Publish llms.txt for agent retrieval
Add a root /llms.txt file that tells AI agents what the site is, which URLs matter, and how to interpret the content.
Why this can grow a startup
AI agents often need compact context before deciding which pages to fetch. A concise Markdown index reduces ambiguity, points models to authoritative URLs, and makes the catalogue easier to cite or summarize without forcing the model to infer the whole product from JavaScript-rendered pages.
Source-backed example
The llms.txt proposal standardizes a root Markdown file with a short project summary and curated file lists for model and agent consumption.
Source details
Source: llmstxt.org
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
Source discovered: May 19, 2026
When to use it
Use this when SEO, AI Search, Content is relevant to pre-launch, 0-100, 100-1K and you can run a bounded test with a free 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.
How to do it
- Choose one target segment and define the exact next action this tactic should prompt.
- Adapt the tactic to SEO and AI Search, using evidence from llmstxt.org as context—not as a promised result.
- Record a baseline for: Qualified search visitors who complete the intended next action. Set a guardrail that would make you pause the test.
- Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
- Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
Compare a stack for your situation
Compare source-backed tactics against your product, stage, budget and channel strengths, then choose one experiment to test.
Explore the context
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Apply this with an operator
Turn isolated search tactics into a crawlable visibility system tied to demand and proof.