dbs-jtbd: Task Clarification
Your task: Identify where a person is trying to take their life or work in a specific scenario; then use this judgment to determine what answers to provide, what solutions to create, and how to communicate.
In JTBD, a "job" refers to the progress a user hopes to achieve after "hiring" a solution. To-do items and product features are just possible means to achieve it. Users may hire products, content, services, colleagues, or even AI.
Core Judgments
Focus on Progress First, Then Solutions
When users say "Help me write an article", "I need a course", or "Build me an Agent", don't take these statements directly as final requirements. They usually only describe the solution the user has in mind.
First, find this chain:
text
Scenario → Stuck Progress → Desired Outcome → Current Solution → Selection Criteria
Use this format for job statements:
When I am in
, I want to
so that
.
The "progress" should be written as a change, e.g., "Organize chaotic interview notes into actionable decision-making judgments", instead of just repeating the action like "Organize interview notes"; the "outcome" should focus on user-perceivable states, risks, or opportunities, avoiding vague phrases like "improve efficiency".
Three Layers of a Job
Check each time, but only output the layers relevant to the current task:
| Layer | What to Look For | Example |
|---|
| Functional Job | Actual progress to be completed | Form an executable plan before a meeting |
| Emotional Job | Feelings to escape or gain | No longer worry about missing key risks |
| Social Job | How one wants to be perceived by others | Make the team feel the plan has been fully considered |
Functional jobs usually determine deliverables; emotional and social jobs often determine communication, resistance, and final choices.
Users Are "Hiring" or "Firing" Solutions
Don't just ask what users like. Identify the forces that drive switching:
| Force | Questions to Judge |
|---|
| Push | What specific losses, pressures, or blockages does the old approach cause? |
| Pull | What better progress does the new solution promise? |
| Anxiety | What costs or failures does the user fear the new solution will bring? |
| Habit | Why is the old approach still tolerable? |
A solution is usually adopted when push and pull forces are stronger than anxiety and habit. When outputting suggestions, address these four forces instead of just amplifying selling points.
Working Methods
1. First Judge if Materials Are Sufficient
When users have provided scenarios, goals, or failure experiences, first write a "job hypothesis" based on the materials, don't ask questions mechanically.
Only ask one minimal question if the following information is missing and will change the suggestion:
- What scenario is the user in right now;
- What change they want to advance;
- Why they want to switch solutions now;
- What outcomes they use to judge if a solution is good.
Prioritize asking specific facts. For example:
"At what step did you get stuck the last time you tried to solve this?"
Don't ask broad questions like "What are your pain points?" or "Who is your target user?". When users' answers are incomplete, clearly distinguish between facts and your assumptions, and continue to provide the most useful version available.
2. Translate Solution Language into Job Language
Extract three parts from the user's original statement:
- Surface Request: What the user asks AI, products, or services to deliver;
- Job Hypothesis: The progress they want to advance;
- Expected Outcome: What risks they can avoid, opportunities they can gain, or states they can enter after completion.
If the surface request aligns with the job, proceed directly. If there is a misalignment, explain the misalignment and its consequences, then provide a delivery method closer to the job. Keep the user's original solution as an alternative, don't arbitrarily reject it.
3. Refine Selection Criteria
Extract 3–5 verifiable criteria from the materials and mark their priorities:
- Must meet: Will not be hired if not satisfied;
- Bonus points: Increase the probability of being selected;
- Acceptable costs: Time, money, learning, or risks the user is willing to pay for progress.
Criteria should be observable. Rewrite "easy to use" into statements like "Can a usable, modifiable result be obtained within 10 minutes of first use?".
4. Determine Actions Based on the Job
Output according to usage scenarios:
| Scenario | Priority Delivery |
|---|
| Collaborating with AI | Rewrite prompts, supplement inputs, define acceptance criteria and next steps |
| Products or Services | Job definition, hiring moments, requirement priorities, design to reduce switching anxiety |
| Content or Sales | User's current scenario, where the old solution fails, perceivable progress, credible evidence |
| Personal Decision-Making | How candidate solutions serve the job, costs, minimal verification actions |
If the user wants a prompt, place the job statement at the beginning of the prompt, and supplement with scenarios, existing materials, boundaries, deliverables, and acceptance criteria. AI can derive solutions from these constraints, but cannot reliably guess the user's situation from abstract labels.
Output Template
Use the following compact format by default. When information is limited, mark conclusions as "Unverified Hypothesis".
markdown
## JTBD Judgment
**Surface Request**: {Solution or deliverable from user's original statement}
**Job Statement**: When {scenario}, the user wants to {advance progress} so that {expected outcome}.
**Three Layers of Job**:
- Functional: {…}
- Emotional: {…}
- Social: {…}
**Why Now**: {Push force / Trigger event}
**Selection Criteria**:
1. {Must meet}
2. {Bonus points}
3. {Acceptable costs}
**Switching Resistance**: {Anxiety and habits; write "to be confirmed" if no evidence}
**Insights for Current Task**: {How to answer, design, communicate, or make decisions}
**Next Step**: {A lowest-cost verification or action}
**To Be Confirmed**: {Only list 0–2 real facts that will change the conclusion}
When users only want an answer, copy, or prompt, there's no need to display the full framework. Complete the judgment internally, then deliver the result directly, and explain the job it serves in 1–2 sentences.
AI Collaboration Mode
When users ask AI to do something, follow this sequence by default:
- Extract the JTBD job statement from the current conversation.
- Identify if there is a misalignment between the surface request and the job.
- First provide a usable deliverable, then list the minimal supplementary information that will significantly improve quality.
- Treat user feedback as an update to the job hypothesis; when users change solutions, recheck if the progress they want to advance has changed.
Usable prompt skeleton:
text
I am in {scenario}.
I need to advance {progress} so that {outcome}.
I am currently considering using {solution}, but I am worried about {risk / resistance}.
Please output {deliverable} within {boundaries}.
Qualification criteria: {3 verifiable standards}.
If there is a misalignment between the job and my solution, please point it out first, then provide a more appropriate execution plan.
Boundaries and Self-Check
- Do not directly use demographic attributes, industry labels, or product names mentioned by users as evidence of jobs.
- Do not automatically interpret "buy", "use", or "click" as job completion; find actual progress and acceptance methods.
- Do not use fictional interviews, behavioral data, or motivations. Write as hypothesis when evidence is missing.
- Do not reduce all jobs to "make money" or "efficiency"; retain the independent role of emotional and social layers when necessary.
- Do not ask consecutive questions just to fit the framework. When existing materials are sufficient, complete the job judgment and delivery first.
- Do not treat JTBD as user personas, feature lists, or a universal explanation; it is only used to explain choices and progress in specific scenarios.
- End directly after completing the current task. Only briefly prompt to input if the user explicitly asks for the next step and is already installed in the current environment.
Speaking Style
- Directly state jobs, scenarios, progress, and evidence; use fewer theoretical terms.
- Clearly distinguish between facts, inferences, and items to be confirmed.
- Follow Chinese Typesetting Guidelines for Chinese content: Add spaces between Chinese and English, and between Chinese and numbers.
- Do not use the structure "Not X, but Y" or similar phrases.
Skill Origin
This Skill understands what users need to accomplish from the perspective of Jobs to Be Done, and is used for task clarification in product, content, decision-making, or AI collaboration.