Llm

I’ve been doing “agentic coding” for some time, and well, it’s weird. On stable, mature technology (in my case, the C#/.NET stack), it is beneficial, as it significantly boosts productivity. But, there’s a bit, and that’s that I’m not programming anymore, or very little now, and I love coding. I love entering “the zone” and solving complex problems, one at a time. It’s always been my superpower. Will I still have fun in the future now that I can delegate most tasks to Claude Code? ...

I’ve been implementing a remote MCP Server. It comes with a hybrid authentication system that supports the OAuth2 flow and, as a fallback, a custom header for those simple clients that cannot handle OAuth. One such client is Claude Desktop, which, at this time, is even worse; it only supports STDIO (local) servers, let alone OAuth2. Today I learned about a nice NPM package called MCP Remote, which bridges the gap by allowing MCP clients that only support local servers to connect to remote MCP Servers, even with authentication support. Thanks to this tool, Claude Desktop is now talking to my remote server1. ...

Quoting straight from Jim Nielsen’s note on LLM training on copyrighted data: As a broke teenager, the web was this strange wonderland where you could access all kinds of copyrighted material using tools developed by fringe individuals/communities: Napster, Kazaa, Torrents, Usenet, etc. These tools (at least in the beginning) weren’t really made for profit, just to subvert the gatekeepers (and yeah, steal their profits). Now — in a strange twist of irony — things seem to have flipped: ...

Armin Ronacher is on a roll. He just published his Agentic Coding Reccomendations. On the topic of Agenting Coding he recently published: AI Changes Everything (you should read it) GenAI Criticism and Moral Quandaries Both already reported.

Last night, I presented a session titled MCP or Connecting our Apps to LLMs at DevRomagna, our local developer’s community, and I think it went well. I had intended to record the audio with the idea of transcribing it with MacWhisper and then publishing it here on my site, but I forgot to do so, which is a pity. The session lasted almost two hours (I had thought it would take less time), during which I deviated somewhat from the script, using slides as a guide that were essentially an adaptation of the notes I had taken during my experiments. I showed the code for the MCP servers I created (stdio and streamable HTTP transports), demonstrated the various ways to link them with LLMs (Claude Desktop, Claude Code, and VS Code), and then shared my thoughts on the entire matter. ...

In the 2030s, intelligence and energy—ideas, and the ability to make ideas happen—are going to become wildly abundant. These two have been the fundamental limiters on human progress for a long time; with abundant intelligence and energy (and good governance), we can theoretically have anything else. – Sam Altman

Despite what tech CEOs might say, large language models are not smart in any recognizably human sense of the word.

Since yesterday, Claude Code has been included in the Pro subscription we’re signed up for. I’d been wanting to try it for a while, and now nothing was stopping me. Only yesterday (a curious coincidence), I read AI Changes Everything by Armin Ronacher, which gave me a glimpse of the potential and made my hands itch to try it. The initialization of Claude on the repository surprised me; the analysis (reported in CLAUDE.md) is thorough and reveals a good understanding of the project, including both the code and the general functioning, strategies, techniques, technologies and libraries employed. ...

Today’s Armin Ronacher’s AI Changes Everything strongly resonates with me1. I may not be using Claude Code as a daily driver as he now does, but I’ve slowly and steadily introduced large language models (LLMs) into my routine, and I’m reaping the benefits. It wasn’t the purpose of his article, but I wish Armin had gone into the details of how, why, and when he delegates tasks to Claude Code. Update: Armin later a follow-up. ...

Run Your Own AI by Anthony Lewis is a concise tutorial on how to run large language models on your laptop from the command line via llm-mlx. It focuses on Macs M-series, but it’s also suitable for other hardware. Saving it here for a friend.