Building an agent-ready website: how to make your site readable for ChatGPT, Perplexity and autonomous agents
<p>A couple of months ago I was on a Zoom call with the founder of <a href="https://follownow.io" rel="noopener noreferrer">FollowNow.io</a>, a social-growth platform we'd just been hired to rebuild. We covered the usual things: Next.js stack, multilingual content, integrating Inte
nexbridge.nl Posted on May 25 • Originally published at nexbridge.nl Building an agent-ready website: how to make your site readable for ChatGPT, Perplexity and autonomous agents # ai # seo # nextjs # webdev A couple of months ago I was on a Zoom call with the founder of FollowNow.io , a social-growth platform we'd just been hired to rebuild. We covered the usual things: Next.js stack, multilingual content, integrating Intercom Fin for support. At the end he added one sentence that ended up reshaping the entire build: "I want our site to be found by ChatGPT and Perplexity, not just Google." That single line is what separates a 2024 website from a 2026 one. If your site is invisible to LLMs and autonomous agents, you're invisible to a fast-growing slice of search traffic, and you're not going to win it back with a few schema tags. Here's the four-layer stack we shipped to make FollowNow.io agent-ready, with concrete file structures and the SDK-level decisions that matter. What "agent-ready" actually means An agent-ready site exposes machine-readable surfaces that LLMs and autonomous agents can consume without having to parse your marketing HTML. Four layers, in priority order: llms.txt at the root → a canonical text document describing what you do, what you don't do, and your public URLs. OpenAPI 3.1 spec at /openapi.json → formal description of the safe, read-only API endpoints agents can call. Agent skills at /.well-known/agent-skills/ → structured "skills" agents can pick up to perform specific tasks. Deep JSON-LD structured data → not just Organization, but Product, Offer, FAQPage and BreadcrumbList everywhere relevant. None of this is hard to ship. The discipline is making sure every layer is generated from a single canonical source so it can't drift from your actual product. Layer 1: llms.txt Like robots.txt but invitational instead of restrictive. Keep it under 10KB so it fits in an agent's context window. The structure we use: # FollowNow > Real growt
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