AI & Agents · 11 min · Sep 13, 2025

Agentic Web (AI Agents)

Prepare your site for autonomous agents with safe actions and guardrails.

Agentic Web (AI Agents)

1. What Agents Actually Do

What Agents Actually Do

Agents read pages, extract info, click buttons, fill forms, and call APIs. They pursue goals through plan-act-observe loops and need clear affordances to stay on track.

Key takeaways:
  • Browse, click, type
  • Call tools/APIs
  • Pursue goals via loops

2. Make Your Site Agent-Ready

Make Your Site Agent-Ready

Use ARIA roles and schema markup. Provide stable `data-*` selectors and publish **action endpoints** for critical tasks with predictable JSON responses.

Key takeaways:
  • Semantic markup
  • Stable data-ids
  • Machine-readable actions

3. Action Schemas & Validation

Action Schemas & Validation

Define actions with schemas, inputs, and pre/post conditions. Idempotent endpoints and clear error classes prevent loops and retries from causing damage.

Key takeaways:
  • JSON schemas
  • Pre/post conditions
  • Idempotency

4. Safety, Auth & Rate Limits

Safety, Auth & Rate Limits

Give agents narrowly scoped tokens and log every action. Apply quotas and anomaly detection to block runaway loops or scraping.

Key takeaways:
  • Scopes & consent
  • Audit trails
  • Quotas

5. Observability & Guardrails

Observability & Guardrails

Track success rate, average steps, and token cost. Use canary tasks with known answers to detect hallucinations early.

Key takeaways:
  • Task success rate
  • Step count & cost
  • Hallucination canaries

6. Where Agents Pay Off

Where Agents Pay Off

Start with internal workflows (support triage, knowledge lookups, data entry) where risk is low and ROI is high. Then graduate to user-facing assistants with strong consent UX.

Key takeaways:
  • Support workflows
  • Research & summarization
  • Back-office automations