Onboarding discovery bundle for AI-native sites
Provision every new content surface with its crawl files from day one: sitemap, llms.txt, robots.txt, and a machine-readable install or query endpoint.
Why this can grow a startup
The discovery layer works best when it ships with the content, not as a cleanup project months later. Bundling those files into onboarding makes machine readability default behavior and keeps new surfaces from becoming invisible to agents. It turns operational discipline into compound discoverability.
Company example
Waldium gives each new customer blog a sitemap, LLMs.txt, robots.txt, an MCP install page, and a live MCP endpoint in under five minutes, while serving 500+ blogs from one deployment with AI query latency under 50ms.
Source and metric
Source: Vercel Blog
Discovery bundle live in under 5 minutes; 500+ blogs on one deployment with AI query latency under 50ms
Source discovered: May 24, 2026
When to use it
Use this when AI Search, SEO, Website is relevant to ai-discovery, content-ops, platform and you can run a bounded test with a medium budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
Founder checklist
- Read Vercel Blog and identify what is directly supported.
- Choose one channel context: AI Search, SEO, Website.
- Define the test around Discovery bundle live in under 5 minutes; 500+ blogs on one deployment with AI query latency under 50ms.
- Set an owner, evidence window, and stop condition before launch.
Explore the context
Apply this with an operator
Turn isolated search tactics into a crawlable visibility system tied to demand and proof.