AI knowledge management uses artificial intelligence to capture, connect and deliver knowledge. The biggest lever is the unwritten knowledge created in daily work. A shared AI memory like Hebby captures it automatically and brings it to where it's needed.
The problem: knowledge evaporates
Every team knows it. Why was that solution chosen back then? Who knows how the old system ticks? What went wrong in the last release? The answers rarely sit in a wiki. They're stuck in heads, chats and meetings. And they vanish when someone leaves, goes on holiday or simply no longer remembers.
With AI agents the problem gets worse. More and more work happens in sessions with Claude Code, Codex or other assistants. Decisions and insights pile up by the minute there. And when each session ends, they're gone.
What is AI knowledge management?
AI knowledge management uses artificial intelligence to capture, organize and deliver knowledge. Classic approaches rely on search: the AI combs through documents, wikis and tickets and answers questions from them. That's useful, but it only covers what someone wrote down.
The bigger treasure is unwritten knowledge: reasons, experience, connections. And that is exactly what increasingly emerges in work with AI agents.
One shared memory for all agents
This is where an AI memory like Hebby comes in. Instead of documenting knowledge after the fact, Hebby captures it while the work happens:
- Captured automatically: Decisions, insights and pitfalls from your sessions land in Hebby.
- Shared: Several agents, machines and team members use the same memory. What one learns, everyone knows.
- With permissions: You set per agent and per person who may know what. Team knowledge is shared, private stays private.
- Proactive: Hebby brings knowledge on its own to where it's needed, linked through its own graph memory.
The best knowledge management is the kind nobody has to do extra work for.
What teams get out of it
- Faster onboarding: New agents and colleagues benefit from the collected knowledge from day one.
- Fewer repeat mistakes: What went wrong once comes up in time.
- Less dependence on individuals: Knowledge stays, even when people change.
- More speed: No explaining, no searching. The agents already know.
The result is a team memory that thinks along. Modeled on human memory, built by psychologists in Germany.
Hebby Memories: the second brain for Claude Code, Codex & co. Learns as you work, thinks ahead, never forgets what matters. Get Early Access →
Frequently asked questions
What is AI knowledge management?
AI knowledge management is the use of artificial intelligence to capture, organize, connect and deliver knowledge in teams and companies when it's needed.
Which tools are there for AI knowledge management?
The range runs from AI features in wikis and note apps through enterprise search to AI memories for agents. Hebby belongs to the last group and captures the knowledge created when working with AI agents.
How do AI agents share knowledge in a team?
Through a shared memory. Hebby can be used by several agents and machines at the same time. What one agent learns is available to all.