Post
CommunityJev Guides & Articles
JEV is a revolution for SEO
A French SEO thread arguing Jev moves the bottleneck from writing to deciding: which page gets a link, which keyword deserves its own URL, and what content to keep.
- Format
- Post
- Reading time
- 2 min
- Published by
- Community
- Author
- Paul Vengeons
- Last verified
- Sep 2026
Works forJev for Classification
Used inJev for Sales & Marketing
Highlights
- Argues drafting is no longer the bottleneck; decisions are.
- Lists decisions such as link targets, keyword URLs, and content to keep.
- Written in French for an SEO audience.
Watch out
No code, measurements, or before-and-after results.
Questions about this entry
Short answers drawn from the linked project or page.
Not from the thread. Those figures come from a test cited in a linked guide, and the post itself has no code, no dataset, and no before-and-after ranking data. The 255-target cap he recommends for internal linking is a preselection limit, not something he measured.
His step 4 is to calibrate a threshold on cases a human has already reviewed: above it you automate, below it a person looks. Step 5 keeps human confirmation for publishing, merging, or deleting. He also suggests batching independent checks such as intent, cannibalization, sources, and internal links into one pass.
Nothing in the model, which is why his own framing keeps a human sign-off on irreversible actions and treats the confidence number as a routing signal rather than a permission. If you automate above a threshold, you are accepting that a wrong high-confidence delete can still happen.
Both, openly. The thread is written in French for an SEO audience and closes by asking for follows, likes, and the word jev in exchange for a guide available in French and English. The 586-page figure is the author's own test as described in that guide; nothing here is an independent evaluation.
Paul Vengeons, a French SEO who calls himself the number one French SEO and runs a business growing revenue through Google and AI, with the guide available in French and English. The thread is SEO operator advice and a funnel for that guide, not a model evaluation.
Four: which page should receive a link, which keyword deserves its own URL, which content to keep, update or merge, and which draft needs human review. His argument is that drafting is no longer the constraint; these post-drafting decisions are, and they are the ones a decision model can compress.
He generalizes it beyond linking: keyword triage, content audits, prospecting, and routing between models all reuse the same five-step pattern of turning decisions into typed questions, grouping independent checks, calibrating a threshold, and keeping a human on irreversible actions. Only the linking test is shown working.
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