Recently, there’s been a lot of talk about the Model Context Protocol. I started looking into some practical examples of how it’s used and came across a video that really helped clarify things for me. It was a simple example, but it opened up my understanding of how to apply the protocol effectively. Hopefully, it’s useful for you as well. I’m looking forward to implementing something similar myself. It should also help deepen my understanding of how to use these tools more practically—especially for projects that can’t be exposed to the internet but still want to take advantage of LLMs.

I recently watched an interesting interview with John Ousterhout, the author of A Philosophy of Software Design The interview begins by exploring how AI tools are evolving and their potential to transform software engineering. One key takeaway is that AI will likely take over many low-level coding tasks. As a result, the importance of software design is only going to grow. What really stood out to me was Ousterhout’s point that as AI handles more of the implementation details, the responsibility for designing clear, scalable, and maintainable systems will become even more critical for developers.

Andrej Karpathy’s video continues his series on large language models (LLMs), shifting from foundational theory to hands-on usage. Below is a timestamped summary of the key points covered. Introduction (0:00–0:34) Karpathy introduces the video as a follow-up to his prior explanation of how LLMs are trained. This session focuses on how to actually use LLMs in daily life and work. LLM Ecosystem (0:34–2:49) He overviews the current LLM landscape: ChatGPT by OpenAI is described as the “Original Gangster” and most feature-rich.