The AI industry is currently undergoing a massive, structural paradigm shift in how we build, train, and interact with large language models. For the past couple of years, we have been living in the era of 'vibe coding'. You type a prompt into a chat interface, the model spits out a block of code, and you manually copy-paste it into your editor, hoping it works. It is a highly manual, human-in-the-loop process. But the frontier is rapidly moving toward 'agentic engineering'. In this new paradigm, AI agents don't just write snippets; they autonomously plan, navigate massive codebases, implement features, run tests, and iteratively fix their own bugs over long time horizons. Achieving this level of autonomy requires fundamentally rethinking how a model reasons, how it handles immense context windows, and'crucially'how we align it using reinforcement learning. Z.ai's GLM-5 is an absolute masterclass in systems engineering that tackles these exact bottlenecks. Let's crack open the hood...
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