1. 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
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
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
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
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
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