TL;DR
Thorsten Meyer AI reported that a May 2026 audit found a 474-site WordPress network was concentrating most output on a small group of sites. The operator says fixes were made across content supply, placement logic and scheduling, but the results will depend on coming weeks of data.
Thorsten Meyer AI reported that a May 2026 audit of its 474-site WordPress publishing network found a major distribution failure: 80% of posts were landing on 38 sites, while 249 sites received no posts during the 28-day review period.
The company said the problem was hidden by healthy aggregate output numbers. According to the engineering note, each individual content placement appeared valid, but the network as a whole had become heavily concentrated on a small group of sites.
The audit found that the top 38 sites, about 8% of the catalog, received 80% of all posts. Four technology sites were each receiving more than 200 articles per week, while 53% of the catalog went dark during the same period.
Thorsten Meyer AI attributed the imbalance to two separate causes. Its DojoClawAI content engine kept selecting the same broad technology sites after relevance matching, while its Stenvrik news-intelligence layer supplied far more tech and AI content than the site catalog could evenly absorb.
Why It Matters
The finding matters because it shows how automated publishing systems can appear productive while weakening their own network. Total output can rise even as many properties receive no new material and a few sites take on excess posting load.
For publishers using automated syndication, the case points to a measurement gap. Throughput alone did not show whether the catalog was being used evenly, whether underused categories had enough source material, or whether placement rules were reinforcing a narrow set of favored destinations.
The company said the fix required changes in both supply and placement, rather than a single adjustment to the matching system. That distinction matters for operators who separate content discovery from article placement, because problems can span both sides even when each system appears to be working on its own.
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Background
The network described by Thorsten Meyer AI uses two cooperating systems. Stenvrik ingests feeds, scores stories and tags them by geography and topic. DojoClawAI rewrites stories in each site’s voice and distributes them across the WordPress catalog.
The audit found a mismatch between incoming content and site demand. About 53% of supplied content was tech or AI-related, while only about 13% of the site catalog was in those categories. The company said that left many non-tech sites without enough suitable material.
Thorsten Meyer AI said it changed placement rules by adding a per-site weekly cap, ordering candidates by network-wide recency and building a floor that pushes long-idle eligible sites into the selection pool. It also said it audited feeds, removed broken RSS sources, added verified feeds in underused categories and raised scheduler limits after adding caps.
“80% of output on 8% of sites”
— Thorsten Meyer AI engineering note
“A site that never entered the pool could never get a turn”
— Thorsten Meyer AI engineering note
“Supply and placement are genuinely separate concerns”
— Thorsten Meyer AI engineering note
“The proof is in the next weeks of data”
— Thorsten Meyer AI engineering note
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What Remains Unclear
It is not yet clear how quickly the 249 dormant sites will begin receiving posts, how evenly the new rules will distribute content across all categories, or whether the higher daily ceiling will create new concentration patterns. The company also said the changes do not retroactively correct the 28-day period in which many sites received no posts.
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What’s Next
The next test is the network’s post-audit data. Thorsten Meyer AI said the main measure will be whether dormant sites shrink as a share of the catalog, whether overloaded sites fall back under the cap, and whether the added feed sources support categories that were previously starved.
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Key Questions
What happened in the audit?
A 28-day audit found that a 474-site WordPress publishing network had concentrated 80% of posts on 38 sites, while 249 sites received no posts.
Was this caused by one bug?
Thorsten Meyer AI says no. The company identified two causes: placement logic that favored the same broad tech sites and a content supply mix that was too heavily weighted toward tech and AI.
What did the company change?
It said it added weekly site caps, network-wide recency ordering, idle-site selection rules, more verified feeds for underused categories and higher scheduler limits after adding load controls.
Is the problem fixed now?
The company says the system behavior has changed, but the result is still developing. The next weeks of publishing data will show whether the network becomes more evenly used.
Why does this matter beyond this one network?
The case shows that automated publishing systems can meet output targets while failing at distribution. Operators may need to measure where content lands, not only how much is produced.
Source: Thorsten Meyer AI
