diff --git a/.gitignore b/.gitignore
index 4f40a94..b5b8334 100644
--- a/.gitignore
+++ b/.gitignore
@@ -164,7 +164,7 @@ cython_debug/
 
 # Figures and videos
 figures/
-*.png
+#*.png
 *.pdf
 *.jpg
 *.jpeg
@@ -188,4 +188,4 @@ figures/
 env*
 
 # VS code
-.vscode/*
\ No newline at end of file
+.vscode/*
diff --git a/README.md b/README.md
index 1b21732..95baae7 100644
--- a/README.md
+++ b/README.md
@@ -1,27 +1,85 @@
-# maxplotlib
+# Maxlotlib
 
-This is a wrapper for matplotlib so I can produce figures with consistent formatting. It also has some pretty nice additions such as using layers and exporting to tikz.
+
+# Maxplotlib
+
+A clean, expressive wrapper around **Matplotlib** **tikzfigure** for
+producing publication-quality figures with minimal boilerplate. Swap
+backends without rewriting your data — render the same canvas as a crisp
+PNG, an interactive Plotly chart, or camera-ready **TikZ** code for
+LaTeX.
 
 ## Install
 
-Create and activate python environment
+``` bash
+pip install maxplotlibx
+```
+
+## Showcase
+
+### Quickstart
 
+``` python
+import numpy as np
+from maxplotlib import Canvas
+
+x = np.linspace(0, 2 * np.pi, 200)
+y = np.sin(x)
+
+canvas, ax = Canvas.subplots()
+ax.plot(x, y)
 ```
-python -m venv env
-source env/bin/activate
-pip install --upgrade pip
+
+Plot the figure with the default (matplotlib) backend:
+
+``` python
+canvas.show()
 ```
 
-Install the code and requirements with pip
+![](README_files/figure-markdown_strict/cell-3-output-1.png)
+
+Alternatively, plot with the TikZ backend (not done yet):
 
+``` python
+canvas.show(backend="tikzfigure")
 ```
-pip install -e .
+
+![](README_files/figure-markdown_strict/cell-4-output-1.png)
+
+### Layers
+
+``` python
+x = np.linspace(0, 2 * np.pi, 200)
+
+canvas, ax = Canvas.subplots(width="10cm", ratio=0.55)
+
+ax.plot(x, np.sin(x), color="steelblue", label=r"$\sin(x)$", layer=0)
+ax.plot(x, np.cos(x), color="tomato", label=r"$\cos(x)$", layer=1)
+ax.plot(
+    x,
+    np.sin(x) * np.cos(x),
+    color="seagreen",
+    label=r"$\sin(x)\cos(x)$",
+    linestyle="dashed",
+    layer=2,
+)
+
+ax.set_xlabel("x")
+ax.set_legend(True)
 ```
 
-Additional dependencies for developers can be installed with
+Show layer 0 only, then layers 0 and 1, then everything:
 
+``` python
+canvas.show(layers=[0])
 ```
-pip install -e ".[dev]"
+
+![](README_files/figure-markdown_strict/cell-6-output-1.png)
+
+Show all layers:
+
+``` python
+canvas.show()
 ```
 
-Some examples can be found in `tutorials/`
\ No newline at end of file
+![](README_files/figure-markdown_strict/cell-7-output-1.png)
diff --git a/README.qmd b/README.qmd
new file mode 100644
index 0000000..980b775
--- /dev/null
+++ b/README.qmd
@@ -0,0 +1,86 @@
+---
+title: Maxlotlib
+format: gfm
+fig-dpi: 150
+---
+
+# Maxplotlib
+
+A clean, expressive wrapper around **Matplotlib** **tikzfigure** for producing publication-quality figures
+with minimal boilerplate. Swap backends without rewriting your data — render the same canvas
+as a crisp PNG, an interactive Plotly chart, or camera-ready **TikZ** code for LaTeX.
+
+## Install
+
+```bash
+pip install maxplotlibx
+```
+
+## Showcase
+
+### Quickstart
+
+```{python}
+#| label: fig-showcase-1
+#| fig-width: 9
+#| fig-height: 6
+
+import numpy as np
+from maxplotlib import Canvas
+
+x = np.linspace(0, 2 * np.pi, 200)
+y = np.sin(x)
+
+canvas, ax = Canvas.subplots()
+ax.plot(x, y)
+```
+
+Plot the figure with the default (matplotlib) backend:
+
+```{python}
+canvas.show()
+```
+
+Alternatively, plot with the TikZ backend (not done yet):
+
+```{python}
+canvas.show(backend="tikzfigure")
+```
+
+### Layers
+
+```{python}
+#| label: fig-showcase-2
+#| fig-width: 9
+#| fig-height: 6
+
+x = np.linspace(0, 2 * np.pi, 200)
+
+canvas, ax = Canvas.subplots(width="10cm", ratio=0.55)
+
+ax.plot(x, np.sin(x), color="steelblue", label=r"$\sin(x)$", layer=0)
+ax.plot(x, np.cos(x), color="tomato", label=r"$\cos(x)$", layer=1)
+ax.plot(
+    x,
+    np.sin(x) * np.cos(x),
+    color="seagreen",
+    label=r"$\sin(x)\cos(x)$",
+    linestyle="dashed",
+    layer=2,
+)
+
+ax.set_xlabel("x")
+ax.set_legend(True)
+```
+
+Show layer 0 only, then layers 0 and 1, then everything:
+
+```{python}
+canvas.show(layers=[0])
+```
+
+Show all layers:
+
+```{python}
+canvas.show()
+```
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