AI Agents
AI Agents are configurable automations you build in FunnelStory: pull data from your workspace or connections, call an LLM where you need judgment or language, then take action — Slack, email, tasks, CRM updates, datasets, and more. Reach for one whenever a built-in feature's fixed rules aren't enough and you need branching logic, a query across your workspace, or several actions chained from one run.
The shape: trigger, step graph, action
Every agent is a directed graph of steps, wired together with a trigger that decides when a new run starts — on a schedule, when an event or signal occurs, when a query returns matching rows, or only when someone starts it manually or from chat. Steps call functions (CALL) or run an LLM for multi-step reasoning (AGENT), passing results forward through variables. See AI Agents overview for the full mental model, including the operation types and how runs and events work.
Two ways to build
You author an agent either on a Canvas — set the trigger, add blocks, configure each step in a side panel — or through Vibe Coding, describing what you want to an AI assistant connected over MCP, which reads FunnelStory's own flow authoring guide and builds or edits the agent for you. See Getting started and Vibe coding.
AI Agents vs. Outcome-Based Agents
Not every agent in FunnelStory is one you build. Outcome-Based Agents are pre-built by FunnelStory around one specific job, with nothing to author — the Needle Mover investigation agent is the first example. AI Agents are the general-purpose counterpart: the graphs are yours to design, for whatever your team needs. See Outcome-Based Agents for the full comparison.
Related
- AI Agents overview — the full mental model and reference set
- Outcome-Based Agents — pre-built agents for a single job, vs. the graphs you configure here
- Renari — the in-product AI copilot, a different kind of AI surface entirely
- MCP Server — how external AI assistants (and Vibe Coding) connect
- Customer Intelligence Graph — the data every agent reasons against