diff --git a/_quarto.yml b/_quarto.yml
index bbc4c44f1..52d1d2927 100644
--- a/_quarto.yml
+++ b/_quarto.yml
@@ -50,15 +50,14 @@ website:
     - text: documentation
       collapse-level: 1
       contents: 
-        - section: "Documentation"
+        - section: "For Users"
           # href: tutorials/index.qmd, This page will be added later so keep this line commented
           contents:
-          - section: "Using Turing - Modelling Syntax and Interface"
+          - section: "Using the Turing library"
             collapse-level: 1
             contents: 
               - tutorials/docs-00-getting-started/index.qmd
-              - text: "Quick Start"
-                href: tutorials/docs-14-using-turing-quick-start/index.qmd
+              - tutorials/00-introduction/index.qmd
               - tutorials/docs-12-using-turing-guide/index.qmd
               - text: "Mode Estimation"
                 href: tutorials/docs-17-mode-estimation/index.qmd
@@ -70,9 +69,8 @@ website:
               - text: "External Samplers"
                 href: tutorials/docs-16-using-turing-external-samplers/index.qmd
 
-          - section: "Using Turing - Tutorials"
+          - section: "Examples of Turing Models"
             contents: 
-              - tutorials/00-introduction/index.qmd
               - text: Gaussian Mixture Models
                 href: tutorials/01-gaussian-mixture-model/index.qmd
               - tutorials/02-logistic-regression/index.qmd
@@ -97,13 +95,15 @@ website:
               - text: "Gaussian Process Latent Variable Models"
                 href: tutorials/12-gplvm/index.qmd
 
-          - section: "Developers: Contributing"
+        - section: "For Developers"
+          contents:
+          - section: "Contributing"
             collapse-level: 1
             contents:
               - text: "How to Contribute"
                 href: tutorials/docs-01-contributing-guide/index.qmd
 
-          - section: "Developers: PPL"
+          - section: "How Turing Works"
             collapse-level: 1
             contents:
               - tutorials/docs-05-for-developers-compiler/index.qmd
diff --git a/tutorials/docs-12-using-turing-guide/index.qmd b/tutorials/docs-12-using-turing-guide/index.qmd
index b66b4d29d..56d59a144 100755
--- a/tutorials/docs-12-using-turing-guide/index.qmd
+++ b/tutorials/docs-12-using-turing-guide/index.qmd
@@ -1,5 +1,5 @@
 ---
-title: Guide
+title: "Turing's Core Functionality"
 engine: julia
 ---
 
@@ -10,6 +10,8 @@ using Pkg;
 Pkg.instantiate();
 ```
 
+This article provides an overview of the core functionality in Turing.jl, which are likely to be used across a wide range of models.
+
 ## Basics
 
 ### Introduction
diff --git a/tutorials/docs-14-using-turing-quick-start/index.qmd b/tutorials/docs-14-using-turing-quick-start/index.qmd
deleted file mode 100755
index 67d848752..000000000
--- a/tutorials/docs-14-using-turing-quick-start/index.qmd
+++ /dev/null
@@ -1,74 +0,0 @@
----
-pagetitle: Quick Start
-title: Probabilistic Programming in Thirty Seconds
-engine: julia
----
-
-```{julia}
-#| echo: false
-#| output: false
-using Pkg;
-Pkg.instantiate();
-```
-
-If you are already well-versed in probabilistic programming and want to take a quick look at how Turing's syntax works or otherwise just want a model to start with, we have provided a complete Bayesian coin-flipping model below.
-
-This example can be run wherever you have Julia installed (see [Getting Started](../docs-00-getting-started/index.qmd), but you will need to install the packages `Turing` and `StatsPlots` if you have not done so already.
-
-This is an excerpt from a more formal example which can be found [here](../00-introduction/index.qmd).
-
-## Import Libraries
-```{julia}
-# Import libraries.
-using Turing, StatsPlots, Random
-```
-
-```{julia}
-# Set the true probability of heads in a coin.
-p_true = 0.5
-
-# Iterate from having seen 0 observations to 100 observations.
-Ns = 0:100
-```
-
-```{julia}
-# Draw data from a Bernoulli distribution, i.e. draw heads or tails.
-Random.seed!(12)
-data = rand(Bernoulli(p_true), last(Ns))
-```
-
-
-## Declare Turing Model
-```{julia}
-# Declare our Turing model.
-@model function coinflip(y)
-    # Our prior belief about the probability of heads in a coin.
-    p ~ Beta(1, 1)
-
-    # The number of observations.
-    N = length(y)
-    for n in 1:N
-        # Heads or tails of a coin are drawn from a Bernoulli distribution.
-        y[n] ~ Bernoulli(p)
-    end
-end
-```
-
-
-## Setting HMC Sampler
-```{julia}
-# Settings of the Hamiltonian Monte Carlo (HMC) sampler.
-iterations = 1000
-ϵ = 0.05
-τ = 10
-
-# Start sampling.
-chain = sample(coinflip(data), HMC(ϵ, τ), iterations, progress=false)
-```
-
-
-## Plot a summary
-```{julia}
-# Plot a summary of the sampling process for the parameter p, i.e. the probability of heads in a coin.
-histogram(chain[:p])
-```
\ No newline at end of file