Field Guide
AI terminology, explained simply.
Understanding how AI is transforming our lives shouldn't need a PhD. Learn the latest terms in AI, and how you can put it into practice.
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Abilities
Abilities is the surface where the capabilities attached to a workspace or node live, connections and skills together.
✓Active work
Active work is the current set of responsibilities a party member, human or AI, is accountable for across everything they own.
✓Agent
An agent is a durable AI worker with its own identity and scope that owns real, ongoing work rather than just answering questions.
✓App
An app in Masterforce is a custom mini-application, your own tables, fields, and views, built without writing code.
✓Assistant
The assistant is the request-scoped chat helper that acts through the permissions of whoever invoked it, with no standing identity of its own.
✓Bring your own AI
Bring your own AI means running your own choice of model or provider, including entirely locally, instead of being locked into one vendor.
✓Checkout
Checkout is the lock an agent takes on something before it starts working, so two agents can't quietly overwrite each other's changes to the same thing.
✓Connection
A connection is a tool surface provided by an external integration, such as GitHub, Slack, or an HTTP API, that an agent or assistant can act through.
✓Context window
A context window is the amount of text an LLM can hold in a single call — everything it can "see" at once, including instructions, conversation history, and any documents provided.
✓Document
A document is an editable, markdown-based file, Masterforce's core format for writing, plans, and knowledge.
✓Fine-tuning
Fine-tuning is additional training on top of an existing model, using your own examples, so it permanently adjusts how the model responds.
✓Guardrails
Guardrails are the rules and checks that constrain what an AI is allowed to do, keeping it inside safe or intended boundaries even when a prompt or a model's own judgment might push past them.
✓Hallucination
A hallucination is when an AI states something confidently that isn't true — a fact, a citation, a piece of data — because it generated plausible-sounding text rather than checked a real source.
✓Harness
A harness is the runtime that gives an AI real tools, real permissions, and real memory instead of just a chat window.
✓Human-in-the-loop
Human-in-the-loop describes an AI system that pauses to ask a real person for a decision at specific points, instead of running fully on its own.
✓Integration
An integration is the specific way one of your apps uses a connection, for example, syncing Google Contacts into a people database.
✓Job
A job is one background execution run for a party member, a single attempt at moving a piece of active work forward.
✓LLM
An LLM (Large Language Model) is the underlying AI model — GPT, Claude, Gemini, and others — that actually generates text, reasoning, and tool calls for an agent or assistant.
✓MCP
MCP, short for Model Context Protocol, is the open protocol that lets an AI call real tools, like reading a file or updating a record, instead of only generating text about doing so.
✓Multi-agent system
A multi-agent system is an AI setup built from several specialized agents working together, instead of one general-purpose agent trying to do everything.
✓Node
A node is an element in the org tree under a workspace, identified by a slug path like co-x3/programs/knowledge, and it is the structural unit permissions and content attach to.
✓OKR
An OKR (Objective and Key Results) is a goal paired with the specific, measurable results that show whether it's actually being achieved.
✓Orchestrator
The orchestrator is the org-level coordinator that runs on a periodic heartbeat, noticing drift and nudging stalled work forward.
✓Party
The party is the combined view of the people and agents working together on the same node.
✓Party member
A party member is a standing actor in the workspace, a person or an agent, with its own identity, permissions, and ability to carry active work over time.
✓RAG
RAG (Retrieval-Augmented Generation) is a technique where an AI looks up relevant documents from a knowledge base and includes them in its prompt, instead of relying only on what it learned during training.
✓Skill
A skill is knowledge an AI reads on demand, a spec, template, or playbook it consults mid-task, rather than a standing tool it executes.
✓System prompt
A system prompt is the standing instructions an AI is given before a conversation starts — who it is, what it can do, and how it should behave — as opposed to whatever the user types.
✓Task
A task is a single unit of assignable work, owned by exactly one party member at a time.
✓Token
A token is the small chunk of text an LLM actually processes — roughly a word or part of a word — and it's the unit both context windows and AI usage costs are measured in.
✓Workspace
A workspace is the top-level container for one organization in Masterforce, holding its own structure, people, and settings.