Update README.md

Reviewed-on: #8

README.md

@@ -1,16 +1,17 @@
-# kongruity: Signal from noise
+# kongruity: Signal from noise - 2025-2026 @sjDev - LICENSE: MIT
 
-“...All those moments will be lost in time, like tears in rain.”
+![kongruity demo image.](kongruity_demo_image.png)
 
-kongruity pulls in unstructured artifacts of the creative-engineering process -- to-dos, action items, agile tickets, Jira thread comments, Slack thread comments, retrospective notes -- and synthesizes them into semantically coherent, prioritized clusters that can be incorporated into implementation planning.
+kongruity pulls in unstructured artifacts of the creative-engineering process, capturing "AHA!" moments scattered across an engineering team's disparate tools: action items or backlog in Atlassian/Jira, user story comments, Slack discussions, retrospective feedback.
 
-In kongruity, the artifacts become "sticky notes." A board full of them looks chaotic.
 
-With a click, they are semantically evaluated, grouped into thematic clusters with descriptive headers, rankable and exportable to project planning and execution tools.
+It stores and synthesizes these into semantically coherent, prioritized clusters that can be incorporated into implementation planning.
 
-## Voyage AI voyage-3.5
 
-![Embedding model benchmarking.](Voyage.jpg)
+In kongruity, artifacts become "sticky notes." A board full looks chaotic. With a click, a RAG-pipeline levearges Models trained to semantically evaluate, group, cluster and add descriptive cluster headers.  
+
+
+These are rankable, editable and exportable to sprint project planning tools. 
 
 ## Clustering and evaluation: methodology
 
@@ -26,6 +27,10 @@ This yields an empirical groundedness evaluation. One model proposes the groupin
 
 Note that: before scoring, structural validation confirms that each note landed in exactly one cluster, that no cluster is empty, and that no hallucinated note IDs appear. A malformed response to the validation completely fails, rather than quietly returning a partial board.
 
+## Voyage AI voyage-3.5: best-in-class embedding
+
+![Embedding model benchmarking.](Voyage.jpg)
+
 ## Reading the cohesion score
 
 Average silhouette width is a widely-used measure of clustering quality. Higher values indicate:

agentic-orchestration.md

@@ -2,13 +2,11 @@
 
 You should assume the tole of  Lead Orchestrator Agent for a complex, long-horizon software development project.
 
-# The first rule. Hereinfter, the "King's Rule".
+# The first, inviolable rule.
 
-This is the King’s Rule: minimize token usage, but do not sacrifice quality.
+The Inviolable Rule: minimize token usage, but do not sacrifice quality.
 
-Strive for strict compliance to the King’s Rule.  
+Here is a non-exhaustive list of suggested strategies to achieve this:
-
-Here is a non-exhaustive list of suggested strategies pertaining to the King’s Rule.
 
 ### Sub-agents