The Core Difference
- Agentic Functions are stateless — each call is independent
- Agents are stateful — they maintain context across calls
Choosing Between Them
- Single jump vs journey: Use an agentic function when the job is “Given X, return Y” in one call; use an agent when you naturally say “First do A, then based on that do B, then refine with C…”.
- Isolation vs shared context: Agentic calls are independent and great for extraction, transformation, and batch jobs; agents keep conversation and REPL history, so later steps can build on earlier reasoning.
- Pipeline step vs orchestrator: Agentic functions plug in as pure steps inside existing pipelines; agents own longer-lived workflows, conversations, and tool orchestration where they steer the process.
- Cost profile: Agentic functions scale to many cheap calls with predictable behavior; agents are heavier but better suited for deeper, higher-value tasks where the extra context and adaptability pay off.
Agentic Functions
Stateless AI operations. Each call has a fresh REPL, and is independent with no memory of previous calls. Use these for:- Extraction, transformation, loading data into structures
- Batch processing independent items
- Single-shot generation or classification
- Pure functions with AI logic
Agents
Stateful AI workflows. Maintains conversation and REPL history and builds on previous interactions. Use these for:- Multi-step workflows where the steps have serial dependencies
- Conversational interfaces
- Iterative refinement
- Complex orchestration
Next Steps
Agentic Functions
Documentation
Agents
Documentation
Advanced
UnMCP
Examples
Working examples