See AI Agents in Action
From Trigger to Resolution, Autonomously

// Manual lead processing workflow:
// 1. Check inbox for new form submissions
// 2. Copy lead info into spreadsheet
// 3. Open CRM, search for existing contact
// 4. Look up company on LinkedIn manually
// 5. Score lead based on gut feeling
// 6. Draft response email from scratch
// 7. Update spreadsheet with status
// 8. Notify sales team via Slack

// Time per lead: ~25 minutes
// Error rate: ~15% (missed fields, typos)
// Availability: Business hours only
// Handles 10 leads/day before burnout

name: lead_qualification_agent
description: >
  Qualifies and routes inbound leads
  through enrichment, scoring, and response

triggers:
  - type: webhook
    source: web_form
    event: new_submission

capabilities:
  - lead_qualifier
  - data_extractor
  - email_responder
  - workflow_orchestrator

guardrails:
  max_actions_per_run: 10
  require_approval:
    - email_responder.send
    - workflow_orchestrator.execute
  escalate_when:
    - score < 30 AND company_size > 500
    - sentiment: negative

schedule:
  monitoring: continuous
  reporting: daily_digest

class AgentRuntime {
  async run(trigger: Trigger) {
    // 1. OBSERVE — gather context
    const context = await this.observe({
      trigger,
      sources: this.config.dataSources,
      enrichment: this.config.enrichment,
    });

    // 2. DECIDE — evaluate against rules
    const decision = await this.decide({
      context,
      scoringModel: this.config.scoring,
      guardrails: this.config.guardrails,
    });

    // 3. ACT — execute chosen actions
    if (decision.requiresApproval) {
      await this.requestApproval(decision);
      return; // pause until human approves
    }

    const results = await this.act({
      actions: decision.actions,
      context,
      retryPolicy: this.config.retries,
    });

    // 4. LEARN — log for improvement
    await this.learn({
      trigger, decision, results,
      feedback: await this.collectFeedback(),
    });
  }
}