Tag: llm
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Agent Memory – Copilot Studio
LLMs are stateless by nature. Yet our agents in Copilot Studio remember. How does it really work, and what does it mean in practice when we build enterprise solutions? Let’s start with a technical fact that is often taken for granted: every time a large language model receives a message, it remembers nothing. It does…
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Context engineering vs Prompt engineering
For years we have called “prompt engineering” the ability to get better results from language models by choosing the right words. Today, however, real applications (enterprise copilots, agents, RAG, multi-step workflows) reveal a clear limitation: it’s not enough to phrase the request well if the model doesn’t “see” the right information. This is where context…
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The AI Bible of Models
How intelligent is artificial intelligence? The quantity of AI models has truly exploded, and the question I asked myself is: “How can I measure how intelligent artificial intelligence really is?” In the ever-evolving world of artificial intelligence, choosing the right model can make the difference between the success and failure of a project. Today, we’ll…
