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LLM ≠ Agent

What actually turns a model into an agent.

Saai Syvendra · · CSE, University of Moratuwa

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People use "LLM", "agent" and "harness" as if they mean the same thing. They don't. In this two-hour session we build one assistant, Campus Buddy, one piece at a time, and watch it go from a model that forgets your name to an agent that plans your week and writes the plan to a file.

An agent is an LLM, plus state, plus tools, running in a loop.

Before the session

Do this at home, not in the hall. The venue Wi-Fi will thank you.

  1. Install Node.js 24 LTS (22 or later works).
  2. Get a free Gemini API key from Google AI Studio. Sign in with a Google account. No card needed.
  3. Clone the repo and install:
git clone https://github.com/saai-syvendra/llm-is-not-an-agent.git
cd llm-is-not-an-agent
npm install
  1. Copy .env.example to .env and paste your key after GEMINI_API_KEY=.
  2. Run the setup check. If it ends with 🎉, you're ready.
npm run doctor

If doctor fails, send me the error before the session and we'll sort it out.

What we build

  1. LLM. A raw call to Gemini. Tell it your name, ask again, and it has no idea. A very smart function that forgets you instantly.
  2. Chatbot. Keep a list of messages and send the whole list every time. Now it remembers, because you remember for it.
  3. Agent. Give it a getWeather tool and write the loop yourself: run the tool it asks for, hand back the result, ask again, and stop when it stops asking.
  4. createAgent. The same agent in about ten lines, with a checkpointer for memory. You write a tool of your own.
  5. Harness. Deep Agents wraps that loop with a to-do list, a file system, skills and long-term memory. Ask it to plan your week before the mid-sem and it writes plan.md.

Steps 1, 2 and 5 are demos you can run along with. Steps 3 and 4 are yours to code.

Take-home challenge

  1. Give Campus Buddy a tool that matters to you: bus times from Katubedda, the canteen menu, your real timetable.
  2. Write a skill for something you know well, like how to prepare for one module's exam.
  3. Ask it to do a task that needs both, and watch which tool and which skill it reaches for.

Where to go next

  • The LangChain JS docs for agents, and Deep Agents for the harness.
  • Put a real UI on Campus Buddy instead of the terminal.
  • Read how coding agents like Claude Code and Cursor work. They run the same loop you wrote in step 3.
#Workshop#AI Agents#TypeScript#LangChain