In 2024, AI-generated code reached 41% of all global code output. This article explains the key drivers behind this surge, including tools like GitHub Copilot, productivity gains, security risks, and expert insights on what's next for AI in software development.
Read MoreThis article traces the technical evolution of generative AI from early probabilistic models like Markov chains to modern transformer architectures. Learn how breakthroughs in neural networks, GANs, and attention mechanisms shaped today's AI capabilities-and the challenges still ahead.
Read MoreChain-of-thought prompting forces AI coding assistants to explain their logic before generating code, reducing errors and building real understanding. Learn how this simple technique transforms how developers work with AI.
Read MoreLearn how to run effective retrospectives for Vibe Coding to turn AI code failures into lasting improvements. Discover the 7-part template, real team examples, and why this is the new standard in AI-assisted development.
Read MoreCursor 2.0 enables AI-powered multi-file changes in large codebases using a multi-agent system and Composer model. Learn how it refactors code across dozens of files, its limitations, and how it compares to alternatives like GitHub Copilot and Aider.
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