"We're entering a new world in which data may be more important than software"
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The provocation isn’t that software is suddenly irrelevant; it’s that software is becoming cheap, copyable plumbing while data turns into the scarce asset with gravitational pull. O’Reilly is writing from the publisher-as-ecosystem-builder vantage point: he’s spent decades watching tech empires form less around clever code than around feedback loops that capture behavior at scale. In that light, “new world” is doing heavy lifting. It implies a phase change: the industry’s center of value shifting from shipping products to operating platforms.
The subtext is a warning dressed up as a forecast. If data is “more important,” then power accrues to whoever can collect, normalize, and retain it, not necessarily whoever writes the most elegant software. Software can be open-sourced, cloned, or commoditized; the dataset behind Google Search, Amazon’s recommendations, or a mapping service can’t be recreated without time, users, and infrastructure. Data becomes both moat and map: it defends incumbents and guides their next move.
Contextually, this line sits in the mid-2000s Web 2.0 moment, when “the internet as platform” replaced “software as product.” It’s also an early sketch of today’s AI economy, where model performance is often gated less by architecture than by training data, data rights, and distribution. The intent isn’t techno-mysticism; it’s a practical revaluation: pay attention to what scales, what compounds, and what locks competitors out. The uncomfortable corollary is that governance matters too, because when data outranks software, privacy, ownership, and accountability stop being side issues and start being the main plot.
The subtext is a warning dressed up as a forecast. If data is “more important,” then power accrues to whoever can collect, normalize, and retain it, not necessarily whoever writes the most elegant software. Software can be open-sourced, cloned, or commoditized; the dataset behind Google Search, Amazon’s recommendations, or a mapping service can’t be recreated without time, users, and infrastructure. Data becomes both moat and map: it defends incumbents and guides their next move.
Contextually, this line sits in the mid-2000s Web 2.0 moment, when “the internet as platform” replaced “software as product.” It’s also an early sketch of today’s AI economy, where model performance is often gated less by architecture than by training data, data rights, and distribution. The intent isn’t techno-mysticism; it’s a practical revaluation: pay attention to what scales, what compounds, and what locks competitors out. The uncomfortable corollary is that governance matters too, because when data outranks software, privacy, ownership, and accountability stop being side issues and start being the main plot.
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| Topic | Technology |
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