Research Memo: The Economics of Engineered Obsolescence
Classification: Cultural Engineering - Competency Degradation Studies
We track a phenomenon that doesn’t appear in disruption literature but should: the intentional obsolescence not of products, but of skills. Not technological unemployment—that’s well-documented—but something more subtle: the strategic erosion of user competency.
The Pattern Framework
Phase 1: The Enabling (1998-2008) Technology arrives promising empowerment. User competency increases:
- HTML basics taught in high schools
- File systems navigated by average users
- Software installation requires technical decision-making
- Troubleshooting becomes transferable skill
Skill transfer rate: High Residual knowledge: Long-term User sovereignty: 78%
Phase 2: The Intervention (2009-2015) The turning point arrives disguised as simplification:
- “User-friendly” interfaces hide underlying complexity
- Default settings govern 94% of configurations
- Manual overrides become deprecated features
- Documentation shifts from technical reference to “getting started” tutorials
Skill transfer rate: Moderate, but declining Residual knowledge: Medium-term, begins decaying in 18-24 months without practice User sovereignty: 51%
Phase 3: The Capture (2016-2020) Competency becomes product differentiator, then obsolete:
- Skills replaced by subscriptions
- Knowledge becomes service
- User learns interface, not system
- Platform dependency reaches critical threshold
Skill transfer rate: Low, specialized to platform Residual knowledge: Short-term, specialized and non-transferable User sovereignty: 23%
Phase 4: Manufactured Oblivion (2021-Present) Users literally forget what was once common knowledge:
- File management → Cloud sync (users can’t locate files without search)
- Software installation → App stores (users confused by .exe files)
- Hardware troubleshooting → Device replacement (users lack diagnostic vocabulary)
- Information seeking → Algorithmic feeds (users forget search operators)
Skill transfer rate: Negligible Residual knowledge: Episodic and context-dependent User sovereignty: 8%
Case Study: The Automobile Paradox
Historical Baseline (1950-1995): The average driver understood:
- Basic combustion engine principles
- Points ignition timing
- Carburetor adjustment
- When to change oil (visually, by darkness/thickness)
- Tire pressure and wear patterns
- Battery maintenance and charging
Competency score on OPOD scale: 6.2/10 Average maintenance cost: $300-800/year Average vehicle lifespan: 15-20 years
Manufactured Oblivion Period (1996-2015): Vehicle computerization begins. Mental model shifts:
- Check engine light becomes mystical oracle
- “Factory recommended maintenance” replaces visual inspection
- Specialized tools required for basic diagnostics
- DIY maintenance becomes economically irrational (tool investment exceeds savings)
Key insight: This wasn’t inevitable. Computerization could have provided more diagnostic information. Instead, it provided less accessible information. The user interface moved from open (lift hood, visually inspect) to closed (connect proprietary scanner, read manufacturer codes).
Competency score: 4.1/10 (34% drop) Average maintenance cost: $800-1500/year Average vehicle lifespan: 11-14 years
Current State (2016-Present): Modern vehicle requires:
- Proprietary software for diagnostic access
- Subscription service for feature activation
- Dealership-level tools for routine maintenance
- Technical equipment for battery replacement (Tesla Model 3: battery replacement requires factory reset procedure)
Most drivers cannot:
- Change their own oil
- Replace brake pads
- Diagnose common issues
- Jump-start vehicle without consulting manual
- Identify basic engine components
Competency score: 1.8/10 (71% drop from baseline) Average maintenance cost: $1500-3000/year Average vehicle lifespan: 8-10 years
The pattern: Capability → Interface → Dependency → Oblivion
Cross-Domain Analysis
Computing:
- 2005: User understands file paths, extensions, program installation, basic troubleshooting
- 2015: User understands app ecosystems, cloud sync, but can’t diagnose system issues
- 2025: User confused by file system concepts; “where is my file?” becomes support ticket
Photography:
- 2001: User understands exposure triangle, film speed, aperture relationship
- 2011: User understands DSLR modes, RAW processing, basic correction
- 2021: User understands filter presets; technical knowledge vestigial
Music:
- 1999: User understands audio formats, bitrates, file management
- 2009: User understands streaming quality tiers, playlist curation
- 2019: User accepts algorithmic recommendations; ownership concept dissolves
Home Maintenance:
- 1995: User can repair basic appliances, understands electrical circuits, plumbing fundamentals
- 2005: User can follow YouTube tutorial for specific model
- 2015: User calls repair service; products designed for replacement, not repair
- 2025: User subscribes to appliance-as-a-service; ownership and maintenance obsolete
The Economics Beneath
Platform economics require user incompetency:
- Competent users don’t subscribe to services; they build their own
- Competent users don’t need technical support; they troubleshoot
- Competent users can migrate between platforms; they maintain portable skills
- Competent users understand value; they resist pricing arbitrage
Therefore: Competency must be managed downward.
Methods observed:
- Semantic Inflation: Redefine “technical” to exclude basic functions
- Interface Obscurantism: Hide system behind layers of abstraction
- Default Governance: Make non-default choices economically irrational
- Documentation Degradation: Shift from technical reference to tutorial ecosystem
- Legal Encirclement: Terms of service prohibit modification or investigation
The Cultural Dimension
What’s lost isn’t just technical skill—it’s entire epistemologies:
- Self-reliance: The confidence that problems are solvable through understanding
- Systemic thinking: The ability to deduce behavior from underlying principles
- Ownership literacy: Understanding what you own vs. license vs. lease
- Maintenance culture: The aesthetic of repairing, tinkering, improving
The replacement epistemology:
- Subjective confidence: Trust in brand, platform, authority
- Interface literacy: Knowing how to operate, not how it works
- Disposable culture: Replace rather than repair
- Algorithmic deference: Trust the recommendation engine
Archival Status
This dispatch documents a pattern more dangerous than planned obsolescence of products: the planned obsolescence of user capability. We are observing the largest transfer of technical sovereignty in history—not to new masters, but to non-existence.
The skills themselves are being erased from cultural memory.
We can map the decay curves, identify inflection points, track the methodology. What we cannot yet predict: whether this is permanent cultural evolution or reversible amnesia.
Two possible futures:
- Permanent dependency: Users accept incompetence as natural state
- Tinkerer resurgence: Economic necessity drives skill reacquisition
OPOD is tracking both hypotheses. Our data suggests the former is winning, but emergence of repair cafes, right-to-repair movements, and retrocomputing communities may indicate counter-trend.
Either way: We are living through the deliberate forgetting of what came before. The skill gaps are not bugs in the system. They are the system working as designed.
Proceed to Archive. Classification: Active Research.