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

AI and automation strategist May Zhan built her own YouTube research tool with Claude Code. Only after building it did she find out vidIQ already existed. So May and Jab put them side by side.

Most owners research content the same way. Open YouTube, type a keyword, and end up ninety tabs deep with nothing written down. In this episode of May Contain Jab: The Owner's Edge, May and Jab show a better way to find out what your audience actually wants to watch.

In this episode, they explain:

◼️ Why the best content ideas are sitting in someone else's comment section ◼️ The tool May built that scans 14 days of YouTube trends in AI and marketing ◼️ Why trending content dies fast, and evergreen content pays out for years ◼️ How to find the gap instead of fighting the biggest channel for the same spot ◼️ What vidIQ shows you, live, and where a homemade tool could beat it ◼️ The one word in a title that beat its channel's average by 60x ◼️ Why an automation specialist tells you to do it by hand first

Chapters:
00:00 Intro
00:36 The Problem: Finding What To Post Without Endless Scrolling
01:58 Inside The Tool May Built With Claude Code 02:30 The AI Analyst That Suggests Your Next Video
04:46 Trending vs Evergreen: Which Content Lasts?
07:27 How Much Research Time Does AI Save?
08:11 From 50 Pound Textbooks To AI Research
12:34 Reading The Comments: Where The Real Ideas Live
14:24 Spotting The Gap Nobody Has Filled
15:56 Don't Compete. Fill What's Missing.
17:24 vidIQ Live Demo: Is It Worth It? 19:28 Outlier Videos: What 58x Performance Looks Like
21:22 The One Word That Makes People Click
24:40 Thumbnails That Tell A Whole Story 25:54 Start With The Process, Then Automate

Your Challenge: Before you automate your content research, do it by hand once. Pick one topic your customers care about. Search it on YouTube, open the top five videos and write down every question in the comments. That list is your next three pieces of content, and it shows you exactly which step is worth automating.

Want us to make a full episode on building AI apps for small business?

Get in touch: Email: mayandjab@maycontainjab.com Website: maycontainjab.com May Zhan on LinkedIn: linkedin.com/in/may-zhan Jab Siwela on LinkedIn: linkedin.com/in/jab-siwela

If you found this useful, follow the show and share it with an owner who's stuck on what to post.

You no longer need to know C++ to build software. You need to know what you want.

In this episode of May Contain Jab: The Owner's Edge, May and Jab dig into vibe coding: describing an app in plain English and letting AI build it. Tools like Lovable, Replit, Cursor and Claude Code have turned weeks of developer time into an afternoon. But is it really that easy, or is it just hype?

May shares what she has built herself, from a client portal to a lightweight to-do app and her own CRM. Jab demos two vibe coded lead magnets live on the show: a marketing "time machine" that shows the cost of doing nothing, and a swipe-style app that asks what it would be like to date yourself based on your lifestyle habits.

They also get honest about the risks. Security. Messy code you cannot read. Credits that disappear like coins in a slot machine. And knowing when to stop building and bring in a developer.

In this episode

• What vibe coding actually is, in plain English
• Why clarity is the real skill, not code
• The simplest thing a founder can build first
• What May has built with Lovable and Claude Code
• Is it really a vibe, or just hype?
• Vibe coding vs automation tools like n8n: when to use which
• The hidden costs: credits, tokens and tool subscriptions
• Where the risks lie: security, authentication and going live
• When to bring in a real developer
• Clawbot and OpenClaw: shiny, but not all green pastures
• Is an MBA still relevant in an AI world?
• Are tech layoffs really about AI?
• Rapid fire: Canva vs Opus Clip, Perplexity vs Gemini, DIY vs consultant
• Live demos: the marketing time machine and the "date yourself" app

Timestamps (from the live edit, check against the final cut)

• 00:00 Welcome to May Contain Jab
• 00:35 What is vibe coding?
• 02:52 How vibe coding differs from ChatGPT
• 04:18 The simplest thing a founder can build
• 07:40 What May has built recently
• 09:08 Is it really a vibe?
• 10:28 Where business owners should start
• 11:28 Best marketing use cases
• 13:23 Is software cannibalising itself?
• 16:13 How to think about tool costs
• 17:54 Common mistakes and the downsides
• 21:01 When to bring in a developer
• 22:19 Clawbot and OpenClaw
• 26:10 Where vibe coding gets dangerous
• 28:57 How to cut through the hype
• 31:56 Is the MBA still relevant?
• 35:26 Tech layoffs and AI
• 39:04 Rapid fire
• 40:53 Three things May would vibe code
• 42:43 Live demo: the marketing time machine
• 45:45 Live demo: date yourself
• 51:27 The takeaway

Jab stopped buying lattes from one of the top three Starbucks in the country for app orders. It wasn't the coffee. It was the app that was meant to make everything faster. In this episode, Jab and May reveal why customer experience is the most underrated lever in your business, how one wrong step quietly costs you customers, and the simple exercise every owner should do before adding more tech.

Jab Siwela is a marketing strategist and the founder of Revalty, a growth partnership for wellness brands. May Zhan is the founder of Venture Voice, an AI and automation consultancy, and brings an MBA and deep systems expertise. Together they break down customer experience from two routes: the feeling that keeps customers coming back, and the systems that deliver it at scale.

They explain:
■ Why customer experience starts before your customer even knows they have a problem
■ How an AI chatbot nearly lost a booking by asking for too much, too soon
■ Why adding more technology can break the very experience it was meant to fix
■ What to map before you automate anything, and why automations fail on edge cases
■ How a pair of socks in the post turned one customer into a lifelong fan
■ Why a loyalty programme can't fix a broken customer experience

Your Listener Challenge
Map your customer journey from first touchpoint to after the sale. At every step, ask: is this adding to my revenue or quietly costing me it? Pick one thing to fix this quarter.

Want the customer journey map from this episode? Comment MAP on YouTube and we'll send it to you.

More at maycontainjab.com

Chapters
00:00 Cold open
00:44 Why customer experience is underrated
02:37 Defining customer experience: the feeling
05:44 The spa AI chatbot
10:24 The two-hour Amazon voucher refund
11:44 Where to start: walk the journey as a customer
13:10 Mapping awareness to advocacy
15:20 When the Starbucks app broke the experience
17:31 Marketing as a philosophy, not a function
19:21 Where automation makes customer experience better
20:46 AI chatbots versus a human in the loop
22:04 Personalisation, data and the FreeAgent socks
25:20 Best experiences and time to value
28:50 Does aesthetic matter?
31:13 Apple unboxing and the Mercedes garage
33:30 Loyalty programmes: Nectar, Godiva, Amex
38:28 One thing to change this quarter

The conversation delves into the challenges and opportunities presented by tech stacks and the ROI of automation.

It explores the evolution of tech stacks, the proliferation of tools, the need for consolidation and efficiency, the true cost of tools, automation and integration, adherence and ROI, marketing campaign costs, and automation costs and debt.

The conversation delves into the ROI of automation, the pitfalls of over-automation, the importance of maintaining and documenting automation, hot takes on tech stack audits, the concept of a minimum viable MarTech stack, and the future of AI automation with agentic workflows and AI agents.

Takeaways

• Tech stacks require careful management and consolidation for efficiency and cost-effectiveness.
• Adherence to automation tools is crucial for realizing ROI and efficiency.
• The true cost of tools goes beyond the price tag and includes training, setup time, and long-term impact.
• Automation and integration can lead to significant time savings and efficiency gains.
• Marketing campaign costs and automation costs need to be carefully evaluated for ROI and effectiveness. Understanding the ROI of automation is crucial for justifying investment
• Over-automation can lead to complexity and inefficiency
• Maintaining and documenting automation processes is essential for sustainability and scalability
• Conducting a tech stack audit and defining a minimum viable MarTech stack are key for optimizing tool usage
• The future of AI automation lies in agentic workflows and AI agents as decision-making tools

Chapters

• 00:00 Tech Stack and ROI
• 03:18 The Evolution of Tech Stack
• 05:21 The Proliferation of Tools
• 08:18 Consolidation and Efficiency
• 10:07 The True Cost of Tools
• 13:29 Automation and Integration
• 18:15 Adherence and ROI
• 36:48 Marketing Campaign Costs
• 45:05 Automation Costs and Debt
• 45:59 The ROI of Automation
• 50:07 The Pitfalls of Over-Automation
• 54:24 Maintaining and Documenting Automation
• 56:36 Hot Takes and Tech Stack Audits
• 01:11:06 Minimum Viable MarTech Stack
• 01:17:11 The Future of AI Automation

Your business doesn't need another AI tool. It needs an address. New AI tools launch every week, and every one promises an edge. In this episode of May Contain Jab: The Owner's Edge, Jab and May argue that most owners are asking the wrong question. The question isn't which tool to use. It's where the business is going. Jab explains strategy as "the address you put in the sat nav", with tactics as every turn along the way. May shows why automation only works once the strategy and the process are in place. Along the way they cover busywork, shiny object syndrome, and why AI education has to come before AI implementation. In this episode: Why strategy means choosing one direction and ruling out the others The difference between a strategy and a to-do list May's lesson from an outreach push with no clear ICP Jab's SOSTAC walkthrough, told through a dating app analogy The real automation unlock: strategy, then process, then automation Using AI as a "ruthless mentor" to stress-test your plan Amazon, eBay and low-cost 24-hour gyms: strategy beating bigger budgets What breaks first in a business with all tactics and no strategy When to stop doing everything yourself A quick-fire round: strategy or tactic? Jab's hot take on AI health and safety for teams Chapters 00:00 Cold open: Jab's dating app strategy 01:15 Welcome: strategy over tactics 02:21 Strategy is the address in the sat nav 04:22 Strategy vs a plan or to-do list 05:30 When busy isn't strategic 07:03 SOSTAC, explained through dating 09:48 The simplest strategic decision a founder can make 10:24 What owners must do now AI is a partner 12:01 The real automation unlock 12:46 Scenario: "AI can help me sell a million of these" 15:35 Does an MBA or consulting background help? 16:55 Can AI replace strategic thinking? 19:38 Strategy beating better-resourced competition 22:46 The most common strategic mistake 26:20 All tactics, no strategy: what breaks first 26:58 When to stop doing everything yourself 29:19 Looking after yourself to make better decisions 30:56 Strategy vs tactics: the field and the chessboard 33:31 Questions to ask: SWOT and Ikigai 35:08 Quick-fire round: strategy or tactic? 36:43 AI implementation or strategy first? 37:31 Hot take: the AI health and safety inspector 40:53 "I don't have time for strategy" 42:46 Two questions every owner should ask 44:05 Where to find May and Jab Listener Challenge Write your strategy in one sentence: the address you'd put in the sat nav. Then go through this week's to-do list and mark each task as either "moves me there" or "keeps me busy". Cut or delegate one task from the busy pile before Friday. Connect with the hosts May Zhan, AI automations and strategy for small business owners and founders: may@venturevoice.ai · linkedin.com/in/may-zhan Jab Siwela, audience, resonance and revenue for wellness brands: linkedin.com/in/jab-siwela More episodes: maycontainjab.com · mayandjab@maycontainjab.com