Murat Buffalo's blog provides insights into computer science research, machine learning, and artificial intelligence. Readers can explore articles covering topics such as algorithm design, data mining, and computational biology. Additionally, they can learn about machine learning algorithms, deep learning techniques, and applications of AI in various domains.

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A review of the December 2025 paper 'Measuring Agents in Production' (MAP), which surveyed 306 practitioners and 20 in-depth case studies across 26 domains. Key findings: 80% of production agent systems use predefined structured workflows rather than autonomous planning, 68% require human intervention within 10 steps, 70% rely on prompting off-the-shelf models rather than fine-tuning, 85% of teams build custom infrastructure instead of using frameworks like LangChain, and 75% skip formal benchmarking. The author draws a parallel to blockchain hype circa 2018, but concedes AI agents differ in that they do deliver real value—just in a far more basic, constrained, and human-supervised form than the hype suggests.