From 2352fb5cffa8b5a935374cb7123e505be328e3b0 Mon Sep 17 00:00:00 2001
From: Jeremiah Lowin <153965+jlowin@users.noreply.github.com>
Date: Wed, 15 May 2024 17:49:26 -0400
Subject: [PATCH] docs

---
 docs/introduction.mdx |  8 ++++----
 docs/mint.json        | 10 +++++-----
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/docs/introduction.mdx b/docs/introduction.mdx
index 9a306c16..8afc93a4 100644
--- a/docs/introduction.mdx
+++ b/docs/introduction.mdx
@@ -2,10 +2,10 @@
 title: Why ControlFlow?
 ---
 
-**ControlFlow is a framework for building agentic LLM workflows.**
-<Tip>
-    An **agentic workflow** is a process that delegates at least some of its work to an LLM agent. An agent is an autonomous entity that is invoked repeatedly to make decisions and perform complex tasks.
-</Tip>
+**ControlFlow is a framework for orchestrating agentic LLM workflows.**
+<Note>
+    An **agentic workflow** is a process that delegates at least some of its work to an LLM agent. An agent is an autonomous entity that is invoked repeatedly to make decisions and perform complex tasks. To learn more, see the [AI glossary](/glossary/agentic-workflow).
+</Note>
 
 LLMs are powerful AI models that can understand and generate human-like text, enabling them to perform a wide range of tasks. However, building applications with LLMs can be challenging due to their complexity, unpredictability, and potential for hallucinating or generating irrelevant outputs.
 
diff --git a/docs/mint.json b/docs/mint.json
index e39df8eb..1e07b678 100644
--- a/docs/mint.json
+++ b/docs/mint.json
@@ -14,12 +14,12 @@
     ],
     "colors": {
         "anchors": {
-            "from": "#0D9373",
-            "to": "#07C983"
+            "from": "#2D6DF6",
+            "to": "#E44BF4"
         },
-        "dark": "#0D9373",
-        "light": "#07C983",
-        "primary": "#0D9373"
+        "dark": "#2D6DF6",
+        "light": "#E44BF4",
+        "primary": "#2D6DF6"
     },
     "favicon": "/favicon.jpeg",
     "footerSocials": {