Growth idea action plan
llms.txt plus MCP content corpus for AI discovery
Package your content so both crawlers and AI assistants can query it directly, using llms.txt, sitemap-grade hygiene, and a machine-readable endpoint where it makes sense.
Why this can grow a startup
Content now has two audiences: humans in browsers and agents inside other tools. A clean AI-readable corpus reduces retrieval friction, gives answer engines a stable path to the canonical material, and lets the same body of work travel into workflows where people actually ask questions. This is especially useful for technical, trust-heavy, or reference-heavy products that want to be cited rather than merely visited.
Key metric to watch
500+ blogs served with AI query response times under 50ms and MCP endpoints live in under 5 minutes
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. For acquisition, I would keep the first test narrow enough that a clear yes or no is possible. Broad reach is not useful if the signal is muddy. 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 llms.txt plus mcp content corpus for ai discovery 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 customer blog a sitemap, llms.txt, and live MCP endpoint in under five minutes. The result is 500+ customer blogs on one deployment, sub-50ms AI query response times, and customer content that can be queried directly inside assistants.
Source: Vercel case study (vercel.com)
GrowthDex source hub: Vercel case study
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.
- Onboarding discovery bundle for AI-native sites same source · 2 shared channels
- Critical-mass UGC SEO release 3 shared channels · 2 shared stages
- Root-domain consolidation after UGC signal 3 shared channels · 2 shared stages
- Checkout-first Core Web Vitals rehab same source · 1 shared channel
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Reading path: SEO
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Reading path: AI products
Use these essays to understand the broader lane this tactic belongs to.
- The launch keeps going after launch day 2026-05-24
- The next useful surface usually beats the homepage 2026-05-24
Read GrowthDex essays
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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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