LABLOOP — full weekly learning notebooks

1. Download all 41 weekly text files as a ZIP and extract it, or download one week from the table below.
2. Create a separate notebook named LABLOOP-WNN · week focus and upload its LABLOOP-WNN.txt. The same text is available as notebooklm.txt in the weekly folder. You can also upload learning-notebook.md or paste its contents. Upload one version, not duplicate copies.
3. Add the selected external reading pages or permitted PDFs separately. Links in a source do not import all their destination content; local cockpit links work only with your app running. Google’s source-import guidance documents supported source types and import limitations.
4. Use Section 10 of that week’s notebook for its specific diagram brief and copy-ready prompts for a concept map, visual lesson/slides, audio/video script, flashcards and research review. Use available Studio features or request the equivalent text outline in chat.
5. Add your actual notes and results as separate sources when you execute. Check generated explanations and visuals against sources, especially units, assumptions and planned versus achieved outcomes.

Each notebook is a reference of roughly 5,000–6,000 words. Read it in sections during the existing 600-minute week; the extra detail does not add compulsory hours. Preparation is complete, but learning, experiments, publications and external events still require their own actual evidence.

The cockpit now has 41 resource stashes named LABLOOP-W00 Notebook through LABLOOP-W40 Notebook, containing that week’s existing resource cards. Core/run/deeper labels remain visible. Existing completed cards, wins, focus history and other stashes are preserved. A saved resource is not a completed lesson. Sources with only search locators remain marked for resolution, and the source-check log records targeted checks rather than claiming universal link verification.

The original weekly specifications and gate requirements still govern acceptance. Notebooks explain the work and its scientific limits; they do not rewrite milestones or fill evidence registers with invented results. Each challenge names the original artifact, its acceptance condition and what proof to retain.

The early concepts are tools you reuse. You do not need to relearn an entire university curriculum before beginning; repair the concept needed for the current artifact, apply it, and revisit it when the next milestone makes it useful again.

The authored learning-notebook.md is the source of truth. TXT files and the ZIP are generated copies. After editing a notebook, run from the project root:

python3 execution-plan/notebooks/export_notebooks.py
python3 execution-plan/notebooks/export_notebooks.py --check

The exporter uses only Python’s standard library, verifies that all 41 weeks exist, writes a SHA-256 manifest and checks exact TXT/ZIP contents. It does not edit the notebooks, stashes, progress or evidence. Re-upload an updated source to your study notebook as needed; downloaded local exports do not automatically refresh themselves.