Agentic System Architecture
First choice: workflow vs autonomous agent
- Workflow (fixed, code-orchestrated steps with LLM calls): predictable, cheap, debuggable. Prefer this when the steps are known.
- Autonomous agent (LLM decides the next action in a loop): flexible, handles open-ended tasks, but less predictable and costlier. Use only when the path genuinely can't be pre-defined.
Orchestration topologies
| Topology | Shape | Fits |
|---|---|---|
| Single agent + tools | One loop, a toolbox | Most tasks; start here |
| Supervisor / sub-agents | Orchestrator delegates to specialists (own context) | Decomposable tasks, context isolation |
| Pipeline / chain | Staged hand-offs | Known multi-stage transforms |
| Network / peer agents | Agents message each other | Rarely needed; high complexity/cost |
Bias to the simplest topology that works; isolate context with sub-agents when a subtask would flood the main context.
Cross-cutting design concerns
- Memory/context: short-term (conversation), long-term (vector/store), and scratch. Compaction/summarization to fit the window; what persists across runs?
- Tool layer: typed tools with clear contracts; least-privilege; validate tool I/O; tools are the agent's blast radius — scope them.
- Control & safety: human-in-the-loop approval for irreversible/outward actions; step/turn budgets; loop/termination conditions; guardrails.
- Determinism & cost: cap iterations, cache, and prefer workflows for the deterministic parts. Observability: trace each step (tool calls, tokens, cost).
- Failure handling: retries, fallbacks, and a defined "give up / escalate" path; don't let agents loop forever.
When to recommend what
- Known steps → workflow. Open-ended + decomposable → supervisor + sub-agents.
- One coherent task → single agent + tools. Reach for multi-agent networks only when simpler shapes demonstrably fail.