How many spoons does your environment cost
summary
Shows live failing demos: GPU vs Apple silicon breakage, missing libgo.so.1 from OS linker, Docker platform/memory mismatches, broken editable installs and dependency conflicts. Claims cognitive cost matters — spoon theory mapped to environment friction — and cites a 23-minute switching cost for task recovery. Notes concrete fixes and standards: PEP 751 pylock.toml, PEP 723, multi‑arch Docker builds, and where pip/conda tooling actually succeeds or still trips. Watch if concrete failure modes, error messages, and remediation steps decide viewing.
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chapters (12)
- 0:00Welcome
- 1:11Python environments hard
- 3:19Spoon theory explained
- 7:17Demo failure hardware
- 10:09Demo failure naming
- 14:27Demo failure OS
- 16:32Hardware abstraction limits
- 18:17Why environments fail
- 20:02Demo failure Docker
- 21:29Ecosystem PEPs
- 22:33Demo failure deps
- 23:36Sustainable autonomy
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