About page: refined narrative + avatar fix

About page: three beats from narrative/ source of truth
- Beat 1: four partnership patterns named with descriptions
- Beat 2: Intent Layer (not what machine can produce... the gap)
- Beat 3: 25 years softened (distance grew, hardest to get right)
- HIP Charter description: 15 positions on the map

Blog author: updated description to 'Builder who governs'
CSS: avatar object-fit fix for blog author images

Author: Nikhil Singhal

docs/about.md

@@ -1,6 +1,6 @@
 ---
 title: "About AI Trust Commons"
-description: "Founded by Nikhil Singhal. 25 years of engineering leadership. Building the cross-provider AI governance layer no single vendor will build."
+description: "Founded by Nikhil Singhal. Builder who governs. The Human Intelligence Partnership Charter, the Intent Layer, and 25 years of engineering leadership."
 hide:
   - navigation
 ---
@@ -13,11 +13,11 @@ hide:
 
 **CTO | VP Engineering | AI Practitioner & Governance Strategist**
 
-25 years leading engineering organizations at Microsoft, AT&T, T-Mobile, Expedia Group, and Hitachi Consulting. Building AI-powered products daily with AI as a full development partner.
+I design, architect, and ship production systems across every pattern of the [Human Intelligence Partnership Charter](https://hipcharter.com): the Foundation pattern, where AI is my daily build partner. The Tooling pattern, where the products I ship use AI to build but work without any AI dependency. The Pipeline pattern, where AI enriches data behind the scenes and users never see it. And the Integration pattern, where AI works alongside proprietary APIs and live data at runtime. These are not wrappers. They are architectures designed for two intelligences working together.
 
-I founded AI Trust Commons because the cross-provider governance layer the industry needs is something no single vendor will build. Every vendor solves for their own platform. This project solves for the enterprise that operates across all of them.
+The building taught me something. The hardest problem in AI is not what the machine can produce. It is the structural gap between what the human means and what the machine does. I call it the Intent Layer. That insight became the HIP Charter, AI Trust Commons, and the *From Instinct to Intent*™ series.
 
-The building taught me something: the gap between what humans mean and what AI does is a governance problem. That insight became the [Human Intelligence Partnership Charter](https://hipcharter.com) and the *From Instinct to Intent*™ series.
+25 years at Microsoft, T-Mobile, AT&T, Expedia Group, and Hitachi Consulting watching the distance grow between what leaders intended and what systems actually delivered. The governance layer between intent and execution was always the hardest part to get right. The same pattern is playing out in AI.
 
 [LinkedIn :material-linkedin:](https://linkedin.com/in/nikhilsinghal){ .md-button }
 [GitHub :material-github:](https://github.com/nikhilsi){ .md-button }
@@ -47,7 +47,7 @@ The core thesis: the bottleneck in AI is no longer the technology. It is humanit
 
 ### The Human Intelligence Partnership Charter
 
-Four patterns of human-AI partnership. Drop "artificial." Start building with intelligence.
+Four partnership patterns. Fifteen positions on the map. Drop "artificial." Start building with intelligence.
 
 [Read the Charter at hipcharter.com](https://hipcharter.com){ .md-button .md-button--primary }
 

docs/blog/.authors.yml

@@ -1,5 +1,5 @@
 authors:
   nikhil:
     name: Nikhil Singhal
-    description: CTO | VP Engineering | AI Practitioner & Governance Strategist. Founder, AI Trust Commons.
+    description: Builder who governs. Founder, AI Trust Commons. Author, Human Intelligence Partnership Charter.
     avatar: https://github.com/nikhilsi.png

docs/stylesheets/extra.css

@@ -61,6 +61,13 @@
   margin: 1rem 0;
 }
 
+/* --- Blog author avatar fix --- */
+.md-post .md-author img,
+.md-post__meta .md-author img {
+  object-fit: cover;
+  object-position: center top;
+}
+
 /* --- Footer --- */
 .md-footer-meta {
   font-size: 0.8rem;