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Publish an llms.txt and agent discovery file
Claude, Perplexity, and Copilot probed for /llms.txt, /.well-known/agent.json, and /.well-known/ai-plugin.json and got 404s. Without these files, generative engines can't reliably describe what you do — so they skip you, or worse, describe you incorrectly. Publishing them is table-stakes for AI search indexability.
Agents can't validate a recommendation against your product
When AI agents research software on a buyer's behalf, they often try to sign up and poke the API to confirm fit before recommending. Your product has no headless signup or API-based registration, so agents bounce and default to a competitor they could actually use. A programmatic signup path (e.g. POST /api/v1/register) keeps you in the answer set.
Pricing isn't surfaced in AI answers
When buyers asked "how much does it cost?", Claude, ChatGPT, and Perplexity all failed to quote your pricing. Models that rely on knowledge-base recall miss pricing entirely and defer to competitors with crawlable price pages. A clear pricing section linked from your docs landing page closes this gap across every engine.
Low presence in LLM training corpora
On open prompts like "best API for X", your product ranked #5 or not at all. Models with smaller context default to competitors that appear more often in the training corpus. Publishing technical posts, earning mentions in API comparison roundups, and syndicating to dev platforms lifts your rank in zero-shot answers.
Publish an llms.txt and agent discovery file
Claude, Perplexity, and Copilot probed for /llms.txt, /.well-known/agent.json, and /.well-known/ai-plugin.json and got 404s. Without these files, generative engines can't reliably describe what you do — so they skip you, or worse, describe you incorrectly. Publishing them is table-stakes for AI search indexability.
Agents can't validate a recommendation against your product
When AI agents research software on a buyer's behalf, they often try to sign up and poke the API to confirm fit before recommending. Your product has no headless signup or API-based registration, so agents bounce and default to a competitor they could actually use. A programmatic signup path (e.g. POST /api/v1/register) keeps you in the answer set.
Pricing isn't surfaced in AI answers
When buyers asked "how much does it cost?", Claude, ChatGPT, and Perplexity all failed to quote your pricing. Models that rely on knowledge-base recall miss pricing entirely and defer to competitors with crawlable price pages. A clear pricing section linked from your docs landing page closes this gap across every engine.
Low presence in LLM training corpora
On open prompts like "best API for X", your product ranked #5 or not at all. Models with smaller context default to competitors that appear more often in the training corpus. Publishing technical posts, earning mentions in API comparison roundups, and syndicating to dev platforms lifts your rank in zero-shot answers.
