Multi-Agent Layer and Design

• Multi-Agent Design
• Recommended use

Multi-Agent Design

Use role-based agents instead of one omnipotent agent.

Orchestration Patterns

●       Manager-worker — a coordinator agent dispatches to specialist workers and merges results.

●       Task graph / stateful graph orchestration — the workflow is modeled as a directed (often cyclic) graph with conditional branching, persistent checkpoints, and interruptible human-in-the-loop points, rather than a fixed linear chain.

●       Shared memory store — agents coordinate through a common memory layer instead of direct message passing.

  Open problem: Byzantine fault tolerance in adversarial multi-agent settings remains an unresolved research area — don't assume agent-reported results are trustworthy without independent verification in high-stakes settings.

Model Routing / Cost Optimization

Use the cheapest model that can reliably complete the task.

Principle: Intelligence should scale with difficulty. Many current model families additionally expose configurable reasoning effort as a routing dimension in its own right — treat effort level as a tunable dimension alongside model size.

Reflection / Critique Loops

Use secondary reasoning for high-stakes decisions.

Trigger Conditions

●       Low confidence

●       High risk

●       Contradictory evidence

●       Large transaction

●       Compliance-sensitive request

Reflection Flow

Human-in-the-Loop Design

Humans should be inserted intelligently.

Confidence Handoff: Escalate when confidence < 0.85–0.90

 

Recommended use

 What to Use When