How to Pass on a Veteran Expert's Experience: Turning Tacit Knowledge Into a Searchable AI Assistant
One of the biggest risks in manufacturing and traditional industries is that decades of technical judgment disappear the moment a key veteran retires or leaves. This article explores how systematic knowledge extraction can turn tacit knowledge into a format your AI assistant can learn from.
8 min read (Chinese original) · 2026-06-15
A veteran expert retiring isn't just a staffing problem — it's the disappearance of decades of judgment, and AI can become the container that preserves it.
Who this is for
Manufacturing and traditional-industry owners, and managers facing the risk of senior staff retiring or leaving
Key takeaways
- ✓Tacit knowledge can't be fully captured by video or manuals alone — it needs systematic knowledge-extraction interviews
- ✓Good extraction questions probe decision conditions, not just operating steps
- ✓Once extracted, you can build a decision knowledge base, a troubleshooting guide, and quality judgment standards
- ✓This challenge isn't unique to manufacturing — services, healthcare, and consulting face it too
- ✓The best time to act is while the key person is still on staff, not after they've announced they're leaving
Implementation steps
- 1.Identify the key knowledge-holders in your company and assess how irreplaceable their knowledge is and their flight risk
- 2.Design an interview framework focused on decision conditions and situational judgment, not just operating steps
- 3.Conduct systematic interviews, recording the key person's judgment logic and real cases
- 4.Structure the interview content into a format AI can search
- 5.Build an AI assistant so new hires can access the veteran's judgment through Q&A
Common mistakes to avoid
- ✗Only starting to worry once the veteran announces retirement, leaving no time to organize properly
- ✗Recording only operational videos, without capturing decision conditions and situational judgment
- ✗Asking "how do you do this" instead of "under what conditions do you do this"
- ✗Not involving the knowledge-holder in review, leading to inaccurate extraction
- ✗Never building a searchable system after the interviews, so the knowledge stays hard to use
This is an English summary. The full article, with detailed walkthroughs and examples, is currently available in Traditional Chinese.
Read the full Chinese article