Does this feature sound useful?
 
-The answers usually sound encouraging. The problem is that they are often not useful. They are often just politeness, support, or a natural instinct to avoid discouraging you face-to-face.
+The replies usually sound encouraging:
 
-That is exactly what **The Mom Test** is about: not how to get nicer conversations, but how to ask questions that reveal real evidence instead of polite support.
+- Sounds good
+- That seems useful
+- I think you should try it
+
+The problem is that these answers usually do not help you decide anything. They are often just politeness, support, or a natural instinct not to discourage you in the moment. You think you collected "market validation," but what you really collected was a pile of comforting feedback that is hard to use.
+
+That is exactly what **The Mom Test** is for. Its central reminder is:
+
+**users are usually not trying to lie to you. The real problem is that your question format often pushes them toward nice but useless answers.**
 
 </ChapterIntroduction>
 
 ::: info Minimal SOP
-**Goal**: After this, you should be better at talking to users in a way that gives you useful evidence, not just nice-sounding feedback.
+**Goal**: After this, you should be much clearer on how to talk to users without getting stuck with “sounds good,” and instead get information that actually helps you judge direction.
 
-**Action**: Rewrite 5 interview questions so they focus on real past behavior instead of opinions about your idea.
+**Action**: Rewrite 5 questions you would normally ask so they focus on “when did this last happen?” and “how did you handle it?”
 
-**Result**: You will leave with a clearer sense of what counts as evidence and what is just encouragement.
+**Result**: You will get better at separating opinions from evidence, and encouragement from demand.
 
-**Quick links**: [What The Mom Test is](#mom-what) · [Core principles](#mom-principles) · [How AI can help](#mom-ai)
+**Quick links**: [What The Mom Test is](#mom-what) · [Three core principles](#mom-principles) · [How AI can help](#mom-ai)
 :::
 
 ## What You Will Learn
 
-1. What problem The Mom Test is really solving
+1. What problem The Mom Test is actually solving, and why many "user interviews" fail to uncover useful truth
-2. Why many “user interviews” fail to produce useful truth
+2. The core principles of the method: ask less about opinions and future hypotheticals, and more about real behavior and real facts
-3. How to rewrite weak, leading questions into stronger ones
+3. How to rewrite low-value questions into stronger interview questions
-4. How The Mom Test connects with JTBD, validation, and MVP decisions
+4. How The Mom Test works together with JTBD, validation, and MVP decisions
 
 <a id="mom-what"></a>
-## 1. What The Mom Test Is [↩ Back to top](#top-mom)
+## [1. What The Mom Test Really Is](#top-mom)
 
 The Mom Test comes from Rob Fitzpatrick's book of the same name. The title sounds playful, but the point is sharp:
 
-Even your mom will struggle to tell you your idea is bad if you ask the wrong question.
+**even your mom will struggle to tell you your idea is bad if you ask the wrong way.**
 
-The problem is not that users are trying to lie. The problem is that your question format often invites nice but weak answers.
+The reason is not that she is dishonest. It is that:
 
-It is not really “don't ask your mom.” It is:
+- she does not want to hurt you
+- she naturally wants to encourage you
+- she will often answer in the direction your question already suggests
 
-**don't ask in a way that makes almost anyone give you a flattering answer.**
+And this is not only about your mom. Friends, coworkers, former classmates, and even strangers often do the same thing when they react to a product idea. A positive answer does not necessarily mean the demand is real. It may simply mean you asked in a way that made a flattering answer easy.
+
+So the point of The Mom Test is not really "do not ask your mom." It is:
+
+**do not ask in a way that makes almost anyone answer by encouraging you.**
+
+What this method really teaches is how to use conversation to get closer to real demand instead of collecting feel-good commentary.
 
 ## 2. The Core Problem It Solves
 
-The Mom Test helps you avoid a very common mistake:
+The Mom Test mainly helps you avoid one very common cognitive mistake:
 
 **mistaking polite positive feedback for real demand.**
 
-Questions like these are dangerous:
+For example, people often ask:
 
-- What do you think of my app idea?
+- What do you think of this app idea?
-- Would you use this if it existed?
+- If I built an AI tool that rewrites resumes, would you use it?
-- Would you pay for this?
+- Does this feature sound valuable?
 
-They ask for opinion, prediction, or encouragement. Those are much less reliable than actual behavior.
+These questions have three things in common:
 
-People also tend to overestimate their future selves. They imagine they will be more disciplined, more experimental, or more willing to pay than they really are.
+- they ask for opinions
+- they contain some amount of suggestion or framing
+- they talk about a future that has not happened yet
 
-That is why “I would probably use that” is usually much weaker than “last week I spent three hours doing this manually.”
+People are usually unreliable when answering about opinion and imagined future behavior. They tend to overestimate their own interest, their own follow-through, and their own willingness to pay.
+
+That is why The Mom Test keeps reminding you:
+
+- do not trust praise for your idea too quickly
+- do not trust predictions about future behavior too quickly
+- bring the conversation back to what the user has already done in real life
+
+Compared with "Would you use this?", a question like "How did you handle this last time?" is usually much closer to truth.
 
 <a id="mom-principles"></a>
-## 3. Three Core Principles [↩ Back to top](#top-mom)
+## [3. Three Core Principles](#top-mom)
 
-### 3.1 Talk about their life, not your idea
+If you want to remember only the most important part first, remember these three principles.
 
-Many weak interviews begin with too much explanation of your product. Once you explain too much, the other person often shifts into “supportive mode.”
+### 3.1 Talk less about your idea and more about the user's real past experience
 
-Instead, ask about their actual experience:
+Many weak interviews start with too much explanation: your solution, your excitement, your product concept, your feature plan. Once you do that, the other person often shifts into "supportive mode."
+
+A better direction is to center the conversation on their real experience:
 
 - When was the last time this happened?
-- What were you doing?
+- What were you doing at the time?
 - How did you handle it?
-- Which part felt annoying or difficult?
+- Which step felt the most annoying?
 
-### 3.2 Ask about facts, not opinions
+Questions like these pull the conversation back into reality instead of keeping it in imagined preference.
 
-“Sounds useful” is weak.  
+### 3.2 Ask less about abstract opinions and more about concrete facts
-“I spent 3 hours doing this last week” is much stronger.
 
-Useful information usually looks like this:
+"That sounds useful," "Seems nice," and "I think I would like that" are all too abstract to guide product decisions.
 
-- I spent two hours on this last week
+Higher-value information usually looks more like this:
-- I am currently holding it together with Excel and chat
-- I already paid for something related to this
-- My real fear is making mistakes, not moving slowly
 
-### 3.3 Look for the problem, not their proposed solution
+- I spent two hours dealing with this last week
+- Right now I am holding it together with Excel and chat
+- I already paid for something related to this last month
+- My biggest fear is not slowness, it is making a mistake
 
-Users are usually better at describing pain than designing the right product.
+That kind of information helps you judge the intensity of the problem, how often it happens, and whether anyone might pay to solve it.
+
+### 3.3 Ask less about the user's preferred solution and pay more attention to how they solve the problem today
+
+Users are often good at describing pain, but not always good at designing the best product.
 
 If you ask:
 
-- Would you like an AI to do this automatically?
+- Would you want an AI to do this automatically?
 - Would a smart feature help?
 
-you often get a vague opinion about your idea rather than evidence about the problem.
+you usually get a vague opinion about a proposed solution, not evidence about the underlying need.
 
 Better questions are:
 
-- What do you do now?
+- What do you do today?
 - Why do you do it that way?
-- What is frustrating about that method?
+- What is bad about that method?
 
-## 4. Why People Give Nice but Unhelpful Answers
+Seeing the current workaround clearly is often more valuable than asking "What do you want us to build?"
 
-If you understand this, you make fewer mistakes during interviews.
+## 4. Why People Keep Giving Nice but Unhelpful Answers
 
-### 4.1 People want to be polite
+If you understand this part, you will make fewer mistakes during interviews.
 
-Especially when the person knows you, they often do not want to say:
+### 4.1 People naturally try to be polite
 
-- this does not sound very strong
+Especially when the person knows you, it is hard for them to say:
+
+- this direction does not sound very strong
 - I would never use this
-- this is not a real problem for me
+- this is not important enough for me
 
-So they soften the truth.
+They are much more likely to say something like "sounds interesting" or "could be useful."
 
 ### 4.2 People overestimate their future selves
 
-They sincerely believe they will:
+Many people honestly believe their future self will:
 
 - be more disciplined
-- be more willing to try something new
+- be more willing to learn
 - be more willing to pay
-- be more proactive next time
+- be more willing to try new tools
 
-That makes future-intention answers especially risky.
+So the sentence "I would probably use that" often does not mean they really will.
 
-### 4.3 Your question can secretly lead the answer
+### 4.3 Your question format is already shaping the answer
 
 When you ask:
 
-- Does this sound useful?
+- My idea sounds pretty good, right?
-- This feature would help, right?
+- This feature would help you, right?
 
-you are already hinting at the “good” answer.
+you are already hiding the "good answer" inside the question.
 
-That is one reason The Mom Test warns you not to turn interviews into a search for reassurance.
+That is one reason The Mom Test strongly warns you:
+
+**do not turn the interview into a search for reassurance.**
 
 ## 5. Weak Questions vs Better Questions
 
+These comparisons are useful because almost every beginner asks some version of them.
+
 | Weak question | Better question |
 | --- | --- |
 | What do you think of this idea? | When was the last time this happened to you? |
-| Would you use this? | How do you handle this now? |
+| Would you use this if it existed? | How do you handle this now? |
-| Would you pay for this? | Have you already spent time or money on this problem? |
+| Would you pay for this? | Have you already spent time or money on this problem? What did you spend it on? |
-| Does this feature matter? | What part of the process feels slow, frustrating, or risky? |
+| Is this feature important? | Which step in the process feels slowest, most frustrating, or least trustworthy? |
-| Would you want an AI to do this? | Why have you not found a better workaround yet? |
+| Would you want an AI to do this automatically? | Why have you not found a better workaround yet? |
 
-The key shift is:
+The most important thing in the table is not the wording itself, but the direction of the shift:
 
 - from opinion to fact
 - from future to past
-- from your solution to their problem
+- from your solution to the user's problem
 
 ## 6. A Simple Interview Flow You Can Use Right Away
 
+If you want to talk to someone now, you can use this order directly.
+
 ### 6.1 Open as a learner, not a seller
 
 For example:
 
-> I'm trying to understand how people deal with this in real life. I'm not selling anything right now.
+> I am trying to understand how people actually deal with this in real life. I am not selling anything right now.
 
-That lowers the pressure to encourage you.
+That makes it easier for the other person to drop the instinct to encourage you.
 
 ### 6.2 Start from the last real incident
 
-Good starting questions:
+Good opening questions are:
 
 - When was the last time this happened?
 - What happened?
 - What did you do first?
 
-Once the conversation enters a real event, information quality usually improves.
+Once the conversation enters one specific real event, the quality of the information usually improves a lot.
 
-### 6.3 Then ask about behavior, costs, and alternatives
+### 6.3 Then ask about behavior, cost, and alternatives
 
-- What do you do now?
+Continue with questions like:
-- What is annoying about that method?
+
+- What do you do today?
+- What feels worst about that method?
 - How much time, money, or energy does it cost?
-- What else have you tried?
+- Have you tried anything else? Why did you stop?
 
 ### 6.4 Only then judge pain and priority
 
-You do not need to ask “how painful is this?” directly. Look for clues:
+You do not have to ask directly, "How painful is this?" You can often judge it from the details:
 
-- does it happen often?
+- does this happen often?
 - are they already actively patching the problem?
-- have they already paid some cost?
+- have they already paid some real cost?
-- do they speak about it with emotion?
+- do they talk about it with visible frustration or emotion?
+
+Those clues are much more useful than asking, "Is this a pain point for you?"
 
 ## 7. A More Complete Example
 
-Suppose you want to build an AI resume-improvement product for students.
+Suppose you want to build an AI product that helps college students improve resumes.
 
 ### Weak questions
 
-> What do you think of an AI resume optimizer?  
+You ask a classmate:
-> If it automatically rewrote your resume for job descriptions, would you use it?
 
-Likely answers:
+> I want to build an AI resume optimizer. What do you think?  
+> If it could automatically rewrite your resume for a job description, would you use it?
+
+They will probably say:
 
 - sounds good
-- probably useful
+- I think that could be useful
-- I would try it if it was free
+- I would try it if it were free
 
-Those answers do not tell you much.
+Those answers give you almost no reliable signal about the actual strength of the demand.
 
 ### Better questions
 
-Try this instead:
+You can change the conversation to this:
 
 > When was the last time you edited your resume?  
-> Why did you need to edit it?  
+> Why did you need to change it?  
 > How did you do it?  
 > Which step felt hardest?  
-> Did you ask anyone for help?  
+> Did you ask anyone else to review it?  
 > Have you ever spent money or a lot of time on this?
 
-What you may learn:
+From these questions, you may learn things like:
 
-- many people do not mainly struggle with writing, but with tailoring
+- many people are not bad at writing, but bad at tailoring the resume for different roles
-- the biggest pain is often not formatting, but not knowing what belongs
+- the biggest pain is often not formatting, but not knowing which experience belongs
-- delay is often not laziness, but exhaustion from repeated revision
+- they delay not because they are lazy, but because every revision round drains them
-- current workarounds include seniors, templates, AI tools, and friends
+- current workarounds already include seniors, templates, AI tools, and friends
 
-That is much closer to truth.
+That gets you much closer to the real problem.
 
 ## 8. How The Mom Test Works with JTBD
 
-If JTBD helps you see what progress users are trying to make, The Mom Test helps you:
+If JTBD helps you see what kind of progress the user is trying to make, The Mom Test teaches you:
 
-**check whether that job is actually real.**
+**how to verify through interviews whether that job is actually real.**
 
-You can combine them like this:
+You can combine the two like this:
 
-1. use JTBD to draft a job hypothesis
+1. use JTBD to draft one job hypothesis
 2. use The Mom Test style questions to ask about the last real situation
 3. judge whether that job is frequent, painful, and worth prioritizing
 
@@ -273,14 +318,14 @@ Now validate it with questions like:
 
 That is how the two methods connect:
 
-- JTBD helps define the hypothesis
+- JTBD helps define the need hypothesis
 - The Mom Test helps validate it through conversation
 
 ## 9. Common Beginner Mistakes in Interviews
 
 ### 9.1 Turning the interview into a product presentation
 
-If you explain too much, the other person starts helping you instead of telling you the truth.
+If you explain too much about your idea, the other person starts helping you instead of telling you the truth.
 
 ### 9.2 Interviewing only friends
 
@@ -288,21 +333,21 @@ Friends are not useless, but they are more likely to encourage you. You need at
 
 ### 9.3 Asking about features too early
 
-If the problem is still unclear, detailed feature questions usually mean you are jumping into solutions too soon.
+If the problem is still unclear, detailed feature questions usually mean you are moving into solution mode too early.
 
-### 9.4 Treating “I would use it” as validation
+### 9.4 Treating "I would use it" as validation
 
-Interviews help you judge direction, but they are not the whole validation step. Real validation still depends on real cost: time, switching effort, trial behavior, or payment.
+Interviews can help you judge direction, but interviews are not the whole validation step. Real validation still depends on real cost: time, switching effort, trial behavior, or payment.
 
 ### 9.5 Not organizing what you learned
 
-If you do not整理 the conversation, it quickly becomes a blurry memory. Try to capture:
+If you do not organize the conversation afterward, it quickly becomes a blurry impression. Try to capture:
 
 - repeated problems
-- emotional words
+- emotional words in the user's own phrasing
 - current workarounds
-- already-paid costs
+- costs already paid
-- your new judgment
+- your updated judgment
 
 ## 10. A Reusable Question Checklist
 
@@ -332,44 +377,48 @@ If you want to start quickly, this set is broad enough for many interviews.
 
 - If this problem came up again, what would an ideal solution feel like?
 
-This is okay to ask near the end, but not at the start. First you need facts, not wishes.
+This is fine near the end, but it should not come first. Earlier in the conversation, you want facts more than wishes.
 
 ## 11. Summary
 
-The Mom Test is not mainly about charm or conversation skills. It is about building better judgment.
+The most important contribution of The Mom Test is not a set of "better conversation tricks." It is a more sober way to judge what you hear:
 
-Do not over-trust:
+- do not trust praise for your idea too quickly
+- do not treat "I would use that" as real demand
+- do not turn interviews into a search for approval
 
-- compliments
+The most useful conversations usually keep coming back to:
-- future promises
-- “I would probably use that”
 
-Trust more in:
+- the user's most recent real experience
+- how they handle the problem today
+- what cost they have already paid
+- where they feel obvious discomfort
 
-- recent real behavior
+When you start asking in this way, the answers may sound less flattering, but they are usually much more useful.
-- current workarounds
-- real costs already paid
-- repeated pain patterns
 
-Useful truth may sound less flattering, but it is far more valuable than encouraging noise.
+**In product work, useful truth is always better than encouraging noise.**
 
 <a id="mom-ai"></a>
-## 12. How AI Can Help with Interviews [↩ Back to top](#top-mom)
+## [12. How AI Can Help with Interviews](#top-mom)
 
-AI cannot replace real user interviews, but it can be a strong helper before, during, and after them.
+The Mom Test is still a method for talking to real people, so AI cannot replace real interviews. But AI is extremely useful before, during, and after interviews, especially for beginners who need structure.
 
 ### 12.1 Rewrite weak questions
 
-```text
+Many people know they should not ask, "What do you think of my idea?", but they still drift back to that kind of wording. You can ask AI to rewrite your draft questions first:
-I plan to ask users:
-1. What do you think of my AI resume tool?
-2. Would you use it?
-3. Would you pay for it?
 
-Please rewrite these using The Mom Test style.
+```text
+Below are the questions I plan to ask in user interviews:
+[paste your questions]
+
+Please rewrite them using The Mom Test principles:
+1. remove opinion-based questions
+2. remove future hypothetical questions
+3. turn them into questions about real past behavior, current alternatives, and real costs
+4. organize the result into 8-10 interview questions I can actually use
 ```
 
-A very beginner-style input is perfectly fine:
+A very beginner-style input also works:
 
 ```text
 I want to ask users:
@@ -383,29 +432,30 @@ Please turn these into better interview questions.
 Possible AI output:
 
 ```text
-Try asking:
+Rewritten questions:
+
 1. When was the last time you edited your resume?
 2. Why did you need to edit it?
 3. How did you do it?
-4. What part took the most effort?
+4. Which part took the most time?
-5. Did you ask anyone for help?
+5. Did you ask anyone else to review it?
 6. Have you ever spent money or a lot of time solving this?
 ```
 
-This is useful because it turns opinion-seeking questions into behavior-seeking questions.
+That output is useful because it turns opinion-seeking questions into behavior-seeking questions.
 
 ### 12.2 Create different interview guides for different user types
 
-The same problem feels different to students, hiring managers, and senior peers. AI can help generate separate interview guides for each group.
+The same problem feels different to different user groups. Students, HR people, and senior peers often care about different parts of the workflow. AI can generate separate interview guides for each group.
 
-Example input:
+For example:
 
 ```text
-I want to interview two groups:
+I want to talk to two groups:
-1. students applying for internships for the first time
+1. college students applying for internships for the first time
-2. seniors who often review resumes
+2. seniors who have reviewed many resumes
 
-Please create 6 interview questions for each group.
+Please create a 6-question interview guide for each group.
 ```
 
 Possible AI output:
@@ -424,10 +474,28 @@ For seniors:
 ...
 ```
 
+That makes interview prep much easier because you do not need to invent every question from scratch.
+
 ### 12.3 Sort interview notes into facts vs opinions
 
+After interviews, the problem is often not "too little information," but "too much scattered information." AI is good at turning messy notes into structured evidence:
+
 ```text
-Here are notes from one interview:
+Below are notes from 3 user interviews.
+Please organize them using The Mom Test:
+1. which parts are facts and which are opinions
+2. what the user's last real behavior was
+3. what the current workaround is
+4. what time, money, or effort cost they have already paid
+5. which problems show up repeatedly
+6. which statements sound positive but have weak evidence
+```
+
+Simple beginner input:
+
+```text
+Here are my notes from one interview:
+
 - she said she would probably try such a tool
 - last week she spent one full evening editing her resume
 - she currently asks friends for feedback
@@ -445,26 +513,26 @@ Opinion:
 Facts:
 - she spent one full evening editing her resume
 - she currently depends on friends for feedback
-- she struggles to tell when a resume is good enough
+- she is not sure when the resume is good enough
 
-Useful demand evidence:
+Useful evidence:
 - the problem happened recently
-- she has already paid a meaningful time cost
+- she already paid a meaningful time cost
-- her workaround depends on other people and is unstable
+- the current workaround depends on other people
 ```
 
-That makes it much easier for beginners to see which notes support a decision and which ones are just conversational noise.
+This is especially useful because it helps beginners separate "sounds nice" from "supports a real decision."
 
 ### 12.4 Do a light web search before interviews
 
-Before you even begin interviews, AI can help with a light external scan:
+Before interviews even begin, AI can help with a light external scan:
 
 - how people complain about the problem in public communities
-- what tools get criticized most often
+- which tools get criticized most often
-- whether users already spend money on related solutions
+- whether people already spend money on related solutions
 - what alternatives already exist
 
-Example input:
+Example prompt:
 
 ```text
 Please look up:
@@ -477,13 +545,13 @@ Possible AI output:
 ```text
 Common complaints:
 1. I don't know what belongs on the resume
-2. I have to rewrite it for every role and it's exhausting
+2. I have to rewrite it for every role and it is exhausting
-3. I keep editing but still don't know if it's good enough
+3. I keep editing but still do not know if it is good enough
-4. I don't have reliable feedback
+4. I do not have reliable feedback
 5. I keep delaying because I never feel ready
 ```
 
-This does not replace real interviews, but it helps you enter interviews with a better starting map.
+This does not replace real interviews, but it helps you enter them with a better starting map.
 
 ### 12.5 Ask AI to review your interview technique
 
@@ -493,12 +561,14 @@ You can also paste one interview transcript and ask AI to critique your question
 Here is a transcript from one user interview.
 Please review it using The Mom Test:
 1. Which questions sound like I was seeking reassurance?
-2. Which ones were leading?
+2. Which questions were leading?
 3. Where should I have asked more about facts?
 4. How could I ask this better next time?
 ```
 
-That is especially helpful for beginners because it trains the instinct to ask, “Am I collecting evidence or just collecting encouragement?”
+That is especially helpful for beginners because it trains the instinct to ask:
+
+**am I collecting evidence, or am I just collecting encouragement?**
 
 ## Assignments
 

docs/public/sitemap.xml

@@ -765,7 +765,7 @@
   </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/guide/introduction/</loc>
-    <lastmod>2026-03-02T02:20:17+08:00</lastmod>
+    <lastmod>2026-03-25T15:06:25+08:00</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.6</priority>
     <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/guide/introduction/"/>
@@ -788,7 +788,7 @@
   </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-0/</loc>
-    <lastmod>2026-03-02T02:20:17+08:00</lastmod>
+    <lastmod>2026-03-25T15:06:25+08:00</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.9</priority>
     <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/stage-0/"/>
@@ -810,13 +810,6 @@
     <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/1.0-finding-great-idea/"/>
     <xhtml:link rel="alternate" hreflang="en" href="https://datawhalechina.github.io/easy-vibe/en/stage-1/1.0-finding-great-idea/"/>
   </url>
-  <url>
-    <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/1.0-finding-great-idea/index.temp-0114254/</loc>
-    <lastmod>2026-03-25T01:55:32.527Z</lastmod>
-    <changefreq>weekly</changefreq>
-    <priority>0.9</priority>
-    <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/1.0-finding-great-idea/index.temp-0114254/"/>
-  </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/1.1-introduction-to-ai-ide/</loc>
     <lastmod>2026-03-25T08:37:27+08:00</lastmod>
@@ -899,7 +892,7 @@
   </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-double-diamond/</loc>
-    <lastmod>2026-03-25T06:31:44.977Z</lastmod>
+    <lastmod>2026-03-25T15:06:25+08:00</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.9</priority>
     <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-double-diamond/"/>
@@ -907,10 +900,11 @@
   </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-idea-sources/</loc>
-    <lastmod>2026-03-25T06:47:22.347Z</lastmod>
+    <lastmod>2026-03-25T17:13:40+08:00</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.9</priority>
     <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-idea-sources/"/>
+    <xhtml:link rel="alternate" hreflang="en" href="https://datawhalechina.github.io/easy-vibe/en/stage-1/appendix-idea-sources/"/>
   </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-industry-scenarios/</loc>
@@ -922,7 +916,7 @@
   </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-jobs-to-be-done/</loc>
-    <lastmod>2026-03-25T06:31:44.976Z</lastmod>
+    <lastmod>2026-03-25T15:06:25+08:00</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.9</priority>
     <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-jobs-to-be-done/"/>
@@ -930,7 +924,7 @@
   </url>
   <url>
     <loc>https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-mom-test/</loc>
-    <lastmod>2026-03-25T06:31:44.976Z</lastmod>
+    <lastmod>2026-03-25T15:06:25+08:00</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.9</priority>
     <xhtml:link rel="alternate" hreflang="zh-CN" href="https://datawhalechina.github.io/easy-vibe/zh-cn/stage-1/appendix-mom-test/"/>

docs/zh-cn/stage-1/appendix-double-diamond/index.md

@@ -48,7 +48,7 @@ const duration = '约 <strong>1.5 小时</strong>'
 4. 如何把双钻模型用在 AI 产品、原型设计和需求验证里
 
 <a id="dd-what"></a>
-## 1. 双钻模型到底是什么 [↩ 回到开头](#top-dd)
+## [1. 双钻模型到底是什么](#top-dd)
 
 双钻模型是英国 **Design Council** 推广的一套经典设计流程框架。它把一个完整的设计与创新过程，画成两个连续的钻石形状。
 
@@ -100,7 +100,7 @@ const duration = '约 <strong>1.5 小时</strong>'
 - 不要因为原型看起来完整，就默认用户会真的需要
 
 <a id="dd-first"></a>
-## 3. 第一个钻石：做对的事情 [↩ 回到开头](#top-dd)
+## [3. 第一个钻石：做对的事情](#top-dd)
 
 第一个钻石关注的是 **问题本身** ，而不是解决方案。
 
@@ -361,7 +361,7 @@ AI 产品特别容易掉进“能力先行”的坑里，因为模型能力看
 **先做对的事情，再把事情做对。**
 
 <a id="dd-ai"></a>
-## 11. 如何利用 AI 帮你跑双钻流程 [↩ 回到开头](#top-dd)
+## [11. 如何利用 AI 帮你跑双钻流程](#top-dd)
 
 双钻模型本身不是 AI 工具，但 AI 很适合在四个阶段里充当“加速器”。关键不是让 AI 替你决策，而是让它帮你扩展视野、整理信息、比较方案和生成验证材料。
 

docs/zh-cn/stage-1/appendix-jobs-to-be-done/index.md

@@ -48,7 +48,7 @@ const duration = '约 <strong>1.5 小时</strong>'
 4. 如何把 JTBD 用在 AI 产品、访谈提问和提示词整理里
 
 <a id="jtbd-what"></a>
-## 1. 什么是 Jobs to Be Done [↩ 回到开头](#top-jtbd)
+## [1. 什么是 Jobs to Be Done](#top-jtbd)
 
 Jobs to Be Done 常被简称为 **JTBD**。它背后的核心想法，和 Clayton Christensen 团队推广的那句经典表达有关：**用户会“雇用”某个产品来完成一件事。**
 
@@ -184,7 +184,7 @@ JTBD 更关心的是下面这些问题：
 如果你连“用户怎么判断值不值”都说不清，那这个方向大概率还没有收敛好。
 
 <a id="jtbd-formula"></a>
-## 5. 直接套用的一句话公式 [↩ 回到开头](#top-jtbd)
+## [5. 直接套用的一句话公式](#top-jtbd)
 
 当你想梳理一个产品方向时，可以先套这个非常实用的句式：
 
@@ -341,7 +341,7 @@ Jobs to Be Done 最有价值的地方，不是给你一个新名词，而是帮
 做产品，尤其是做 AI 产品，最怕的是一开始就沉迷能力展示。JTBD 能帮你把注意力拉回到真正重要的地方：**用户为什么需要你，以及你到底在帮他完成什么进展。**
 
 <a id="jtbd-ai"></a>
-## 12. 如何利用 AI 帮你实践 JTBD [↩ 回到开头](#top-jtbd)
+## [12. 如何利用 AI 帮你实践 JTBD](#top-jtbd)
 
 JTBD 不是 AI 发明的，但 AI 很适合在这套方法里当你的研究助手、整理助手和对照助手。关键是：**让 AI 帮你整理和扩展，而不是替你臆测用户。**
 

docs/zh-cn/stage-1/appendix-mom-test/index.md

@@ -56,7 +56,7 @@ The Mom Test 这套方法，就是专门用来解决这个问题的。它提醒
 4. 如何把 The Mom Test 和 JTBD、需求验证、MVP 判断连起来使用
 
 <a id="mom-what"></a>
-## 1. The Mom Test 到底是什么 [↩ 回到开头](#top-mom)
+## [1. The Mom Test 到底是什么](#top-mom)
 
 The Mom Test 来自 Rob Fitzpatrick 的同名书籍。它的名字听起来有点像玩笑，但点得非常准：
 
@@ -105,7 +105,7 @@ The Mom Test 主要解决的是一种非常常见的认知错觉：
 因为和“你会不会用”相比，“你上次怎么处理这件事的”往往更接近真相。
 
 <a id="mom-principles"></a>
-## 3. 三个最核心的原则 [↩ 回到开头](#top-mom)
+## [3. 三个最核心的原则](#top-mom)
 
 如果你只想先记住最重要的部分，可以先记下面这三个原则。
 
@@ -394,7 +394,7 @@ The Mom Test 最重要的贡献，不是给你一套“更会聊天”的技巧
 而做产品时，**有用的真相，永远比好听的鼓励更重要。**
 
 <a id="mom-ai"></a>
-## 12. 如何利用 AI 帮你做用户访谈 [↩ 回到开头](#top-mom)
+## [12. 如何利用 AI 帮你做用户访谈](#top-mom)
 
 The Mom Test 本质上还是一套“和真人聊”的方法，所以 AI 不能替代真实访谈。但 AI 非常适合在访谈前、中、后给你打辅助，尤其适合帮新手降低门槛。