It's here! The culmination of our series on agents, and if you've ever wondered how to make the most of the AI agents in your business (without a huge budget or a team of developers), this is the episode for you.

This week on Early Adoptr, we are joined by Rob Webster, who has spent 25 years working at the intersection of data, machine learning, and marketing, including working on data and technology for brands like Dell, Tesco, and Coca-Cola. He now runs Tau Marketing Solutions, where he helps businesses adopt AI and build agents to solve real marketing problems. In this episode he joins Jess and Kyle and shares everything he has learned about making agents that actually work. From the "Fisher Price Agent" to building a daily action plan, the four components every working agent needs and why most agents fail, this episode is a goldmine of tips from years of experience.

We also cover a major deal between SpaceX and Cursor, and what it tells us about where the real competition in AI is playing out right now.

What You'll Learn

The two-prompt method Rob uses to turn a vague goal into a concrete daily action plan
The four components every working agent needs and the reason most agent setups fail to produce useful output
Why the most valuable skill in AI right now has nothing to do with technology, and how anyone can develop it
What human-in-the-loop looks like as a working habit rather than a safety concept
How to start with a "Fisher Price Agent"
Rob's tips for getting unstuck when you hit a wall

Timestamps:

00:00 What We've Been Up to This Week

03:16 Interview with Robert Webster

05:07 AI News: SpaceX and Cursor Deal

05:47 Meet Rob Webster

10:51 The Two-Prompt Method: Going from Vague Goal to Concrete Plan

13:28 The Four Components Every Working Agent Needs

18:14 Why Knowing What Good Looks Like Is the Real Skill

20:26 Human-in-the-Loop in Practice

26:20 Building a Co-CEO Agent: From Fisher Price to Advanced

33:01 Where to Start If You Are Not Technical

37:42 Takeaways

Stop Building AI Agents the Hard Way: Lessons from 25 Years in AI (w/ Rob Webster)