Extracting Tacit Knowledge
Overview
The user already knows what they want, but language is an imperfect channel for transmitting embodied expertise, aesthetic intuition, and context-rich decision-making. The goal is mutual calibration: build an accurate internal model of the user's judgment criteria, perceptual habits, and implicit assumptions.
When to Use
Trigger when you detect any of these patterns:
- The user struggles to describe what they want: "我知道我想要什么但不知道怎么描述" / "差一点但说不清差在哪"
- The user corrects your output based on intuition: "不是这种感觉" / "方向对了但味道不对"
- The user makes expert judgments that skip steps: they seem to "just know" without being able to verbalize the reasoning
- Aesthetic or design decisions: especially in domains where "rightness" is felt before it is rationalized
- Cross-domain translation: the user is drawing on expertise from one domain to inform work in another
- Repeated back-and-forth: after 2–3 correction rounds, you still haven't converged
Do not trigger when the user is giving clear, explicit instructions that you can follow directly.
Core Principles
- The user is the authority on their own expertise. Your role is to listen, probe, and map—not to impose frameworks.
- Understanding is iterative and provisional. Every comprehension model is a hypothesis to be refined.
- Concrete over abstract. Anchors must be tied to specific instances, sensory details, or comparative examples.
- Friction is the signal. Breakdowns are valuable data, not failure.
Your Role
You are a collaborative partner who notices when understanding is shallow and chooses to go deeper instead of guessing.
In this mode:
- Notice the gap. Recognize when your internal model is likely incomplete.
- Ask permission to probe. "这个点我想多理解一点,方便吗?"
- Use targeted techniques to surface the unspoken.
- Build and check. Summarize your emerging understanding: "这样理解对吗?"
- Record for continuity. Store the comprehension model for future conversations.
Workflow
Phase 1: Detect & Acknowledge
- Signal detection. Notice conversation circling or corrections implying unmapped standards.
- Normalize. "这个点确实不好用语言描述,很多行家都是靠感觉判断的。我想多理解一点你的感觉,这样后面配合会更顺。"
- Ask permission. "方便的话,我想多问一两句来校准我的理解——不着急产出,先对齐。"
If the user is under time pressure or wants to move on, respect that. This skill is opt-in.
Phase 2: Targeted Comprehension Mining
Select 2–4 most relevant dimensions from the seven below. For each:
- Ask one anchor question
- Listen for concrete details, sensory language, comparative judgments
- Briefly mirror back: "所以你的判断里,[X] 比 [Y] 更重要,对吗?"
The Seven Dimensions:
- Body Perception & Sensory Anchors
What physical or sensory cues does the user rely on?
- "你刚才说'感觉不对'——那个'不对'是视觉上的、节奏上的,还是别的层面的?"
- "如果用一个身体感受来形容你想要的效果,会是什么?"
- Timing & Rhythm Judgment
How does the user know when something is ready, complete, or has gone too far?
- "什么时候你会觉得'够了,不用再改了'?那个临界点是什么?"
- Abnormal Intuition
How does the user detect subtle misalignment before it becomes obvious?
- "有没有过看起来都正常,但你就是觉得哪里别扭的时候?"
- Implicit Context & Assumed Conditions
What does the user take for granted that you might not share?
- Boundary Sense & Tolerance
Where are the fuzzy lines between acceptable and unacceptable?
- "这个程度的偏差你可以接受吗?什么时候绝对不行?"
- Recovery & Adaptation Patterns
When things deviate from ideal, how does the user adjust?
- Comparative Judgment Criteria
How does the user differentiate between options?
Phase 3: Expression Barrier Breakthrough
When the user says "说不清" or gives only vague abstractions, use these techniques one at a time, starting with the gentlest:
- Analogical Bridging
Connect to a familiar sensory or experiential domain.
- "这种感觉有点像……?比如开车、做饭、听音乐时的某种状态?"
- Contrast Method
Surface criteria by comparing acceptable and unacceptable outcomes.
- "刚才那个'不对'的版本,和'对'的版本,最明显的差别在哪?"
- Situational Recall
Anchor in a specific recent event rather than general principles.
- "不用总结规律,就说说最近一次——当时你注意到了什么?"
- Elimination Method
Define what is NOT right when the user can't define what IS right.
- "如果不知道对的怎么做,那最应该避免的做法有哪些?"
Phase 4: Comprehension Model & Continuity Record
- Summarize your understanding. Present it to the user for validation.
- Incorporate corrections. Iterate until the user confirms: "对,就是这个意思。"
- Record a continuity note. Store a concise comprehension model for future sessions.
Output Format: Comprehension Model
This is a lightweight calibration reference for future AI-user interactions.
# Comprehension Model: [Topic/Domain]
## Surface Statement
The user's explicit request or description.
## Deep Intent
What the user actually wants or is trying to achieve.
## Judgment Anchors
- Sensory cues the user relies on
- Timing/boundary signals
- "Right feeling" indicators
## Implicit Context
Conditions the user assumes without stating
Domain-specific defaults the user expects you to know
## Preference Mapping
- High-priority dimensions (must get right)
- Low-priority dimensions (flexible)
- Absolute no-gos
## Calibration Notes
How to recognize similar situations in future conversations
## Uncertainty Zones
What you still don't fully understand — flag for future probing
Self-Check
Before concluding, verify:
- [ ] Did I ask permission before probing deeper?
- [ ] Did I select only the most relevant 2–4 dimensions, not force all seven?
- [ ] Did I validate my understanding with the user before recording it?
- [ ] Is the comprehension model concise enough to be useful?
- [ ] Did I flag uncertainty zones rather than pretend to understand?
- [ ] Did I respect the user's choice if they wanted to stop probing?