* Add Part 3 of the “Conda Is Not PyPI” series:

Title: Practical Power: Reproducibility, Automation, and Layering with Conda

Focus:
- Shows how conda’s embedded package metadata (`info/` + rendered recipe) enables auditable, rebuildable provenance.
- Explains reproducibility workflows with `conda-lock` (multi-platform lockfiles) and Renovate-driven automated dependency updates.
- Details performance and footprint benefits (no bundled glibc → faster CI/HPC/env creation).
- Describes layering model: conda base (multi-language distro layer) + pip/npm application layer.
- Highlights real-world advantages for data science, ML, research reproducibility, enterprise automation, and onboarding.
- Extends scope beyond “scientific Python” to DevOps / platform tooling (helm, terraform, opentofu, packer, etc.).
- Concludes the series: Part 1 (conceptual distinction), Part 2 (position on spectrum), Part 3 (practical workflows).

Authored by @dbast and @jezdez to document the practical implications of conda as a user‑space distribution.

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* Update blog/2025-11-11-conda-practical-power.mdx

Co-authored-by: h-vetinari <[email protected]>

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* Update blog/2025-11-11-conda-practical-power.mdx

Co-authored-by: h-vetinari <[email protected]>

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

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* Update blog/2025-11-11-conda-practical-power.mdx

Co-authored-by: h-vetinari <[email protected]>

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Co-authored-by: h-vetinari <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Jannis Leidel <[email protected]>