Agents demystified

Don't you hate it when someone tries to make you feel stupid by wrapping a simple concept in layers of manufactured complexity?

Case in point these days: AI Agents. Oh, Large Language Models (LLMs) are so 2024. But 2025 is the year of agents. Agentic AI this, Agentic AI that. You better sign up for all these Gartner webinars or, better yet, pay a million bucks to Accenture to build you a custom proof-of-concept project (true story). Don't miss out, or they'll be coming for you and your business!

Here, I lay out the simple logical steps that take you from an LLM to an Agent:

Step 0: The LLM as a chat bot

That's the ChatGPT and co we all know. We type in our query and get an answer back.

Step 1: Integration: Calling the LLM from another program

My to-do app has a feature that takes a large task and uses generative AI to break it down into smaller steps. Behind the scenes, the to-do app just posts a well-crafted question to the LLM and uses the answer to provide that functionality.

Step 2: Workflows

Like step 1, but with more complexity in the control logic, and with more than one call to the LLM involved. Includes examples like:

• Using one call to an LLM with one set of instructions to create some output and using another call with another set of instructions to critique or improve that output

• Posing the same question to multiple LLMs, then aggregating their responses

• Asking one LLM to break down a larger query into multiple steps, then feeding those steps to specialist LLMs

Step 3: Agents

In the previous step, we hard-coded the control logic. In this step, we hand the reins over to the LLM. In addition, we provide access to tools:

• An extra layer around the LLM checks its output for special commands where the LLM says that it wants to do something, like search the web, check something in your database, or run some code.

• Part of the prompt involves telling the LLM what tools it has access to and how it should invoke them.

• Then you just let it do its thing.

And that's the whole secret. Let's end with a quote from the excellent article by Anthropic on Building effective agents, because it fits so well with our general theme of simplicity:

Consistently, the most successful implementations weren't using complex frameworks or specialized libraries. Instead, they were building with simple, composable patterns.