incorporating feedback

README.md

@@ -105,7 +105,7 @@ shinyApp(app$ui, app$server)
 
 Please see [`teal.gallery`](https://insightsengineering.github.io/teal.gallery) and [TLG Catalog](https://insightsengineering.github.io/tlg-catalog) to see examples of `teal` apps.
 
-Please start with the ["Getting Started" article](https://insightsengineering.github.io/teal/latest-tag/articles/teal.html) and then other [package vignettes](https://insightsengineering.github.io/teal/articles/index.html) for more detailed guide.
+Please start with the ["Technical Blueprint" article](https://insightsengineering.github.io/teal/articles/blueprint/index.html), ["Getting Started" article](https://insightsengineering.github.io/teal/latest-tag/articles/teal.html), and then other [package vignettes](https://insightsengineering.github.io/teal/articles/index.html) for more detailed guide.
 
 ## Getting help
 

vignettes/blueprint/dataflow.Rmd

@@ -32,11 +32,11 @@ sequenceDiagram;
 The sequence diagram above illustrates the different stages that data goes through within the `teal` framework, supported by the `teal.slice` R package:
 
 1. Data is loaded into the `teal` app;
-    - See the [Filter panel vignette](filterpanel.qmd) for details;
+    - See the [Filter panel vignette](filter_panel.html) for details;
 2. Data is passed to the filter panel;
     - Users _(or app developers)_ can specify filters to apply;
     - Filters can be specified globally, for the whole app, or for specific modules;
 3. Filtered data is sent to `teal` modules for analysis;
-    - Each modulev creates a [`qenv`](qenv.qmd) object track the code that is be applied to the data _(and used for reproducibility)_;
+    - Each module creates a [`qenv`](qenv.html) object track the code that is be applied to the data _(and used for reproducibility)_;
 
 Whenever filters are added or removed, the data coming into modules is re-computed, providing the `teal` module with new filtered data to conduct the required analysis.

vignettes/blueprint/index.Rmd

@@ -16,7 +16,3 @@ We will explore crucial `teal` concepts such as data flow, actors, and filter pa
 While this material will be presented at a high-level, we will direct you to our remarkable vignettes for a more in-depth understanding.
 
 Our hope is that this resource will provide new developers with a strong grasp of `teal` products, enabling them to contribute to code with confidence.
-
-## Acknowledgement
-
-The NEST initiative from Roche/Genentech launched `teal`, which is being made possible by the Core Development team within NEST.

vignettes/blueprint/products_map.Rmd

@@ -80,4 +80,4 @@ By breaking down `teal` features, modules, and calculations into dedicated R pac
 
 Additionally, this separation allows for a clear distinction between the various roles and actors involved in the development of `teal`.
 
-To learn different roles/actors in `teal` development, visit [Actors](actors.qmd).
+To learn different roles/actors in `teal` development, visit [Actors](actors.html).

vignettes/blueprint/qenv.Rmd

@@ -10,11 +10,11 @@ vignette: >
 
 ## Introduction
 
-Reproducibility is paramount in the pharmaceutical industry. 
+Reproducibility is paramount in the pharmaceutical industry.
 Accurate and consistent results are essential to ensure high-quality research and the safety of patients.
 By prioritizing reproducibility, researchers can validate their methods, confirm their findings, and contribute to the advancement of the field.
 
-`qenv` is an essential feature provided by the `teal.code` package that facilitates code reproducibility.
+[`qenv`](https://insightsengineering.github.io/teal.code/latest-tag/articles/qenv.html) is an essential feature provided by the `teal.code` package that facilitates code reproducibility.
 It is a class that stores both data and code, which enables tracking of the analytical process, and thus allows for sharing and replication of R code.
 Code is passed to a `qenv` object, where it is evaluated in a specific environment and stored, and can be retrieved on request.