{"slug": "ai-is-giving-software-its-quartz-moment", "title": "AI is giving software its quartz moment", "summary": "AI is giving software its quartz moment, according to Camilo Nova, CEO of an unnamed company, who draws a parallel between the 1969 Seiko Quartz Astron 35SQ and the current AI shift. The quartz watch, initially expensive and unthreatening, eventually collapsed Swiss watch employment from 90,000 to 33,000 and reduced manufacturers from 1,618 to 634 between 1970 and 1985, as AI similarly rewrites software economics by replacing specialized labor with scalable technology.", "body_md": "Blog\n\n# AI is giving software its quartz moment\n\nCamilo Nova\n\nCEOOn Christmas Day in 1969, Seiko released a watch that looked nothing like the beginning of an industrial collapse.\n\nThe [Quartz Astron 35SQ](https://www.seikowatches.com/global-en/products/astron/special/story_qa50th_1) came in an eighteen-karat gold case and cost ¥450,000, more than many popular cars in Japan at the time. Its development team had produced only 20 watches by December.\n\nThis was not a cheap watch for the masses. It was an expensive technological demonstration.\n\nInside it, however, was a completely different way to tell time.\n\nInstead of relying on a carefully assembled system of springs, wheels, jewels, and escapements, the Astron used a battery, an integrated circuit, a small motor, and a quartz crystal vibrating 8,192 times per second.\n\nIt was accurate to within five seconds per month, about 100 times more accurate than a typical mechanical watch of the period.\n\nThe first Astron did not look disruptive because people were looking at the product rather than the technology beneath it.\n\nIt was expensive. It was difficult to manufacture. It did not yet threaten an industry that had spent centuries perfecting mechanical watchmaking.\n\nBut quartz was not competing on the same production curve.\n\nIn 1945, Switzerland produced approximately 19 million of the world’s 21.5 million watches. That production was distributed across roughly 2,500 companies, 90% of which employed fewer than 50 people.\n\nThe industry depended on specialized workshops, skilled labor, apprenticeships, coordination, and knowledge accumulated over generations.\n\nQuartz replaced much of that system with electronics.\n\nOnce manufacturers had invested in the necessary machinery, they could produce watches with fewer components, less assembly knowledge, lower labor requirements, and dramatically lower marginal costs.\n\nQuartz watch prices eventually [fell by roughly one thousand times](https://en.wikipedia.org/wiki/Quartz_crisis). What started at the price of a car became something that could be sold in a convenience store.\n\nA cheaper production method does not simply lower prices. It rewrites the industry map.\n\nQuartz turned precision machinery into mass-market electronics. For the first time, watch manufacturing had the economics of a technology business operating inside an artisan market.\n\nHigh fixed costs. Low variable costs. Economies of scale. Operating leverage.\n\nOnce the curve started moving, the transformation happened quickly.\n\nBy the end of the 1970s, quartz watches were cheaper and more accurate than mechanical ones. In most situations, the mechanical watch had become functionally obsolete.\n\nThe functional market went to quartz.\n\nThe effect on Switzerland was devastating. Between 1970 and 1985, the number of Swiss watch manufacturers [fell from 1,618 to 634](https://www.hautehorlogerie.org/en/watches-and-culture/library/a-view-of-the-swiss-watch-industry). Employment collapsed from more than 90,000 people to approximately 33,000.\n\nQuartz did not eliminate watches. It separated the function of telling time from the business of watchmaking.\n\nMechanical watches survived by becoming something else.\n\nThey became objects of craftsmanship, scarcity, identity, heritage, and status. The fact that a mechanical watch was more complicated, less accurate, more expensive, and labor-intensive no longer counted as a weakness.\n\nThose characteristics became exactly the reason to buy one.\n\nDecades later, mechanical watches accounted for only 37 percent of Swiss watch exports by unit volume but more than 85 percent of their value.\n\nSwitzerland lost the mass market and captured the premium one (probably by accident).\n\nNot every Swiss company understood what was happening.\n\nOmega entered the 1970s as one of the most important watch brands in the world. Its watches had reached the moon (I'm wearing that one). It sponsored the Olympics. As late as 1977, it remained the third largest watch brand behind Seiko and Timex.\n\nThen it panicked.\n\nOmega launched too many models, moved heavily into quartz, expanded across price points, licensed its brand, and tried to compete with the new manufacturers on their terms.\n\nIt attempted to install a new technology within an organization designed for a completely different economic model.\n\nQuartz manufacturing required another culture, cost structure, workforce, and operating model. A mechanical watch company and a quartz company could both produce objects that told time while having almost nothing else in common.\n\nRolex chose another path.\n\nIt did not ignore quartz. Rolex invested heavily in the technology and produced the Oysterquartz in limited quantities. It preserved its ability to follow the market if necessary.\n\nBut it did not attempt to beat Japanese manufacturers at producing the cheapest and most accurate watch.\n\nInstead, Rolex leaned into what quartz could not commoditize: consistency, engineering, scarcity, history, distribution, brand, and control over the customer experience.\n\nIt stopped competing primarily on the watch's accuracy and strengthened the ** meaning of owning one**.\n\nThis is the part of the story the software industry should be studying.\n\nSoftware has always had unusual economics. Once software exists, distribution is almost free. But creating it remains expensive.\n\nBuilding serious software requires developers, designers, product managers, infrastructure engineers, security specialists, testing, coordination, and months or years of accumulated context.\n\nAI is blowing away that creation cost.\n\nThe foundation model is the expensive factory. Training requires enormous capital, infrastructure, data, energy, and specialized talent.\n\nBut once the model exists, generating another function, interface, test, migration, or prototype can have an extremely low marginal cost.\n\nThis is remarkably similar to quartz.\n\nHigh fixed costs. Falling variable costs. Increasing automation. Less dependence on scarce artisanal labor.\n\nThe software equivalent of a quartz crystal is not a single coding assistant. It is the combination of foundation models, inexpensive inference, coding agents, automated testing, and natural language interfaces.\n\nTogether, they are beginning to separate code production from the traditional craft of programming.\n\nThe change is already visible.\n\n[Vercel’s v0](https://vercel.com/docs/v0) allows people to describe an application in natural language and receive the code, interface, and deployable project in return. The user does not need to begin with a programming language. The user begins with an idea.\n\nThat is the software equivalent of quartz: a lower-friction core technology that makes a once-specialized craft accessible to far more people.\n\nThe numbers show the direction of the curve.\n\nThe cost of querying an AI model at approximately the [GPT-3.5 level fell](https://hai.stanford.edu/ai-index/2025-ai-index-report/research-and-development) from $20 per million tokens in November 2022 to $0.07 by October 2024.\n\nThat is a reduction of more than 280 times in approximately 18 months. Depending on the task, inference prices were falling between 9 and 900 times per year.\n\nCapability has been moving almost as quickly. On SWE Bench Verified, a benchmark based on real software issues, the leading model performance rose from approximately 60 percent to nearly 100 percent in a [single year](https://hai.stanford.edu/ai-index/2026-ai-index-report).\n\nThe systems remain imperfect. But they are no longer toy demonstrations.\n\nThe first quartz clock, built at Bell Labs in 1927, occupied an entire room. The first commercial quartz wristwatch was priced like a car.\n\nThe mistake would have been measuring the first product and ignoring the learning curve.\n\nThe cost of generating code is not the total cost of delivering dependable software.\n\nArchitecture, security, integration, product judgment, deployment, maintenance, and accountability remain expensive.\n\nBut the marginal cost of producing competent code is collapsing. That changes the industry's structure even before AI becomes fully autonomous.\n\nSoftware may be approaching the same separation that happened in watches.\n\nSimple interfaces, internal dashboards, administrative systems, integrations, prototypes, reports, marketing sites, and narrow workflow applications are becoming the equivalent of basic timekeeping.\n\nThey will not disappear. There may be more of them than ever.\n\nBut producing them will require less time, less capital, and fewer people.\n\nA department that previously had to purchase a large platform may generate a small application for its exact process. A company that could afford one major software initiative may launch twenty experiments.\n\nSome applications may be temporary, created for a project and discarded afterward, just as inexpensive quartz watches became accessories rather than lifelong possessions.\n\nThe quantity of software could explode while the price of an individual piece of software collapses.\n\nThat is bad news for businesses whose value depends primarily on the difficulty of writing code.\n\nIt is especially dangerous for consulting firms that charge according to team size, development hours, or the apparent complexity of implementation.\n\nWhen production becomes faster, maintaining the same organizational structure and billing model does not preserve value. It exposes how much of the old price depended on scarcity.\n\nMany software companies are making the Omega move, and I can't blame them.\n\nThey buy AI tools, attach them to the existing workflow, keep the same management layers, same pricing, and ask developers to produce more code.\n\nThey treat AI as an efficiency feature rather than a different production system.\n\nAn AI native software company does not look like a traditional software company with a coding assistant subscription.\n\nIt should have different team sizes, different responsibilities, different margins, different delivery cycles, and a different definition of what customers are paying for.\n\nThe software version of Rolex will not be a company that proudly writes every line by hand.\n\nNobody will pay extra because a developer manually typed a database migration that an AI could have produced safely in seconds.\n\nRomanticizing inefficient code production would be like selling a less accurate watch while refusing to explain why it matters.\n\nThe premium layer in software will come from judgment, trust, domain knowledge, product taste, proprietary data, integration, security, distribution, and accountability.\n\nCustomers will not pay for the code.\n\nThey will pay for choosing the right problem, making the right trade-offs, fitting the system into a complex organization, keeping it reliable, and taking responsibility when something goes wrong.\n\nThe strongest companies will use AI aggressively inside their production process while making that process almost invisible to customers.\n\nTheir promise will not be that they employ more programmers.\n\nTheir promise is that they understand the business, deliver the results, and remain accountable for them.\n\nThe quartz revolution did not destroy the watch industry. It destroyed the assumption that telling time was the whole industry.\n\nAI may not destroy software. It will destroy the assumption that writing code is the whole industry.\n\nWhat happens to software subscriptions when a customer can generate a credible replacement?\n\nWhat happens to agencies when months of implementation become days?\n\nWhat happens to junior developers when the repetitive work that once trained them is automated?\n\nWill companies continue purchasing enormous platforms, or will they build hundreds of smaller systems tailored to their specific operations?\n\nWhich businesses will become Seiko, producing useful software at an extraordinary scale and low cost?\n\nWhich will become Rolex, capturing value through trust, judgment, and ownership?\n\nWhich will behave like Omega, trapped between a disappearing craft economy and a production model they were never designed to compete in?\n\nAnd when code is no longer scarce, what exactly will a software company be selling?\n\nWritten by Camilo Nova\n\nAxiacore CEO. Camilo writes thoughts about the intersection between business, technology, and philosophy\n\nSubscribe to our newsletter here:\n\nLearn how to use technology to get back your time and enjoy an empty calendar on a work day.\n\nWe respect your inbox. [Privacy policy](/privacy-policy/)", "url": "https://wpnews.pro/news/ai-is-giving-software-its-quartz-moment", "canonical_source": "https://axiacore.com/blog/ai-is-giving-software-its-quartz-moment-1016/", "published_at": "2026-07-24 21:24:04+00:00", "updated_at": "2026-07-24 21:52:25.056300+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-products", "ai-infrastructure"], "entities": ["Seiko", "Quartz Astron 35SQ", "Omega", "Switzerland", "Camilo Nova"], "alternates": {"html": "https://wpnews.pro/news/ai-is-giving-software-its-quartz-moment", "markdown": "https://wpnews.pro/news/ai-is-giving-software-its-quartz-moment.md", "text": "https://wpnews.pro/news/ai-is-giving-software-its-quartz-moment.txt", "jsonld": "https://wpnews.pro/news/ai-is-giving-software-its-quartz-moment.jsonld"}}