Why syllagent?

The name combines “syllabus” and “agent” — two ideas I think about constantly. On one hand, there’s the structured craft of teaching: curriculum design, scaffolding, building a learning path. On the other, there’s the emerging world of AI agents and large language models that are transforming how we think about knowledge work.

What to expect

This blog will cover:

• Teaching with AI — practical experiments and reflections
• AI Agents — how they work, where they’re going
• LLMs & Education — research, essays, and hot takes
• Building things — coding, tools, and prototypes

The site itself is styled after classic Final Fantasy RPG interfaces — because learning should feel like an adventure, not a chore.

Example Code Block

Here’s a quick Python example showing how you might call an LLM API:

import openai

def ask_llm(prompt: str, model: str = "gpt-4") -> str:
    """Send a prompt to an LLM and get a response."""
    response = openai.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": prompt}]
    )
    return response.choices[0].message.content

# Example usage
response = ask_llm("What is an AI agent?")
print(response)

And here’s some JavaScript for good measure:

// A simple async function to fetch data
async function fetchPosts() {
  const response = await fetch('/api/posts');
  const data = await response.json();
  return data.filter(post => post.published);
}

Stay tuned for more posts soon.