In this episode, I show how I actually use ChatGPT to run my business: settings, models, custom GPTs, and Projects.

Then we do a live demo: I ask ChatGPT to write the prompt, and we generate an ad image from 2 photos.

ChatGPT updates constantly. New models, new features, new hype cycles.

But the real advantage isn’t the latest update — it’s how you use the tool.

In this episode, I walk you through my real ChatGPT workflow:

• Free vs Plus plan (and why I use Plus)
• The settings that matter (personalization + memory)
• Model selection (thinking vs instant)
• Uploading files/images for better context
• Custom GPTs (shareable) vs Projects (internal)
• How I build a business GPT (Customer Avatar Finder)
• My favorite trick: ask ChatGPT to write the prompt
• Live demo: combine two photos into a photorealistic ad image

Sponsored by:

• Grata Software — custom AI + automation for small businesses
• Digital Strike — DIY training for AI + automation

Comment what you want me to show next:
Lead gen, sales follow-up, customer avatars, offers, or automations.

00:00 We’re finally using tools (ChatGPT)
01:10 AI hype cycles & why strategy matters
04:37 ChatGPT plans: Free vs Plus
06:58 Personalization settings
09:27 Why I keep Memory OFF
11:47 Data controls + privacy reality
14:11 Protecting data (local models)
15:00 Models: thinking vs instant + training dates
16:33 RAG explained in plain English
18:56 Files, context windows, and uploads
21:13 Agent mode warning
23:35 Sidebar: chats, images, apps, codex
25:51 Custom GPTs vs Projects
30:25 Why ChatGPT changed business research forever
32:42 Building a Custom GPT (Avatar Finder)
35:06 Knowledge base “secret sauce”
37:29 Projects example (travel budget)
39:53 Ask AI to write the prompt (pro move)
44:25 Live image generation results
46:44 CTA + next episode

#ChatGPT #AI #Automation #SmallBusiness #Marketing

Most people don’t understand how AI actually works — and that’s okay.

In this episode, I explain Large Language Models using a simple story anyone can understand.

Neural networks, transformers, hallucinations, and RAG are usually explained with math, code, and diagrams that look like spider webs.

So I did something different.

In this bonus episode of the AI Automation Alchemist podcast, I use a simple story — a flat tire and a cocktail party — to explain:

• How Large Language Models actually work
• What input layers and hidden nodes really do
• Why AI hallucinates
• How transformers keep context intact
• How Retrieval Augmented Generation (RAG) injects facts
• Why AI feels intelligent without “thinking”

No code. No math. No hype.

If you’ve ever nodded along pretending to understand neural networks — this episode is for you.

Sponsored by:

• Grata Software — custom AI & automation
• Digital Strike Hub — learn AI the right way

#ChatGPT #LLM #ArtificialIntelligence #AIExplained #Automation

ChatGPT isn’t thinking — it’s calculating probabilities.
In this episode, I explain how Large Language Models actually work, in plain English.

Most people use ChatGPT daily without understanding what it’s actually doing.

In this episode of the AI Automation Alchemist podcast, I break down:

• What Large Language Models (LLMs) are
• How neural networks work (simplified)
• What transformers actually do
• Why context matters more than prompts
• Why AI feels intelligent without “thinking”

This is not hype, not marketing, and not theory — it’s a practical explanation for business owners and builders who want to use AI correctly.

00:00 What this episode covers
00:45 Why I used Notebook LM
02:10 What a Large Language Model is
03:15 Neural networks (simplified)
04:40 Hidden nodes & parallel processing
06:00 Transformers & context
07:40 Why words mean different things
09:00 Why AI feels intelligent
10:15 The simplified explanation epiphany

Resources & Links:

• Notebook LM
• Grata Software
• Digital Strike

Connect with Rey Ortega:

• LinkedIn
• X/Twitter
  

#ChatGPT #LLM #ArtificialIntelligence #AIExplained #Automation

Next week we go tactical: AI tools that help you find customers, target them, message them, and convert them.

This week we talked about AI hype, conferences, and the wild claims people make about “AI expertise.”
Now we’re moving forward.

Next week’s episodes focus on tactical AI tools for business owners, especially:

• How to identify the right customers (demographics + psychographics)
• How to craft an offer that speaks to them
• How to message them on social and email
• What tools to use (and which are a waste)
• How to control tool costs and ensure 10x ROI

Sponsored by:

• Grata Software — custom AI + automation for small businesses
• Digital Strike — DIY training community for AI + automation

Drop a comment with the #1 thing you want AI to help you with:

Lead gen, sales, content, ops, or customer support.

00:00 This week recap: AI hype + misinformation
01:10 Disclaimer: marketers still help beginners
02:20 Sponsors: Grata Software + Digital Strike
03:00 Next week: tactical AI tools for business growth
04:10 Customer acquisition: who to target + why
05:10 Tool cost problem + how to think ROI
06:10 The 30-day podcast challenge + why I’m doing this
07:10 What topics do you want next?

#AI #Automation #SmallBusiness #Marketing #CustomerAcquisition

Using AI tools doesn’t make you an AI expert — and pretending it does is hurting businesses.

In this episode, I explain the difference between tool users and real AI expertise.

I’m recording this episode from an indie game jam where I’m mentoring engineers, and it perfectly highlights a growing problem in the AI industry.

Too many people — especially marketers — are calling themselves “AI experts” after learning a handful of tools or getting certified. Using tools does not equal expertise.

In this episode, I break down:

• Why AI tools don’t give you “god-like skills”
• The difference between tool users and experts
• Why AI certifications don’t impress real companies
• Why Siemens, GE, and enterprise clients only care about experience
• Who AI tools are actually for (and why that’s still valuable)
• How bad AI advice is costing companies millions

If you want to learn AI properly, check out Digital Strike.
If you want AI done for you, contact Grata Software.

The conversation delves into the misconceptions surrounding AI and automation, particularly focusing on the Chat GPT technology. It addresses the false notion of 'genius mode' and the reality of how the technology functions. Additionally, it explores the Chat GPT ecosystem and its various components.

Takeaways

• AI and Automation Misconceptions
• Understanding Chat GPT Ecosystem

Chapters

• 00:00 Introduction to AI and Automation Misconceptions

Most AI implementations fail because people start with tools (the 10%) instead of culture (70%) and process (20%).

In this episode, I break down the 70/20/10 rule for AI and how to use it to actually implement automation.

In this episode you’ll learn:

• What the 70/20/10 rule is (and where it came from)
• Why “AI consultants” often teach tools with no purpose
• The #1 problem: you can’t automate what doesn’t exist
• How to implement AI the right way:
  • 70% = culture + buy-in + skills
  • 20% = SOPs + workflows + integration
  • 10% = models, tools, algorithms, automation build

If you want our AI + Automation implementation guide, comment: NEED A PLAN.

Sponsored by:

• Grata Software (custom AI + automation)
• Digital Strike Hub (training + community)

#AI #Automation #BusinessSystems #SOP #AIImplementation

00:00 The 70/20/10 rule for AI
00:30 What the framework is (70 core / 20 related / 10 new)
01:26 Why most AI consultants miss it
02:50 Client story: “Where’s your list?”
04:19 You can’t automate what isn’t there
05:40 Secret #1: 70% is buy-in + culture
07:07 Secret #2: 20% is SOPs + integration
09:27 Secret #3: 10% is the tech
11:47 Recap + how to apply it
12:46 Comment “NEED A PLAN”

Someone told a room full of people: ‘I know AI like nobody else… I started in 2022.’ That’s when I knew we had a problem.

AI was everywhere at the conferences I attended — especially PodFest — and a lot of it was oversold.
In this episode, I explain why “using AI tools” ≠ being an “AI expert,” and I highlight **3 presenters who did it the right way.

You’ll learn:

• Why “AI expert since 2022” is a red flag (and what real expertise looks like)
• The 10,000-hour rule as a reality check for skill claims
• 3 great presentations and what made them credible:
  • Dr. Catrice Austin (Celebrity Branding USA) — PR + AI used responsibly
  • Jennifer Navarrete — podcasting experience + practical AI use
  • Chad Parazan (Ader Communications) — prompts + workflows for podcast automation
• How to use AI for podcast prep, editing, trailers, and clips the smart way

👋 I’m Rey Ortega, a 26-year software engineer & automation builder (250+ business applications).

Sponsored by: Grata Software + Digital Strike

✅ Links mentioned in this episode (add yours here):

• Grata Software
• Digital Strike Hub
• Celebrity Branding USA
• Brew Media / Jennifer Navarrete
• Ader Communications / podfest prompts

#ai #automation #podcasting #chatgpt #businessautomation

00:00 AI wasn’t supposed to be the topic… but it was
01:05 The conference “AI hook” problem
06:55 “AI expert since 2022” (the credibility issue)
07:35 The 10,000-hour rule reality check
10:45 AI isn’t new (since the 60s) + what “real AI” is
13:30 Presenter #1: Dr. Catrice Austin (PR + AI done right)
16:55 Presenter #2: Jennifer Navarrete (podcasting truth + volume)
27:50 Presenter #3: Chad Parazan (prompts + full podcast automation)
33:25 Wrap-up: the standard going forward