Post by Julian Gilson

I’m excited to kick off Build an Agent With Me, my series of posts showing you a hands-on approach into how to build AI agents that think, decide, and act. This is a step beyond our usual uses of Gen AI, which consists mostly of running one-off prompts. 🎯 What makes an agent an agent? An AI agent takes information as input, reasons, makes a decision, and then takes an action, whether that’s amending every relevant clause in a document for updates to a new regulation or scheduling your team’s weekly sync. 🔍 Teaching an agent to reason Reasoning is what allows an agent to make decisions instead of just reacting. It’s the ability to evaluate inputs, consider different options, and choose what to do next based on its current goal. ⚙️ The project flow In this series, we’ll be following a simple, repeatable process to bring the agent to life: • Set up logic: Define how the agent should reason through tasks and make decisions. • Test logic: Run sample inputs to make sure the reasoning works as expected. • Set up with add-in: Connect the logic to a real-world interface (like a Word or browser extension) where users interact with it. • Repeat: Refine and extend the logic with each iteration. 🚀 What’s ahead Next, we’ll dive into crafting reasoning modules and writing chain-of-thought prompts that power the agent’s brain. What’s one decision you’d want your AI agent to handle for you automatically? Drop your thoughts below — I’ll use your input to shape future posts! P.S. For this project, I’ll be using Airia - Enterprise AI Simplified — a powerful low-code platform for building, testing, and deploying AI agents with real-world integrations. But the lessons here will apply no matter what tools you use.