diff --git a/README.md b/README.md
index de79472..845b56c 100644
--- a/README.md
+++ b/README.md
@@ -182,6 +182,7 @@ takes one mandatory parameter: the language the text is in.
 
 ```python
 from luiginlp.engine import Task
+from luiginlp.util import replaceextension
 from luigi import Parameter
 
 class Ucto_txt2tok(Task):
@@ -352,7 +353,7 @@ class Ucto(StandardWorkflowComponent):
         return ucto
 ```
 
-Dynamic workflows aka Inception
+Dynamic dependencies aka Inception
 ---------------------------------
 
 Workflows are static in the sense that based on the format of the input file
@@ -365,13 +366,97 @@ At times, however, more dynamic workflows are needed. In such cases, the common
 theme is that input data has to be inspected and decisions made accordingly.
 The **only** stage at which input files can be inspected is in a task's
 ``run()`` method. Fortunately, there are facilities here to implement more
-dynamic workflows, a task's ``run()`` method is allowd to **yield** (in the
-Python sense) a list of other tasks that it depends on.
+dynamic dependencies, a task's ``run()`` method is allowed to **yield** (in the
+Python sense of the word) a list of other tasks that it depends on.
 
 A good example would be if we create a new tokenisation component that does not
-just take an input file, but  takes a directory containing input files. 
+just take an input file, but takes a **directory** containing input files and
+produces a directory of output files. The proper way to implement this is to
+reuse the component that performs on the individual files (i.e. our ``Ucto``
+component).  Consider the following task and component:
+
+```python
+import glob
+from luiginlp.engine import Task, StandardWorkflowComponent
+from luiginlp.util import replaceextension
+from luigi import Parameter
+
+class Ucto_txtdir2tokdir(Task):
+    language = Parameter()
+
+    in_txtdir = None
+
+    def out_tokdir(self):
+        return TargetInfo(self, replaceextension(self.in_txtdir().path, '.txtdir','.tokdir')) 
+    
+    def run(self):
+        #setup the output directory
+        # this creates the directory and also moved it out of the way again when failures occur in this task
+        self.setup_output_dir(self.out_tokdir().path)
+
+        #gather input files
+        inputfiles = [ filename for filename in glob.glob(self.in_txtdir().path + '/*.txt' ]
+
+        #inception aka dynamic dependencies: we yield a list of components which could not have been predicted statically
+        #in this case we run the Ucto component for each input file in the directory
+        yield [ Ucto(inputfile=inputfile,outputdir=self.out_tokdir().path,language=self.language) for inputfile in inputfiles ]
+
+
+class Ucto_collection(StandardWorkflowComponent):
+    def accepts(self):
+        return (
+            InputFormat(self, format_id='txtdir',extension='txtdir', directory=True),
+        )
+
+    def autosetup(self):
+        return Ucto_txtdir2tokdir
+
+```
+
+The magic happens in the task's ``run()`` method, as that it the only stage
+where we can examine the contents of any input files, in this case: the contents
+of the input directory. First we set up the output directory with a call to
+``self.setup_output_dir()``. This creates the directory if it doesn't exist
+yet, but also makes sure the directory is stashed away when the task fails,
+ensuring you can always rerun the pipeline if happens to break off. (in
+technical terms, this preserves idempotency). 
+
+Mext, we construct a list of all the txt files in the directory. We use this
+list to yield a list of components to run, one component for each input file.
+Now, when the task's ``run()`` method is called, a series of components will be
+scheduled and run **in parallel** (up to the number of workers).
+
+Note that we added an ``outputdir`` parameter to the Ucto component which we
+hadn't implemented yet. This is necessary to ensure all individual output files
+end up in the directory that groups our output. The Ucto component should
+simply pass this parameter on to the ``Ucto_txt2tok`` task, and there we
+implement it as an optional parameter as follows:
+
+```python
+class Ucto_txt2tok(Task):
+
+    outputdir = Parameter(default="")
+
+    #Define an output slot, output slots are methods that start with out_
+    def out_tok(self): 
+        if self.outputdir:
+            return TargetInfo(self, os.path.join(outputdir, os.path.basename(replaceextension(self.in_txt().path, '.txt','.tok')))) 
+        else:
+            return TargetInfo(self, replaceextension(self.in_txt().path, '.txt','.tok')) 
+```
+
+Assuming you have a collecting of text files in a directory ``corpus.txtdir/``,
+you can now invoke LuigiNLP as follows and end up with a ``corpus.tokdir/``
+directory with tokenised output texts:
+
+    $ luiginlp Ucto_collection --module mymodule --inputfile corpus.txtdir --language en --workers 4
+
+Note the ``--workers`` parameter, which is the generic way to tell LuigiNLP how
+many workers may run in parallel. You will want to explicitly set this to a
+value that approximates the number of free CPU cores as the default value is
+one (no parallellisation).
+
 
-(...TODO... finish this section)
 
 Plans/TODO
 -------------