What's the Deal with Agents?

Andrew Ng gave a talk about AI agents at Sequoia Capital . Andrew talked about how "The Future is Agentic". What the heck is "Agentic"?? I can't wait to be so rich I can just make up words.

Despite the phonetic tom-foolery, Andrew makes great points in his talk. Let's break down what AI agents are, and why they are cool.

An agent is pretty much ChatGPT, but custom-built for you. Agents can use tools to do things that LLMs can't do. Like send emails to potential clients, generate exceptional code; basically run your company for you. I like to think of agents as your own personal over-caffeinated intern, except this intern never sleeps, eats, or gets wasted going to see Lana del Ray at Coachella (what a talent).

Here's how it works (In this part of the show, I'll be leaning heavily on the Nvidia's excellent post about agents):

• An AI agent is just an LLM with a few minor tweaks. Here are the tweaks:
• Software engineers prompt the LLM so that it learns to operate in a "world class". The agent's "world" consists of tools it can use (APIs, databases, other agents, etc)
• The agent takes the user's input and uses its LLM to break the prompt down into sub-tasks

• The agent takes stock of the resources it has access to, then tries to accomplish each sub task by delegating tasks to other agents or tools it has access to

For example, if a user asks why their girlfriend broke up with them, a plain-old LLM would deterministically spit out a answer that sounds like something from the r/relationships subreddit. An agent with access to the user's journal on Notion will instead use this data to point out specific behaviours that make them repellant to the female species. Now that's science!

One other cool feature of AI agents is that they can talk with each other. Andrew Ng gave the example of one agent that was prompted to write code, and another that was prompted to review code. You can then setup a system where the coder agent sends the code to be reviewed by the reviewer agent, and they go back and forth, iteratively improving the quality of the code:

To close, an LLM is like a super smart stranger, AI agents have the potential to be your super smart co-worker who has access to all the resources you do, and can do all the little annoying tasks that keep you from doing the thing you were meant to do: read Calvin & Hobbes for a living.

I just did the Google Vertex AI hackathon, where I built my very own AI agent from scratch. Stay tuned for another riveting article outlining step by step details on how to make your own AI buddy that does your job for you.

Pip pip,

Gabe