Content Scoring — Week of 2026-05-13
Pieces Scored
| Piece | Score | Top | Weak |
|---|---|---|---|
| LinkedIn — AI use case we trust least | 8.1 | Voice authenticity / Value density | Shareability |
| Long-form outline — Production AI in Indian real estate | 7.7 | Specificity / Platform fit | Emotional resonance |
| Long-form — Production AI in Indian real estate | 8.4 | Specificity | Emotional resonance |
| LinkedIn — Production AI pull quote | 8.1 | Value density | Shareability |
| LinkedIn — AI use case categories | 8.1 | Value density | Call-to-action |
| LinkedIn — AI agent enterprise day | 7.8 | Voice authenticity | Call-to-action |
Average
8.0/10 — down -0.2 vs 2026-05-06 average of 8.2/10.
Learnings
- Control-layer content is consistently credible. Named systems, audit trails, human owners, and source-of-truth language keep the practitioner signal strong.
- The content is now at risk of thematic sameness. Multiple pieces repeat the same governance/control-layer thesis; quality is high, but novelty and share triggers soften.
- CTA/shareability is the current bottleneck. Questions invite practitioner replies, but there are few taggable frameworks, checklists, or debate hooks that make readers pull others in.
Next Hypotheses
- Open one post with a concrete operating number or visible artifact: a checklist, scorecard, readiness ladder, or “4-question gate” to lift stop-scrolling/shareability.
- Add one personal/practitioner micro-story per week — a messy system disagreement, ownership debate, or audit-trail moment — to lift emotional resonance without inventing claims.
- Vary the thesis: rotate from “control layer” to “where AI creates operating leverage,” “where demos lie,” and “what teams should kill early” to prevent audience fatigue.