Jev runs a 586-page internal link audit in 45 seconds for $0.21
The author used Jev for an internal linking audit: it processed 586 pages in 45.1 seconds, placed 584 links and declined to force links onto 139 pages, for a total cost of $0.21, while Claude Opus 5 got through only 21 pages and spent $1.43.
We’ve been massively overpaying for AI marketing work that doesn’t need frontier intelligence. I ran Jev across 586 pages of a site for an internal linking audit. In 45.1 seconds, it processed every page, rebuilt the internal link map, placed 584 links, and refused to force links onto 139 pages where nothing actually fit. Total cost: $0.21. I gave Claude Opus 5 the same 586 pages, same queue, same rubric, same clock. It got through 21 pages and spent $1.43 before the run stopped. That works out to roughly 190x more cost per page. A full Opus pass at that rate would have cost around $43. The interesting part isn’t that Jev is “better at SEO.” Internal linking is simply the kind of marketing task where using a frontier model can be overkill. The job is basically thousands of small classification decisions: should page A link to page B, and does relevant anchor text already exist in the copy? We’ve spent the last few years asking which AI model is smartest. For marketing teams, the more useful question might be: what is the cheapest level of intelligence that can reliably make this specific decision? As AI gets embedded deeper into marketing workflows, model routing will matter as much as model capability. The best AI stack won’t run everything through the smartest model. It’ll know when intelligence is actually worth paying for.
This post quotes another post: x.com/wwardenn/status/2102842288619814925