diff --git a/thesis/Main.tex b/thesis/Main.tex
index 2ade45d..17ab394 100755
--- a/thesis/Main.tex
+++ b/thesis/Main.tex
@@ -898,19 +898,79 @@ By evaluating and comparing both approaches, we hope to demonstrate a more thoro
 {codebase, hardware description overview of training setup, details of deepsad setup}
 {overview of chapter given $\rightarrow$ give sequential setup overview}
 
-\todo[inline]{codebase}
+%\todo[inline]{codebase}
 
-\newsection{setup_overview}{General Description}
-  \todo[inline]{starting from deepsad codebase}
-  \todo[inline]{data preprocessed (2d projections, normalized range)}
-  \todo[inline]{k-fold data loading, training, testing}
-  \todo[inline]{deepsad + baselines = isoforest, ocsvm (deepsad ae, dim reduction)}
-  \todo[inline]{roc, prc, inference}
+\newsection{setup_overview}{Experimental Setup Overview}
+
+%\todo[inline]{starting from deepsad codebase}
+\threadtodo
+{Explain deepsad codebase as starting point}
+{what is the starting point?}
+{codebase, github, dataloading, training, testing, baselines}
+{codebase understood $\rightarrow$ how was it adapted}
+
+%\todo[inline]{data preprocessed (2d projections, normalized range)}
+\threadtodo
+{explain how dataloading was adapted}
+{loading data first point step to new training}
+{preprocessed numpy (script), load, labels/meta, split, k-fold}
+{k-fold $\rightarrow$ also adapted in training/testing}
+
+%\todo[inline]{k-fold data loading, training, testing}
+\threadtodo
+{how was training/testing adapted (networks overview), inference, ae tuning}
+{data has been loaded, how is it processed}
+{networks defined, training/testing k-fold, more metrics, inference + ae tuning implemented}
+{training procesure known $\rightarrow$ what methods were evaluated}
+%\todo[inline]{deepsad + baselines = isoforest, ocsvm (deepsad ae, dim reduction)}
+\threadtodo
+{what methods were evaluated}
+{we know what testing/training was implemented for deepsad, but what is it compared to}
+{isoforest, ocsvm adapted, for ocsvm only dim reduced feasible (ae from deepsad)}
+{compared methods known $\rightarrow$ what methods were used}
+%\todo[inline]{roc, prc, inference}
+\threadtodo
+{what evaluation methods were used}
+{we know what is compared but want to know exactly how}
+{explain roc, prc, inference with experiment left out of training}
+{experiment overview given $\rightarrow$ details to deepsad during training?}
 
 
-\newsection{setup_deepsad}{DeepSAD Description}
-  \todo[inline]{architectures, visualization, receptive field (explanation, images, x/y resolution)}
-  \todo[inline]{hyperparameters, LR, eta, epochs, latent space size (hyper param search), semi labels}
+\newsection{setup_deepsad}{DeepSAD Experimental Setup}
+\threadtodo
+{custom arch necessary, first lenet then second arch to evaluate importance of arch}
+{training process understood, but what networks were actually trained}
+{custom arch, lenet from paper and simple, receptive field problem, arch really important?}
+{motivation behind archs given $\rightarrow$ what do they look like}
+%\todo[inline]{architectures, visualization, receptive field (explanation, images, x/y resolution)}
+\threadtodo
+{show and explain both archs}
+{we know why we need them but what do they look like}
+{visualization of archs, explain LeNet and why other arch was chosen that way}
+{both archs known $\rightarrow$ what about the other inputs/hyperparameters}
+%\todo[inline]{hyperparameters, LR, eta, epochs, latent space size (hyper param search), semi labels}
+\threadtodo
+{give overview of hyperparameters}
+{deepsad arch known, other hyperparameters?}
+{LR, eta, epochs, latent space size (hyper param search), semi labels}
+{everything that goes into training known $\rightarrow$ what experiments were actually done?}
+
+\newsection{setup_matrix}{Experiment Matrix}
+
+%\todo[inline]{what experiments were performed and why (table/list containing experiments)}
+\threadtodo
+{give overview of experiments and their motivations}
+{training setup clear, but not what was trained/tested}
+{explanation of what was searched for (ae latent space first), other hyperparams and why}
+{all experiments known $\rightarrow$ how long do they take to train}
+
+\newsection{setup_hardware}{Experiment Hardware and Runtimes}
+
+\threadtodo
+{give overview about hardware setup and how long things take to train}
+{we know what we trained but not how long that takes}
+{table of hardware and of how long different trainings took}
+{experiment setup understood $\rightarrow$ what were the experiments' results}
 
 % \newsection{autoencoder_architecture}{Deep SAD Autoencoder Architecture}
 % \newsection{data_setup}{Training/Evaluation Data Distribution}