Without adding to workloads.
Knowledge trapped in heads can't transfer to anyone or anything. There's a way to capture it without making it anyone's job.
Your experienced people know how things actually work. The workarounds. The exceptions. The things that aren't in any manual.
When they get sick, take vacation, or leave for a new job, that knowledge goes with them. Suddenly, no one knows how things work.
You've tried asking people to document their work. It never happens. Or it happens once and never gets updated.
The same knowledge gap blocks AI capability.
You want to build AI capability. But AI can only work with knowledge that's been extracted and encoded. What's in people's heads isn't available.
Your AI doesn't handle the exceptions or understand the context. Because that knowledge was never articulated. It can't learn what was never explained.
You automated a process but it doesn't work like the expert did it. Because the AI was trained on documentation, not on how things actually work.
Knowledge that lives in heads can't transfer.
Not to new people. Not to AI. Not to anything.
You ask busy people to document what they know. They're already at capacity. They have no time to add a new task.
“Please document your processes”
It gets pushed to “when I have time”
“When I have time” never comes
Knowledge stays in heads
Documentation becomes another thing
that doesn't get done.
The problem isn't willingness. It's capacity.
The solution isn't asking more. It's asking differently.
Fix Perspective
The problem isn't willingness. It's capacity. Your people want to help. They just can't add documentation to their already full workload. So knowledge stays trapped.
Enhance Perspective
You can't skip extraction and go straight to AI. You think you'll just “add AI” and it will figure things out. But AI can only work with what's been articulated. No extraction means no foundation for AI to build on.
Active effort required
Ask people to write down what they know
Adds to their existing workload
Burden falls on the knowledge holders
Rarely happens, quickly outdated
Capture what's happening
Observe and record existing work
No additional tasks for anyone
Burden falls on the extraction process
Happens naturally, stays current
The difference is where the burden falls.
Extraction captures knowledge without adding to anyone's plate. And that knowledge powers both human transfer and AI capability.
Two outcomes from one process:
You know how it works now. Someone new starts. They shadow the person who knows everything for a week. That expert explains how things really work, not how the manual says they work. Three months later, they leave. And now you need someone else to become that person.
Or you try to build AI that does what they did. But the AI doesn't know what they knew.
New people wait for the right person to be free
Your best people spend time teaching instead of building
Every departure is a scramble
AI can't replicate what experts do
New people learn without interrupting anyone
Your best people stay focused on high-value work
Departures are transitions, not emergencies
AI actually works because it has what experts know
Fix Perspective
This connects to Total Ownership. The knowledge lives in systems you own. Not in people who might leave. Not in vendors who could raise prices. In your systems.
→ See Total OwnershipEnhance Perspective
This is what makes AI work. AI capability isn't magic. It's extracted knowledge, encoded and deployed. The AI that works like Sarah is the AI that has what Sarah knows.
The uncomfortable question every business should ask:
“How many people could leave before critical operations fail?”
The uncomfortable question before building AI:
“What happens when you build AI on knowledge that was never extracted?”
Extraction improves both numbers.
Without putting the burden on the people who have the knowledge.
Maybe you already know who holds the knowledge. And you know what happens if they leave before you capture it. Or maybe you're planning to build AI capability and you realize it needs a foundation of extracted knowledge to actually work.
They keep working. You get the knowledge. It stays when they don't. And it powers what you build next.
Questions from founders who need knowledge out of heads and into systems.
Documentation adds to workloads. Extraction doesn't. Traditional documentation asks busy people to stop doing their job and write down how they do it. That never happens because they're already at capacity. Extraction captures knowledge from what's already happening. Conversations, decisions, processes in motion. The burden falls on the extraction process, not the people who hold the knowledge. That's why it actually works.