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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