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AI Agents for Beginners

How to Get Your Systems in Order, Deploy Your First Reliable Agent, & Automate Your Business (AI for Business, Strategy, & Leadership)

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AI Agents for Beginners

By: Austin Chen
Narrated by: Jay Ball
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About this listen

You open your CRM and find three versions of the same client. Your file system has a folder called "Final FINAL v3." Your spreadsheet has columns that no one on your team can explain — including the person who made them.

And somewhere in the back of your mind, a voice is saying: I should probably be using AI by now.

Here is what that voice isn't telling you: so should everyone else. And almost no one's business is ready for it.

Not because the technology is too advanced. Because the foundation underneath it — the data, the files, the processes — is held together with habit, memory, and manual effort. And every AI resource on the shelf skips straight past that mess to the shiny part. They hand you the agent. They never mention the infrastructure underneath it. And when it breaks — when the chatbot hallucinates, the automation fires into an uncleaned list, the API bill triples — you blame yourself.

You were not the problem. The sequence was.

AI Agents for Beginners starts where you actually are — with the mess — and shows you how to turn it into something an AI agent can work with.

The Foundation-First Method is a five-phase system built for the non-technical business operator who wants AI agents working in his business but knows his infrastructure is not ready. Instead of jumping to tools, platforms, and prompt engineering, it walks you through the preparation that makes agents reliable:

The Data Floor — the minimum viable standard of organization your business needs before any AI agent can operate reliably, scoped narrowly to your first task so you are not reorganizing your entire company before you can deploy anything

The Task Filter — a four-criteria decision framework that identifies the single safest, highest-confidence task to automate first, based on data readiness, repetitiveness, error tolerance, and business impact — so you stop asking "what should I do first?" and start with the task that is practically engineered to succeed

©2026 Blackstone Publications (P)2026 Blackstone Publications
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