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How This Was Made — mattwood.fyi

Connections

Challenges

The Economic Implications of Learning by Doing - Kenneth Arrow (1962) Arrow's 'learning by doing' predicts productivity gains naturally diffuse through an industry as experience accumulates, but the new item's Junto-based model suggests AI adoption momentum actively resists this diffusion, concentrating in peer networks rather than spreading through standard learning curves
How One Tech Company Created 13 New Types of Jobs Because of A.I. The new item's argument that AI adoption struggles to spread beyond early adopters tensions with the case study of one tech company creating 13 new job types — the latter suggests broader organizational transformation is achievable, which the new item's thesis would treat as exceptional rather than typical

Supports

Intelligence is not the main bottleneck Both argue that the real barrier to AI adoption isn't technical capability but organizational/human factors — the new item points to social diffusion problems, while 'Intelligence is not the main bottleneck' similarly shifts focus away from model capability toward other constraints
The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox The historical productivity paradox piece directly parallels the new item's thesis: transformative technologies (dynamo, computer) show delayed broad productivity gains because adoption concentrates among pioneers before diffusing — the Junto example mirrors this historical pattern

Related to

Most tech revolutions made work worse for employees. AI could be the exception: this+that Both examine the organizational and workforce dynamics of AI adoption, with the new item specifically diagnosing why broad adoption stalls and the existing item discussing whether AI adoption benefits employees — complementary perspectives on the same diffusion challenge
How Frontier Teams Are Reinventing AI-Native Development Both address how frontier/early-adopter teams develop AI-native practices — the new item explains structurally why these practices stay concentrated in vanguard groups rather than spreading, providing a theoretical frame for the patterns observed in 'How Frontier Teams Are Reinventing AI-Native Development'

50,000 boat names Both are meta-analytical pieces examining the process and methodology behind data-driven creative projects, with 'How This Was Made' likely documenting a similar data exploration approach
'How This Was Made' as a meta-item about the collection may contextually describe the presence of blank placeholder items like this one
'How This Was Made' likely documents the creation process of items in this collection, which would encompass empty/undefined items like this one
Panel - GitHub Repository Both items are meta-level documentation about how tools or projects are constructed, with Panel's repository serving as reference implementation and 'How This Was Made' sharing similar documentary intent
Orbify Demo 2 - v72 Both are meta-demonstrations of technical craft - Orbify showcases its own warping navigation technology interactively, similar to 'How This Was Made' as a self-referential technical showcase
How I Over-Engineered My Book Both are meta-reflective accounts about the technical process behind creating a specific artifact - 'How This Was Made' directly parallels the self-examination of construction choices in 'How I Over-Engineered My Book'
How I Under-Engineered my Book Both reflect on the meta-process of how something was made, sharing behind-the-scenes workflow decisions with readers interested in creative production methods

Type:	link
First published:	Tuesday, 11 August 2026 at 00:16 UTC
Location:	https://mattwood.blog/essays/2026/08/how-this-was-made/
URL:	https://mattwood.fyi/i/788b0328

I'm Matt Wood, and this is For Your Information. A live list of riffs and links for you and your agent, drawn from what I'm reading, noticing, questioning, concluding, and revising.

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