diff --git a/website/docs/api/util.jade b/website/docs/api/util.jade
index ed8b5d8e5..f14cdbb6d 100644
--- a/website/docs/api/util.jade
+++ b/website/docs/api/util.jade
@@ -225,7 +225,7 @@ p
 p
     |  Print a formatted, text-wrapped message with optional title. If a text
     |  argument is a #[code Path], it's converted to a string. Should only
-    |  be used for interactive components like the #[+a("/docs/usage/cli") CLI].
+    |  be used for interactive components like the #[+a("/docs/api/cli") CLI].
 
 +aside-code("Example").
     data_path = Path('/some/path')
diff --git a/website/docs/usage/adding-languages.jade b/website/docs/usage/adding-languages.jade
index f77acdf24..7eadde4b6 100644
--- a/website/docs/usage/adding-languages.jade
+++ b/website/docs/usage/adding-languages.jade
@@ -535,7 +535,7 @@ p
     |  #[+src(gh("spacy-dev-resources", "training/word_freqs.py")) word_freqs.py]
     |  script from the spaCy developer resources. Note that your corpus should
     |  not be preprocessed (i.e. you need punctuation for example). The
-    |  #[+a("/docs/usage/cli#model") #[code model] command] expects a
+    |  #[+a("/docs/api/cli#model") #[code model]] command expects a
     |  tab-separated word frequencies file with three columns:
 
 +list("numbers")
@@ -651,13 +651,13 @@ p
     |  If your corpus uses the
     |  #[+a("http://universaldependencies.org/docs/format.html") CoNLL-U] format,
     |  i.e. files with the extension #[code .conllu], you can use the
-    |  #[+a("/docs/usage/cli#convert") #[code convert] command] to convert it to
+    |  #[+a("/docs/api/cli#convert") #[code convert]] command to convert it to
     |  spaCy's #[+a("/docs/api/annotation#json-input") JSON format] for training.
 
 p
     |  Once you have your UD corpus transformed into JSON, you can train your
     |  model use the using spaCy's
-    |  #[+a("/docs/usage/cli#train") #[code train] command]:
+    |  #[+a("/docs/api/cli#train") #[code train]] command:
 
 +code(false, "bash").
     python -m spacy train [lang] [output_dir] [train_data] [dev_data] [--n_iter] [--parser_L1] [--no_tagger] [--no_parser] [--no_ner]
diff --git a/website/docs/usage/saving-loading.jade b/website/docs/usage/saving-loading.jade
index b11007683..3513e9505 100644
--- a/website/docs/usage/saving-loading.jade
+++ b/website/docs/usage/saving-loading.jade
@@ -28,7 +28,7 @@ p
     |  and walk you through generating the meta data. You can also create the
     |  meta.json manually and place it in the model data directory, or supply a
     |  path to it using the #[code --meta] flag. For more info on this, see the
-    |  #[+a("/docs/usage/cli/#package") #[code package] command] documentation.
+    |  #[+a("/docs/api/cli#package") #[code package]] command documentation.
 
 +aside-code("meta.json", "json").
     {
diff --git a/website/docs/usage/training-ner.jade b/website/docs/usage/training-ner.jade
index 78eb4905e..4d864ac9d 100644
--- a/website/docs/usage/training-ner.jade
+++ b/website/docs/usage/training-ner.jade
@@ -77,8 +77,8 @@ p
 p
     |  To make the model more convenient to deploy, we recommend wrapping it as
     |  a Python package, so that you can install it via pip and load it as a
-    |  module. spaCy comes with a handy #[+a("/docs/usage/cli#package") CLI command]
-    |  to create all required files and directories.
+    |  module. spaCy comes with a handy #[+a("/docs/api/cli#package") #[code package]]
+    |  CLI command to create all required files and directories.
 
 +code(false, "bash").
     python -m spacy package /home/me/data/en_technology /home/me/my_models