Public Evidence Lab / Dossier O-2881
Collected sample: 7 independent content items across 2 source families. Known publication dates: 2026-08-15 — 2026-10-23.
First seen 2026-08-15 · Last updated 2026-11-13 · Recalculated daily
These observations describe collected samples, not platform-wide prevalence; they cannot establish whether a problem is widespread or accelerating. Collection scope changed on 09-16 and 09-27; monthly counts must not be read as trends.
Post title: I got codex do some digging on logs regarding the usage drain. here is what it found.
I have pro (x5) subscription, for the kind of task…
The public layer keeps only a minimal excerpt. Open the source for full context.
Post title: Tell HN: I Hate Codex with Passion
I have a $20 OpenAI subscription and a $20 Claude subscription.
Post title: AI yapp is here🥲
But this month I shifted to codex with chatgpt plu…
The public layer keeps only a minimal excerpt. Open the source for full context.
Post title: I just confirmed the real culprit draining your usage limit: Its Sol generated 30 hidden, expensive child and grandchild agents in a matter of minutes!
It is a feature OpenAI introduced in March called …
The public layer keeps only a minimal excerpt. Open the source for full context.
Post title: How it started vs how it’s going
“We found several bugs draining your usage and we’…
The public layer keeps only a minimal excerpt. Open the source for full context.
Post title: fr i highly think codex models have become dumber in this update
also fsr the tokens are being spent quicker for co…
The public layer keeps only a minimal excerpt. Open the source for full context.
Post title: OpenCode + DeepSeek Flash: Is 268.9M cumulative tokens and 309M cache reads normal?
I'm trying to understand whether my token usage wi…
The public layer keeps only a minimal excerpt. Open the source for full context.
What this evidence does not show yet
This dossier already carries first-hand payment evidence. What it still cannot tell you: market size, how reachable these people are, or what it costs to acquire them.
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Scoring summary
Evidence confidence = strength × evidence volume × source diversity × payment × competition × trend × 10. Counts use independent content items; only first-hand pain, current spend, explicit willingness to pay and concrete feature requests affect the score. Repeated posts by one author are discounted. Scoring and status changes follow deterministic rules.
“Payment-backed” means first-hand payment evidence exists in the record. It does not mean the business is worth building. “Fading” is a recency tag shown alongside any evidence level, not a lower level. Read the full methodology.