diff --git a/.github/website/src/index.html.jinja b/.github/website/src/index.html.jinja
index 6dc6117..6d646ed 100644
--- a/.github/website/src/index.html.jinja
+++ b/.github/website/src/index.html.jinja
@@ -61,7 +61,6 @@
           <a href="https://twitter.com/intent/tweet?url=https://hacker-laws.com/#{{ section.id}}?hashtags=example" title="Share on Twitter" target="_blank"><i class="bi bi-twitter"></i></a>
           <a href="https://www.facebook.com/sharer/sharer.php?u=https://hacker-laws.com/&num;{{ section.id }}" title="Share on Facebook" target="_blank"><i class="bi bi-facebook"></i></a>
         </div>
-        <div class="back-to-top"><a href="#top">↑ Back to Top</a></div>
       </section>
       {% endfor %}
 
diff --git a/.github/website/src/script.js b/.github/website/src/script.js
index 0dd5292..67c9fd5 100644
--- a/.github/website/src/script.js
+++ b/.github/website/src/script.js
@@ -15,4 +15,7 @@ $(document).ready(function() {
         // Append to the heading
         $heading.append($anchor);
     });
+
+    //  Bootstrap requires that blockquote elements have the 'blockquote' class.
+    $('blockquote').addClass('blockquote').addClass('.quote');
 });
diff --git a/.github/website/src/styles.css b/.github/website/src/styles.css
index af2a022..1500c6a 100644
--- a/.github/website/src/styles.css
+++ b/.github/website/src/styles.css
@@ -11,17 +11,24 @@ body {
 .container {
   max-width: 800px;
 }
+
 header {
   text-align: center;
   margin-bottom: 2rem;
   padding: 2rem 0;
   border-bottom: 1px solid #e5e5e5;
 }
+
 h1, h2, h3, h4, h5, h6 {
   font-family: 'Libre Baskerville', serif;
   /* Avoid scrolling under the sticky header. */
   scroll-margin-top: 80px;
 }
+
+blockquote {
+  font-style: italic;
+}
+  
 .law-section {
   margin-bottom: 2rem;
   padding: 1.5rem;
diff --git a/README.md b/README.md
index 1d3da5a..f44ea09 100644
--- a/README.md
+++ b/README.md
@@ -4,10 +4,10 @@
 ---
 
 - 📖 Check out my new book [Effective Shell](https://effective-shell) on [Amazon](https://amzn.to/4ho0F91)
-- 🌍 Check out the website [hacker-laws.com](https://hacker-laws.com)
+- 🌍 Try [hacker-laws.com](https://hacker-laws.com)
+- 🧠 Experiment with my new project [Terminal AI](https://github.com/dwmkerr/terminal-ai)
 - ☕️ Like this project? Consider [buying me a coffee with a one-off donation](https://github.com/sponsors/dwmkerr?frequency=one-time)
-- 🧠 Check out my new project [Terminal AI](https://github.com/dwmkerr/terminal-ai)
-- 🎧 Try the podcast [The Changelog - Laws for Hackers to Live By](https://changelog.com/podcast/403)
+- 🎧 Listen to the podcast [The Changelog - Laws for Hackers to Live By](https://changelog.com/podcast/403)
 - 📖 Download the [PDF eBook](https://github.com/dwmkerr/hacker-laws/releases/latest/download/hacker-laws.pd)
 
 ---
@@ -47,6 +47,7 @@
     - [Premature Optimization Effect](#premature-optimization-effect)
     - [Putt's Law](#putts-law)
     - [Reed's Law](#reeds-law)
+    - [The Bitter Lesson](#the-bitter-lesson)
     - [The Ringelmann Effect](#the-ringelmann-effect)
     - [The Law of Conservation of Complexity (Tesler's Law)](#the-law-of-conservation-of-complexity-teslers-law)
     - [The Law of Demeter](#the-law-of-demeter)
@@ -598,6 +599,18 @@ See also:
 - [Metcalfe's Law](#metcalfes-law)
 - [Dunbar's Number](#dunbars-number)
 
+### The Bitter Lesson
+
+[The Bitter Lesson by Richard S. Sutton](http://www.incompleteideas.net/IncIdeas/BitterLesson.html)
+
+> The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin.
+>
+> Richard S. Sutton (2019)
+
+The "Bitter Lesson", stated by [Rich S. Sutton](https://en.wikipedia.org/wiki/Richard_S._Sutton), says that scale (in terms of both data and computational power) has driven the most significant advancements in AI research, rather than the intricacies of the research methods themselves.
+
+He goes on to suggest that this indicates we should stop trying to build simplified (or even complex) models of the mind as history has shown that these have always in the long term been failures compared to (as an example) scaling the capacity of neural networks and applying existing methods such as convolution.
+
 ### The Ringelmann Effect
 
 [The Ringelmann effect on Wikipedia](https://en.wikipedia.org/wiki/Ringelmann_effect)