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The Trillion Dollar Problem – O’Reilly
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Picture this: You’re a data analyst on day one at a midsize SaaS company. You’ve got the beginnings of a data warehouse—some structured, usable data and ...

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The Java Developer’s Dilemma: Part 2 – O’Reilly
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This is the second of a three-part series by Markus Eisele. Part 1 can be found here. Stay tuned for part 3.Many AI projects fail. The reason is often ...

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Everyday AI Agents – O’Reilly
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A common misconception about O’Reilly is that we cater only to the deeply technical learner. While we’re proud of our deep roots in the tech community, the ...

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Trust but Verify – O’Reilly
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We often say AIs “understand” code, but they don’t truly understand your problem or your codebase in the sense that humans understand things. They’re ...

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When AI Writes Code, Who Secures It? – O’Reilly
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In early 2024, a striking deepfake fraud case in Hong Kong brought the vulnerabilities of AI-driven deception into sharp relief. A finance employee was ...

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Working with Contexts – O’Reilly
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The following article comes from two blog posts by Drew Breunig: “How Long Contexts Fail” and “How to Fix Your Contexts.”Managing Your Context Is the Key to ...

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The Future of Engineering Leadership – O’Reilly
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We’re still in the early days of GenAI adoption, but it’s clear that LLMs are going to materially impact the way that software is built and that engineering ...

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Normal Technology at Scale – O’Reilly
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The widely read and discussed article “AI as Normal Technology” is a reaction against claims of “superintelligence,” as its headline suggests. I’m ...

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AI First Puts Humans First – O’Reilly
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While I prefer “AI native” to describe the product development approach centered on AI that we’re trying to encourage at O’Reilly, I’ve sometimes used the ...

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Takeaways from Coding with AI – O’Reilly
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I thought I’d offer a few takeaways and reflections based on last week’s first AI Codecon virtual conference, Coding with AI: The End of Software ...

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