Why is OpenAI running 26 ads at once, and why did one of us score them just 2 out of 30? Learn how to use the Meta Ad Library to run a free competitor ad analysis in 10 minutes. In this episode of May Contain Jab, Jab and May tear down OpenAI's ChatGPT Business ads and score them on scroll-stopping power, shareability and emotion.

If you're a small business owner or founder running paid ads, you'll see exactly how to find any competitor's Meta ads, spot what's working, and audit your own ad creative honestly. No big budget, no agency, no expensive tools.

In this episode:

• How to use the Meta Ad Library to see every ad a competitor is running

• Why creative volume matters in Meta ads (OpenAI is running 26 at once)

• A teardown of a simple static ad in customer quote format

• A teardown of a 15-second video ad: production quality vs. emotional payoff

• Why every ad needs a story, a payoff and a transformation

• Why people don't have short attention spans, only a shortage of entertainment

• How UGC (user-generated content) and nostalgia can fix a high-production ad

• How to rebuild a video ad so the value lands in the first 3 to 5 seconds

The Impact Score: a simple ad scoring framework you can use on your own ads

1. Scroll-stopping power (the first 3 seconds)

2. Shareability (would someone send this to a friend?)

3. Emotional impact (joy, excitement, nostalgia, curiosity)

Score each out of 10, then total out of 30.

Your turn: comment with your scroll-stopping, shareability and emotion scores for an ad you've seen recently. We'd love to see how you score it.

Want us to tear down your Meta ads, automation or website? Email mayandjab@maycontainjab.com or connect with us on LinkedIn.

About May Contain Jab

May Contain Jab is a podcast for small business owners and founders who don't have time to test every new tool and technology. Practical AI strategy, automation and marketing teardowns, minus the hype. Subscribe so you don't miss the next episode.

Chapters

00:00 Welcome and what we're covering

00:51 How to use the Meta Ad Library

01:40 Why OpenAI is running 26 ads

02:30 Teardown 1: the simple quote ad

06:46 Teardown 2: the 15-second video ad

09:08 Why every ad needs a payoff

11:07 Do people really have

May's been cooking in the AI lab. In this episode of May Contain Jab: The Owner's Edge, Jab and May whiteboard what it's really like building with Fable: stronger reasoning and fewer breakages, but new guardrails, privacy blocks and serious credit costs. May shares her trick for getting round the constant drops to Opus. Then they break down LLM Wikis and RAG in plain English: how a small business can turn years of SOPs, transcripts and processes into a searchable "business brain".

"It's not the tool, it's what you do with it." May

In this episode:

• Why the specific AI tool matters less than what you do with it

• Fable's strengths: better reasoning, fewer breakages, smoother website builds (Vercel, Sanity, Formspree)

• The new guardrails: privacy blocks and constant drops to Opus

• May's workaround: Opus on ultra mode with Fable sub-agents, and why you can't fully audit what sub-agents do

• Fable's suspension and return, and whether restrictions are slowing the builders down

• Why Fable is so credit-intensive

• LLM Wikis explained: raw files in, a personal Wikipedia out, viewed in Obsidian

• RAG (retrieval augmented generation) explained: chunking, embeddings and finding the right file fast

• Practical uses for growing businesses: SOPs, onboarding, support knowledge bases and content processes

• Live demo of May's LLM Wiki and its knowledge graph

CHAPTERS

00:00 Welcome: vibe coding with Fable

02:30 It's not the tool, it's what you do with it

03:09 Whiteboard: the race, Fable vs Codex

03:50 Fable's strengths: reasoning and building websites

05:31 Does Fable live up to the hype? Guardrails and privacy

06:54 The trick: Opus ultra mode + Fable sub-agents

08:47 Before vs after the ban

09:07 Why Fable was restricted

09:48 Is the government killing the vibe?

11:08 Let us party: the Google AdWords lesson

12:29 Credit-intensive: the cost of Fable

13:44 What is an LLM Wiki?

15:44 RAG explained: retrieval augmented generation

17:00 "Detective May AI": searching your business files

19:22 LLM Wiki vs RAG: two structures

20:54 Demo: May's LLM Wiki in Obsidian

22:13 Why owners need this: SOPs, onboarding and process

25:43 How to get in touch

27:27 Codex and ChatGPT: coming next episode

28:08 Recap

CONNECT

Website: https://maycontainjab.com

Email: mayandjab@maycontainjab.com

May Zhan (AI automation and strategy): https://linkedin.com/in/may-zhan

Jab Siwela (audience, resonance and revenue): https://linkedin.com/in/jab-siwela

Subscribe for weekly episodes that give small business owners and founders the owner's edge on marketing, AI and automation.

#MayContainJab #TheOwnersEdge #AIAutomation #VibeCoding #LLMWiki #SmallBusiness #Founders

Most businesses are using AI to make more content. Very few are using it to make better content.

In this episode of May Contain Jab: The Owner's Edge, Jab (marketing and audience strategy) and May (AI automation and systems) break down where content actually starts, why AI slop happens, and how to build a content system that scales without losing the human connection that makes people buy.

"If you have garbage in, then it's garbage out." May

"How do you want the person to feel at the end of that interaction? That will be your North Star." Jab

In this episode:

• Why every piece of content starts with a customer problem, not a product

• The inputs and processes behind AI content that doesn't sound generic

• How to tie content to revenue when buyers need 12 to 15 touch points

• Brand content vs conversion content, and the split we'd actually use

• A step-by-step automated content stack using n8n, Claude and Gamma

• Why human flaws will be the edge in a world of polished AI video

• The storytelling framework that turns a product into something people talk about

• The mistake founders find hardest to fix on their own

LISTENER CHALLENGE

Pick your last three posts. Read each one as your customer. Then ask the question Jab ends on: how should they feel at the end? If you can't answer it, that's your first fix.

CHAPTERS

00:00 Intro

00:35 Where content actually starts

01:49 Garbage in, garbage out: inputs and process

03:07 Where AI saves the most time

04:04 The risk of AI-generated content

06:25 Can you tie content to revenue?

08:04 Brand content vs conversion content

10:40 70/30 or 30/70? Organic vs paid

12:48 Measuring ROI when attribution is messy

14:37 How automation changes the ROI equation

17:04 What an automated content stack looks like

19:40 Automating presentations with Gamma

23:25 The AI tools for video, images and text

23:51 AI influencers and why human flaws win

27:48 The power of storytelling

29:36 The hidden cost: same content on every channel

31:04 The biggest mistake wellness brands make

32:12 The mistake founders struggle to fix

36:06 Rapid-fire hot takes

41:05 The AI content automation impressing May right now

42:24 Fix your content this week

45:10 The lean content system for a team of 1 to 3

45:59 Working with May and Jab

47:18 Final thoughts

CONNECT

Website: https://maycontainjab.com

Email: mayandjab@maycontainjab.com

May Zhan (AI automation and strategy): https://linkedin.com/in/may-zhan

Jab Siwela (audience, resonance and revenue): https://linkedin.com/in/jab-siwela

Subscribe for weekly episodes that give small business owners and founders the owner's edge on marketing, AI and automation.

#MayContainJab #TheOwnersEdge #ContentStrategy #AIAutomation #ContentMarketing #SmallBusiness #Founders