The AI Capability Dictionary
Twenty concepts, and the dozens of features beneath them, defining how modern AI actually works. Written for leaders who need to evaluate AI, not just experiment with it.
Focus less on the vendor. Focus more on the capability.
This guide will not try to sell you a platform. The features it explains, things like context, projects, memory, connectors, agents, and MCP, are appearing across Copilot, Claude, ChatGPT and Gemini alike. Understand the capability, and you can evaluate any tool that claims to have it.
Chat is becoming workflows. Workflows are becoming tools. Tools are becoming agents. Agents are becoming digital teammates.
From the closing chapter
Twenty entries, one per capability
Each entry opens with a plain-language definition, then explains what it means for real operations.
Built like a dictionary, written like a briefing
Every capability gets a headword, a one-sentence definition, and then the part most guides skip: what it changes about how your business runs.
Related features are nested underneath, so Agents also covers subagents, agent teams, and dynamic agents.
Def. Autonomous AI systems capable of completing multi-step tasks and workflows with limited human supervision.
Think of the difference between an employee who answers questions and an employee who owns a process. An agent could review incoming documentation, identify missing information, generate requests, notify responsible parties, and track responses.
You don't need all twenty at once
Most organizations are somewhere between Phase 1 and Phase 2 today. The guide closes with a four-phase roadmap so you know what to build next.
Written for the people making the call
Evaluate technology investments and spot opportunities without needing to become technical.
See where AI attaches to the workflows your teams already run every day.
Get shared vocabulary for connectors, MCP, permissions and agent architecture.
Get The AI Capability Dictionary
Twenty entries. Vendor-neutral. Free.
