· 5 min read
How to capture tacit knowledge with AI
Documents give AI agents the what. Learn how a 5 to 7 minute AI interview and three circles of context capture the how and the why. Checklist included.
ReadField notes on AI agents and context
Guides, comparisons and research from the team building Dactic.
What is context engineering for business teams?
Context engineering is how teams give AI agents the right information at the right moment. A plain-English guide for operations leaders.
Dactic vs hiring an AI consultant
Traditional consulting: $300,000+ and 6+ months. Compare it with Dactic on cost, time to first agent, what you own and whether it stays current.
Dactic vs building your own RAG: which fits your team?
Should you build RAG in-house or use a context layer? A side-by-side on cost, upkeep, accuracy and what each one can capture.
Tacit AI: what tacit knowledge in the AI layer is, and why it matters
Tacit AI means giving AI agents the judgment your best people never wrote down. Learn what it is, where it sits in the AI stack, and why it matters.
Tools for capturing tribal knowledge before a key employee leaves
Compare five kinds of tools for capturing tribal knowledge before a key employee leaves, from wikis to AI interviewers, with a plan for the notice period.
Why do AI agents fail at work?
Most AI agents fail at work for the same four reasons, and the model is rarely one of them. Here is what goes wrong and how teams fix it.
What is a context layer for AI agents?
A context layer gives AI agents your systems, rules and unwritten know-how so they act like your best people. How it works and when you need one.
Least Privilege for AI Agents: A Security Review Checklist
A vendor wants read access to your employees' email, chat, calendar, and files. In exchange, it will deploy autonomous agents into your workspace that take actions on behalf of your staff.
Why Vector Search Is Not Enough for Agent Grounding
You built the RAG pipeline. Chunking is tuned, embeddings are solid, retrieval precision looks good on your eval set. The agent still gets things wrong in production, and the failures are strange.
The Real Cost of AI That Almost Works
Your team bought an AI tool. It works. Nobody uses it. That is not a contradiction. It is the most common outcome of enterprise AI deployment, and it happens for a reason that shows up nowhere on the invoice.
