AI Agents — Interactive Explainer

↓ Outside world — signals, events, data

Human oversight ▾

Sets the rules — what agents can decide alone, what requires sign-off. Reviews ranked options before the company acts on anything consequential.

↳ A senior executive reviews three response options and selects "accelerate last-mile partnerships."

Sensing agents ▾

Monitor the external world continuously — news feeds, competitor announcements, regulatory changes — and surface what is worth paying attention to.

↳ Flags: "Competitor X announced same-day delivery in three cities — 2 hours ago."

Interpretation agents ▾

Assess what a signal actually means for this business specifically — threat level, affected segments, and how urgently a response is needed.

↳ Threat level: high. Primary exposure: urban grocery. Response window: 48 hours before customer churn risk rises.

Decision agents ▾

Generate response options and rank them by projected impact, cost, and feasibility. Escalate to human oversight if the decision crosses defined risk thresholds.

↳ Option A: last-mile partnerships (+18% reach, 3 weeks). Option B: acquire delivery startup (+40%, 6 months). Option C: monitor only.

Orchestration agents ▾

Coordinate the approved response across systems — notifying teams, updating models, triggering workflows — so a decision becomes an action.

↳ Notifies logistics team, updates pricing model, schedules executive review for 9am tomorrow.

↓ Action + outcome

Learning
loop

Each layer adds intelligence to the one below it. The learning loop feeds outcomes back through the stack — every cycle, the system refines its understanding of what works.