Industrialization of AI

AI's one-way evolutionary shift to commodity utility — a step-function regime change in which everyone runs faster just to stay in place.

Also known as: industrialisation (of ML), industrialisation of ML, industrialization phase (of AI), growing up, componentisation, Red Queen (evolutionary theory), Red Queen, step function shift (vs. acceleration), engineering vs craft (in software)

How authors use it

Oldest first (extraction date when no publication date is known).

Documents (4)

• AI and the Looming Competition for Margin Philipp Carlsson-Szlezak and Paul Swartz (BCG) · 2026-07-30 Reader 🖥️
  AI productivity gains are inherently deflationary — because a widely diffused technology confers no durable competitive advantage, the industries best at converting AI into productivity growth will see the fiercest price competition and margin erosion, making consumers rather than firms the real winners, so executives must invest anyway (the risk of abstention is asymmetric) while expecting the payoff to be survival, not profit.
• Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) Kent Beck — Still Burning Podcast · 2026-05-20 Reader 🖥️
  We are not in another technology hype wave but in a step-function transformation: the marginal cost of producing software is collapsing toward zero, large incumbents are adopting AI faster than any prior shift, and the whole ecosystem — not just the AI labs — is accelerating; in this 'Red Queen' regime, profit and productivity may not visibly improve because every competitor is running at the new tempo, so the only sane response is to paddle straight into the wave by sustaining the maker's compulsion (the 'itchy brain'), reshaping engineering leadership toward hands-on impact, and accepting that software engineering as a profession will resemble medicine or law more than the unique 2010s template that minted six-figure undergrads.
• The Week AI Grew Up AI Daily Brief · 2026-05-01 source ↗ Reader 🖥️
  The AI industry crossed from subsidized experimentation into mature economic infrastructure in the week of April 28, 2026 — visible simultaneously in pricing model shifts, cloud earnings, geopolitical treatment, and the industrialization of agent harnesses — and everyone from developers to governments must now operate accordingly.
• Simon Wardley's Post — Industrialisation of ML: nine notes on what to expect Simon Wardley · 2025-12 Reader 🖥️
  What is happening with AI is the industrialisation of machine learning — a one-way evolutionary shift to commodity/utility — and the right posture toward it is neither resistance nor hype but disciplined adaptation through the predictable 5-8 year co-evolution of practices, with explicit attention to where bottlenecks, supply-chain power, and inequality will actually land.

Propositions touching this concept (4)

By publication month, oldest first (extraction month when no publication date is known).

2025-12

• explicitdevelopedThe 'AI jobs apocalypse' framing is wrong; industrialisation will create new industries via adjacent possibles (componentisation), not collapse the labour market.
  Simon Wardley's Post — Industrialisation of ML: nine notes on what to expect · p4
• implicitThe framing battle ('industrialisation of ML' vs 'AI') is itself strategic — choosing the right description determines which playbook you reach for.
  Simon Wardley's Post — Industrialisation of ML: nine notes on what to expect · p16

2026-05

• competitive-dynamics / counter to BeckcontestedProfit cannot serve as the measure, because under Red Queen dynamics every competitor adopts the same technology, so the baseline shifts with you; speed (faster experimentation, faster market exploration) is the better indicator.
  Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) · p8

2026-09

• explicitWriting is a learned skill, distinct from speech (which is acquired naturally in growing up), that requires deliberately learning to structure an argument, make distinctions, and avoid becoming too attached to an earlier draft, because the thought captured in it is still developing.
  Writing vs. Thinking · p14

Open gaps (17)

• incompleteThe prescriptive 'What This Means for Executives' section treats the deflationary thesis as urgent enough to mandate immediate, full-scale investment for every executive, without differentiating strategy by how fast or slow deflation is likely to arrive given the very frictions the piece itself lists (regulation, market structure, utilization rates). A firm in a friction-heavy sector (the piece's own medical-care example) gets the identical 'the race is mandatory' prescription as one in a friction-free sector, even though the auto and agriculture case studies show the same dynamic can take seven decades to fully play out.
  AI and the Looming Competition for Margin — read next: None specified by the author — an open strategic question about how urgency should scale with an industry's specific competition-inhibitor profile.
• incompleteThe auto-industry chart's claim that margins fell 'to near 0%' doesn't specify which margin metric (gross, operating, net) is plotted or whether it's an industry-aggregate accounting figure vs. actual firm-level profitability — making the empirical anchor for the central thesis difficult to independently verify or compare against known auto-manufacturer profit margins.
  AI and the Looming Competition for Margin — read next: Primary BEA/BLS/BCG Center for Macroeconomics data cited as the chart's source.
• incompleteAsymmetry is unaddressed. If you pick a rival and they don't pick you, or if they outclass you, the 'close past outcomes' criterion fails — yet the prescription proceeds as if rivalry is a unilateral choice.
  The Power of Rivalry in Performance Boosting — read next: Game-theoretic treatments of asymmetric competition; 'Red Queen' dynamics in business strategy; status-tournament literature.
• illogicalThe China-dominance argument compresses 'supply chain understanding' into a near-sufficient condition for long-run dominance. Other variables (capital allocation efficiency, demographics, talent migration, capability of domestic models, export-control regimes, energy supply, civil-military fusion costs) are not weighed.
  Simon Wardley's Post — Industrialisation of ML: nine notes on what to expect — read next: Read against Dan Wang on Chinese tech policy, CSIS/RAND supply-chain analyses, and any sceptical takes on PRC industrial policy execution (e.g. semiconductor self-sufficiency progress vs targets).
• incompleteThe Jevons-paradox reframing (adjacent possibles becoming real) is asserted but the conditions under which adjacent possibles actually become real industries — vs stalling — are not specified. Sometimes the adjacent possible is real and stays small.
  Simon Wardley's Post — Industrialisation of ML: nine notes on what to expect — read next: Read against the slower-than-expected industrialisation histories — early electricity (the 40-year productivity paradox), enterprise software in the 1990s. Beck and Shoup on Jevons-in-coding is a sharper instantiation of this same claim worth juxtaposing.
• uninformed (mild)The post under-weights regulatory ratchets — particularly EU AI Act, sector-specific liability regimes, GDPR-style data sovereignty rules — as climatic variables that shape what 'industrialised ML' actually looks like in different jurisdictions. Wardley's mapping treats regulation as doctrine; this post treats it as background.
  Simon Wardley's Post — Industrialisation of ML: nine notes on what to expect — read next: Read alongside EU AI Act implementing acts, NSM/Datatilsynet guidance for the Norwegian context, and Frederiksen on Coop Bank sovereignty for how an enterprise actually reasons about regulatory ratchets as architectural constraint.
• incompleteThe post is silent on the cultural and organisational variation in how 'practice converges' over the 5-8 year window. Nordic public-sector institutions, Japanese manufacturers, and Silicon Valley startups will not converge to the same practice — but the post talks as if there is one convergence trajectory.
  Simon Wardley's Post — Industrialisation of ML: nine notes on what to expect — read next: Read against Cutler on organisational operating systems and the Heis stable's Norwegian-leader interviews — concrete evidence that practice-convergence is mediated by national culture and institutional shape, not just by elapsed years.
• incompleteVendor incentive distortion in the 'whole ecosystem is accelerating' claim
  Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) — read next: DORA 2025 and the Stanford/Microsoft developer-productivity studies on AI's actual code-quality effects; Gergely Orosz on enterprise sales-cycle compression; Marc Andreessen's classic 'why software is eating the world' for the prior pattern. For the contrarian counterweight: Gary Marcus and Ed Zitron on whether the AI productivity story is being narrated by the people selling it.
• incompleteThe marginal-cost claim is accounting-incomplete (Beck flags it; Grinich doesn't return)
  Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) — read next: Anything in your Kent Beck file on TCR and scope-of-done (this is exactly the conversation about plausible deniability and shrinking scope); Lorin Hochstein on operational complexity; the Böckeler harness-engineering extraction in this repo (the 'gap between running system and trusted system' is the harness-engineering surface). The Adam Tooze / Brad DeLong line on 'productivity gains that don't show up in the statistics' is the macroeconomic complement.
• incompleteThe 'descaling of software' counter-trend is named by Beck and left hanging
  Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) — read next: Steve Yegge on vibe coding; Gene Kim's vibe coding series; Simon Willison on the 'no-coder using LLMs to build real software' phenomenon; the Schoening agency-over-skills extraction in this repo (the agency thesis is the descaling-friendly side of this tug of war). Honest framing: Beck's craft instincts and Grinich's institutional instincts pull in opposite directions; you may have to choose.
• incompleteGrinich's 'industrialization phase' analogy launders externalities
  Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) — read next: Tooze on energy transitions; the IEA's compute-electricity projections; the literature on whether the late-19th-century industrialization actually 'cleaned up' or just exported externalities. For Kjetil specifically: this is the systems-thinking lens — feedback loops, stocks/flows, who absorbs what — applied to the rhetoric of inevitability.
• incompleteWhat changes about Beck specifically — the craft thinker in this regime
  Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) — read next: Beck's own recent Substack posts (Tidy First, the 'starving genies' piece, 'forest thinning'); your highlights on Beck for where he reframes craft for the agentic era; Hickey's 'Simple Made Easy' as the substrate craft argument; Ousterhout's complexity work. The persona-relevant cross-thread: this is where Kjetil's 'fragility of ideas' hidden layer touches the AI transition — if the craft of attentive code-reading is the protected attention surface, what protects it now?
• incompleteWhat does the 'itchy brain' protect against, exactly?
  Itchy Brain (Still Burning: Michael Grinich & Kent Beck on AI adoption, enterprise developer tools) — read next: Pressfield on Resistance; Cal Newport on deep work degradation under tool proliferation; the David Whyte/Maria Popova line on the difference between making and consuming; the persona's Bailey/Hyperfocus annotations on what attention needs in order to do anything. This is where the persona's hidden layer (fragility of ideas) and the episode's title concept (itchy brain) collide — and it is the most productive question the episode opens.
• incompleteThe piece argues the subsidy era is ending but never addresses what happens to the vast user base that was acquired through subsidized pricing. Will usage-based billing cause churn, consolidation around cheaper models, or a bifurcation between power users and casual users? The demand-is-infinite claim and the end-of-subsidies claim are in tension — if prices rise substantially, demand may not be as infinite as claimed.
  The Week AI Grew Up — read next: Benedict Evans or Ben Thompson on AI pricing elasticity; economic analysis of SaaS-to-usage transitions in cloud computing history
• incompleteThe claim that knowledge workers will choose to become more technical (favoring Codex over Cowork) is asserted without evidence. Historical precedent suggests the opposite — most technology adoption succeeds by lowering the technical bar, not raising it.
  The Week AI Grew Up — read next: Clayton Christensen on 'good enough' technology; history of no-code/low-code adoption
• uninformedThe piece treats the AI industry's 'growing up' entirely from a US-centric perspective. No mention of Chinese AI labs, EU regulation, or non-Western demand patterns, despite framing AI as 'critical global economic infrastructure.'
  The Week AI Grew Up — read next: Matt Sheehan on China's AI ecosystem; EU AI Act implementation updates
• incompleteThe goblin incident is treated as a curiosity with alignment implications, but the piece doesn't explore the depth of those implications — what does it mean for safety training specifically when RL quirks cascade through model stacks?
  The Week AI Grew Up — read next: Anthropic's research on reward hacking; papers on RLHF failure modes and distributional shift