Growth idea action plan
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.
Key metric to watch
Discovery bundle live in under 5 minutes; 500+ blogs on one deployment with AI query latency under 50ms
Ian's take
From scaling consumer platforms across MENA and Southeast Asia, my default is to distrust growth work that only looks good in a slide. For SEO and AI search, I care less about clever keyword tricks and more about clarity. A buyer, crawler, or answer engine should quickly understand who this is for, why it works, what proof backs it, and what page deserves to be cited. I would run it small enough to learn quickly, then only scale the parts that real users repeat, save, reply to, or buy from. For this tactic, I would watch one clear growth signal before putting more time or budget behind it.
Action plan
- Define one narrow startup segment where onboarding discovery bundle for ai-native sites can create a measurable lift.
- Turn the tactic into one offer, page, campaign, or workflow for the AI Search and SEO channel.
- Use the evidence from vercel.com to set the first version of the message, format, and audience.
- Launch a small test for 7 to 14 days with one success metric: one measurable growth signal.
- Review the result, keep the winning message, remove weak variants, and turn the learning into a repeatable growth playbook.
Source-backed 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: Vercel Blog (vercel.com)
GrowthDex source hub: Vercel Blog
Last checked: May 24, 2026
Adjacent tactics in the same lane
If this page is close to your problem, these tactic pages usually belong in the same working set.
- llms.txt plus MCP content corpus for AI discovery same source · 2 shared channels
- AI-agent auto-detected markdown fallback 2 shared channels · 2 shared stages
- Content-negotiated markdown on canonical URLs 3 shared channels · 1 shared stage
- sitemap.md semantic discovery map 3 shared channels · 1 shared stage
Related GrowthDex essays
- The machine reader is part of the audience now SEO, AI discovery, content systems
Read GrowthDex essays
The Blog turns real growth tactics into plain-English case studies by niche, channel, and buying situation.
Why this is worth your time
GrowthDex starts with tactics that founders, marketers, and product teams have actually tried. Each essay turns the evidence into a practical move you can test without pretending one case study is a guarantee.
Ian Goh has helped grow consumer platforms across Southeast Asia, India, and MENA. His work includes scaling Tiki to 100M+ users, doubling BIGO's MENA revenue in 7 months, and increasing OYO's direct booking share across 6 Southeast Asian markets.
- Helped scale Tiki to 100M+ users.
- Doubled BIGO's MENA revenue in 7 months.
- Raised OYO's direct booking share by 50% across 6 Southeast Asian markets.
Want help turning this into a growth system?
If you want someone to pressure-test this against your real market, Ian works with founders on growth, market entry, and operator-led distribution.
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