Part 2 of Two Roads to AI Agents. This time we apply the framework to something real. In Part 1, we drew the line between Agent SDKs (code orchestration) and Agent Skills (markdown knowledge). Now let’s see where that line falls in practice. We’ll walk through a pipeline that turns any article into a narrated MP4 — and at each step, I’ll label whether it belongs in SDK code or Skill knowledge, and why. ...
I wanted a way to turn my blog posts into narrated videos without spending hours in video editors. What I ended up building was a full pipeline: give it an article, a URL, or a PowerPoint file — get back a 1080p MP4 with animated slides, syntax-highlighted code blocks, and an AI voiceover in any language. The whole thing is open source: github.com/nmnhut-it/educational-video-pipeline. This post walks through how it works and how you can build your own. ...
LLMs Don’t Actually “Call” Tools Here is a fact that surprises most people: LLMs cannot run code. They cannot call APIs. They cannot read files. All they do is predict the next token — they output raw text, one piece at a time. So how do they “use tools”? The trick: structured wishes During training, models are fine-tuned on augmented datasets that include tool call examples. The training pipeline works roughly like this: ...
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