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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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Why AI Efficiency May Be Making Your Organization More Fragile

By Brinda Sarathy, Rajeshwari Ganesan | September 25, 2025

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Trust but Verify

By Andrew Stellman | September 24, 2025

podcast

Generative AI in the Real World: Faye Zhang on Using AI to Improve Discovery

By Ben Lorica, Faye Zhang | September 18, 2025
Generative AI in the Real World: Faye Zhang on Using AI to Improve Discovery
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Prompt Engineering Is Requirements Engineering

By Andrew Stellman | September 17, 2025

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MCP in Practice

By Ilan Strauss, Sruly Rosenblat, Isobel Moure, Tim O’Reilly | September 16, 2025

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When AI Writes Code, Who Secures It?

By Chloé Messdaghi | September 15, 2025

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Taming Chaos with Antifragile GenAI Architecture

By Shreshta Shyamsundar | September 11, 2025

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Building AI-Resistant Technical Debt

By Andrew Stellman | September 10, 2025

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Megawatts and Gigawatts of AI

By Mike Loukides | September 9, 2025

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A “Beam Versus Dataflow” Conversation

By Aaron Black | September 8, 2025

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AI Security Takes Center Stage at Black Hat USA 2025

By Simina Calin | September 4, 2025

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Looking Forward to AI Codecon

By Tim O’Reilly | September 3, 2025

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Working with Contexts

By Drew Breunig | August 28, 2025

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MCP Introduces Deep Integration—and Serious Security Concerns

By Andrew Stellman | August 27, 2025

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LLM System Design and Model Selection

By Louis-François Bouchard, Louie Peters | August 26, 2025

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Firing Junior Developers Is Indeed the “Dumbest Thing”

By Mike Loukides | August 25, 2025