Agent-ready vs SEO-ready: what changes when your customer is a bot

If you have done SEO, you already understand half of agent-readiness. The instincts transfer: be discoverable, be well-structured, be fast, be clear. But agents are a different kind of reader, and a few things genuinely change when your "visitor" is software acting for someone else.

A quick recap of what SEO optimises for

Classic SEO makes your pages easy for search engines to crawl, understand and rank: clean URLs, sitemaps, fast loads, good headings, structured data, helpful content. The goal is a human clicking a result.

What carries straight over

Most of it. Sitemaps, robots rules, fast responses, clear headings and structured data all help agents too. A well-built SEO site is already ahead. If your technical SEO is solid, you have a head start — not a blank slate.

What is genuinely new

The difference is that an agent does not want to land on a page and look at it. It wants to read content and take an action on someone’s behalf. That introduces signals SEO never needed:

llms.txt — a curated guide to your best resources, for agents specifically.
Markdown on request — returning clean content when an agent asks, instead of a page it has to strip down.
Discovery files — /.well-known/api-catalog, openapi.json, an MCP server card — so an agent can find and use your operations without guessing.
A clear access policy — stating, in machine-readable form, what agents may train on, read and do.

SEO is about being found and read by a person. Agent-readiness adds being understood and acted on by software.

Side by side

SEO checklist	Agent-readiness checklist
Crawlable, fast pages	Same — plus clean Markdown on request
XML sitemap	Same
Structured data for rich results	`llms.txt` + `.well-known` discovery
Internal linking for authority	Described APIs / tools for actions
Content that answers a query	Content an agent can extract and trust

Where to start if you have already "done SEO"

Do not rip anything up. Layer the new signals on top: add an llms.txt, serve Markdown on your most important pages, and publish the discovery files for anything machine-usable you already have. Then measure.