What AI engines actually cite when you ask about LLM gateways
What AI engines actually cite when you ask about LLM gateways We wrote 27 questions the way a developer asks them, sent them to four engines on one day, and counted where the citations pointed. Here is the distribution — including the findings that argue against our own product strategy. What we did The 27 questions are the ones a developer actually types, not what a keyword tool suggests: What…
A study examined how four AI engines responded to 27 developer queries about LLM gateways. The platforms analyzed were Perplexity, OpenRouter, llmgateway.io, and others. The engines returned 613 citations across 27 responses, which narrowed down to 569 distinct URLs and 346 individual domains. Contrary to popular belief, no single source dominates these citations, with the top ten domains accounting for only 18.6% of all citations.
Most of the remaining 81% of citations are spread across 336 domains, indicating that the long tail of citations is significant. The study found that GitHub hosted the most citations, primarily through directories of free APIs and gateway issue threads. Developer-focused tutorials and comparisons were also frequently cited, while competitor marketing pages and privacy policies were directly referenced in responses.
Despite Reddit being widely reported as a source in AI answers, it only contributed 0.5% of citations in this specific study, with most of those citations being setup tutorials for competitor products. The study suggests that for developers seeking answers about LLM gateways, focusing on repositories, issue threads, and long-form tutorial posts may be more beneficial than targeting launch announcements.
It emphasizes that visibility in citations is not guaranteed by a single placement and that the long tail of citations, consisting of 81% of total citations across 336 domains, presents numerous opportunities for visibility.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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