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How Truth
Gets Made.
We aggregate public discussion about consumer products and synthesize it into a single, sourced review. The methodology is fully open — you can audit any verdict back to the exact comments it came from.
The Pipeline.
Every GYIBB review is produced end-to-end by specialized AI agents — no human editorial involvement, no sponsored placement, no exceptions.
Monitors product launches, Reddit threads, HackerNews frontpage, and ProductHunt to surface products people are actively discussing. Feeds the queue that the rest of the pipeline processes.
Harvests raw user discussion from 8 platforms simultaneously: Reddit, Trustpilot, YouTube (comments + transcripts), HackerNews, Lemmy, Stack Exchange, ProductHunt, and the brand's own site. Runs on a residential IP to reach Trustpilot and Reddit without datacenter blocks.
Feeds all harvested data into the four-layer reality model and runs the LLM synthesis with extended thinking enabled. Produces a structured review: rating, sentiment distribution, pros/cons, tension points, and the full four-layer narrative. The rating is derived mathematically from sentiment — not generated by the LLM directly.
Validates the review against GYIBB's data floor (minimum voice count, platform diversity, schema integrity). Attaches affiliate links, generates SEO metadata, and writes the review file to the site. Emits a page.published event that kicks off the downstream agents.
An independent agent that receives Quinn's draft and the raw source data — with no knowledge that Quinn produced it. Its only job: find claims in the review that aren't supported by the source evidence. Reviews that fail are rejected and re-run. Ubik also surfaces contradictions between layers (e.g. brand claims 30h battery, median user reports 14h).
Submits new URLs to Google Search Console, monitors CTR and impressions, and flags reviews that need optimization.
Posts 3 content angles (stat, tension, verdict) to X and Bluesky. Monitors @mentions and replies with data-backed answers.
Monitors journalist query platforms (HARO, SourceBottle) and pitches data-backed responses to earn editorial backlinks.
Watches every event on the pipeline bus (Redis Streams). Tracks cycle health, detects stuck or failed runs, maintains the admin dashboard, and exposes the /api/v1/cycles API that powers internal monitoring.
All agents communicate over a Redis Streams event bus. Each event is durably stored — no message is lost during restarts or deploys.
Four-Layer Reality.
Every review is built from up to four independent layers. We flag where they agree, where they contradict, and where data is thin.
Comments from actual people describing their experience — the most important layer. Signal, not noise.
Long-form review videos: what independent reviewers tested, measured, and concluded over hours of use.
Aggregate ratings from category-specific review authorities. Cross-checked, not taken at face value.
What the manufacturer claims on their official site. Compared (not trusted) against the other three layers.
The Data Floor.
Truth comes from sample size. We refuse to publish below a minimum — empty catalog beats a confident lie.
- ✓ At least 10 user voices across all platforms combined
- ✓ At least 2 distinct platforms — single-platform reviews are echo chambers
- ✓ A real user-experience prose section ≥ 200 characters
- ✓ Category in our canonical taxonomy
- ✓ Rating not the LLM fallback sentinel (5.5)
Products that fail these checks stay in our queue and are reviewed again later. They never appear on the site as a half-baked verdict.
Confidence Tiers.
Every published review carries a tier label based on the number of unique user voices we collected.
Verdict based on early signals. Check back as more discussion accrues.
Verdict synthesized from substantial user feedback across multiple platforms.
Verdict drawn from a large, diverse pool. Most reliable tier.
What We Don't Do.
- ✗ We do not Use Reddit, YouTube, or any user-generated content to train AI models. Source data flows through inference at synthesis time and is then discarded.
- ✗ We do not Sell, license, or share collected data with third parties.
- ✗ We do not Retain content marked as [deleted] or [removed]; deletions propagate.
- ✗ We do not Derive sensitive characteristics about commenters.
- ✗ We do not Write reviews of products we couldn't gather enough data on. Empty section beats a confident lie.
Affiliate Disclosure.
GYIBB earns commissions from some links (Amazon Associates and select brand programs). The presence of an affiliate link never influences what we say about a product or how we score it — the synthesis is locked before any link is attached. Affiliate links are disclosed inline, sit after the verdict (never before), and only appear if the brand has a public program.
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