Tag: knowledge-management
Do you need a director of ontology for AI agents?
A director of ontology builds the shared vocabulary AI agents reason over. Capital One, Novartis and Lockheed Martin are hiring for the work, yet UK ads citing ontologies were 0.035% of permanent job ads in the six months to October 2026. Most companies should start with typed files instead.
Your AI context layer is only half a brain
An AI context layer feeds every model one governed source of company truth, and DataHub and Atlan will sell you that read half today. The half that notices when a person did not get what they wanted, the re-ask nobody logged, is what turns a knowledge store into a brain.
Ask Your Org, and the case for scoping Claude yourself
Claude Ask Your Org connects Claude to Slack, Microsoft 365, and Drive in one project. Its security model is sound, permission-aware and not indexed. The question it makes easy to skip is scope. Here is when to use the broad tool and when to scope Claude yourself with a filesystem MCP server.
The forgetting curve is the math behind your make-or-buy decision for knowledge work
Humans forget 58% of new information in 20 minutes, 75% in a day, 90% in a week. Ebbinghaus measured this in 1885 and Murre replicated it cleanly in 2015. The forgetting curve is the cognitive-science substrate that decides which retention-critical knowledge work AI can structurally replace at a mid-size company.
Why your company processes should improve themselves using Claude
Processes that update their own documentation sound impossible until you see the architecture. An LLM compiler reads raw organizational data and writes structured process wikis that compound institutional knowledge automatically. Here is how to build it and what breaks.
Claude Projects as your team prompt library
80% of effective prompting is context and setup. Only 20% is the actual question. Most teams optimize the wrong end. A company context document in Claude Projects turns generic AI into AI that understands your business and survives employee turnover.
Your AI center of excellence should work itself out of a job
Most AI centers of excellence become permanent bureaucratic bottlenecks that slow adoption instead of accelerating it. With very few organizations qualifying as AI high performers, Peter Drucker was right: build distributed capability, then dissolve the support structure.
AI multiplies consultant expertise without replacing consultants
Professional services firms are using AI to scale expertise rather than cut headcount. A Harvard Business School study found junior consultants improve productivity by 43% with AI tools, while experienced partners multiply their impact across more clients.
Claude Projects for team collaboration - the honest guide
Your team uses Claude but everyone has different prompts and context. Claude Projects by Anthropic treats AI as shared working memory, not documentation that goes stale. A Microsoft case study found most new developer tasks involve relearning things someone already knows.
Claude Projects: your new knowledge management system
Replaced three knowledge tools with Claude Projects. It is knowledge that answers questions instead of requiring search. The wiki is dead. Traditional knowledge management systems store information that nobody finds. Claude Projects turn your documentation into conversations that actually help your team get work done faster.
Multi-source RAG: Why diversity beats quality
An ACM study found multi-source RAG systems achieve 62% distinct word coverage versus 52% for single-source approaches. Five good knowledge sources often outperform two excellent ones because diversity of perspectives matters more than individual source quality for building real user trust.
The prompt library that changed our productivity
Building a prompt library of 500+ prompts as living documentation at Tallyfy. How systematic organization, version control, and team adoption turn individual tools into organizational assets.