AI automation is hands-off execution within clear bounds — ingest, classify, draft, notify — while humans keep publish and policy.
In my daily workflow
- I automate data movement and first drafts; I review anything public-facing.
- Schedules trigger revalidation, embedding refresh, and health checks.
- Agents draft admin descriptions or SEO snippets; I edit before publish.
- I monitor automation failure queues daily.
How it makes me work smarter
Automation frees time for architecture and content quality. The portfolio's value is still human curation — automation handles sync, indexing, and repetitive codegen paths that skills already define.
My setup
- GitHub Actions for CI and keep-alive
- Server actions on publish hooks
- n8n for external webhooks
- Cursor agents for batch refactors with human review
On this portfolio
Publishing triggers cache revalidation and sitemap updates automatically. SEO and optimization skills help generate metadata drafts; knowledge status remains manual control before the world sees changes.
