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AI & ML

Few technologies have the potential to change the nature of work and how we live as artificial intelligence (AI) and machine learning (ML).

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AI Overviews Shouldn’t Be “One Size Fits All”

By Tim O’Reilly | November 13, 2025

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Your AI Pair Programmer Is Not a Person

By Tim O'Brien | November 12, 2025

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The Other 80%: What Productivity Really Means

By Mike Loukides | November 11, 2025

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Fixing Enterprise Apps with AI: The T+n Problem

By Subramanian Radhakrishnan, Rajeshwari Ganesan | November 10, 2025

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Data Engineering in the Age of AI

By Andy Kwan | November 6, 2025

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Jensen Huang Gets It Wrong, Claude Gets It Right

By Tim O’Reilly | November 6, 2025

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Think Smaller: The Counterintuitive Path to AI Adoption

By Ben Lorica | November 5, 2025

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Balancing Cost, Power, and AI Performance

By Eduardo Alvarez | November 4, 2025

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The Java Developer’s Dilemma: Part 3

By Markus Eisele | October 28, 2025

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AI Integration Is the New Moat

By Tim O’Reilly | October 27, 2025

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Code Generation and the Shifting Value of Software

By Tim O'Brien | October 23, 2025

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AI Is Reshaping Developer Career Paths

By Andrew Stellman | October 22, 2025

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The Java Developer’s Dilemma: Part 2

By Markus Eisele | October 21, 2025

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A Human-Centered Approach to Competitive Advantage

By Kord Davis | October 20, 2025

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From Habits to Tools

By Andrew Stellman | October 15, 2025

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Magic Words: Programming the Next Generation of AI Applications

By Tim O’Reilly | October 15, 2025