150+ people turned up. Really heartening to see the marketing community in Singapore being so passionate about AI.

As a marketer trying to make sense of this post-AI world, there are a few things I’ve come to believe:

1. Community matters more than ever.

2. We learn faster (and better) from each other than figuring everything out alone.

3. No one has this figured out. We’re all still students.

Below are some highlights from the session, plus the deck I shared.

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Designing Agentic Systems

I think agentic systems should be built around two simple principles:

• Repeatability

• Your biggest bottleneck

Repeatable systems let you run proper evaluations, handle errors cleanly, and feed context back into the workflow without things breaking.

Bottlenecks force clarity. Identify the biggest constraint in your role or business, then design a system specifically to remove that choke point.

Agentic Systems = Workflow Layer + Data Layer + LLM Layer

3 things every agentic systems needs:

1. Workflow Layer: This is where everything gets built and automated. It handles the logic, the routing, and the sequence of tasks.

2. Data Layer: Feeds your workflow with the information it needs, such as internal and/or external data

3. LLM Layer: Uses a model to interpret inputs, make decisions, and generate actions or outputs.

Bottleneck → Supply or Demand Constrained

Generally speaking:

• Supply Constrained: Build operational efficinecy agentic systems

• Demand Constrained: Build demand gen/customer acquisition agentic systems

Why I think bottleneck identification is important?

In the AI world we’re in, there’s just too much noise. And too little time.

We need to cut through the noise and fight the fomo. And not explore endlessly or try to build every single type of agentic workflow out there.

This was actually me 4-5 months ago, where I was trying to build everything, test everything, and ended up spreading myself too thin.

Now, I’m super focused on the parts of agentic marketing that actually is required for my role.

Remember: The market rewards depth over breath

Mockup of a Demand Generation n8n Workflow

I also built a mock workflow in n8n using the problem statement below.

Your role: You’re a demand generation marketer at Airwallex.

Your goal: Acquire more net-new F&B customers in Singapore for Airwallex’s payment gateway.

Workflow steps

1. Scrape Google for “online bakery”–related keywords in Singapore

2. Render the HTML to extract content

3. Pass everything into LLMs to do three things:

   1. Extract the email

   2. Check if the business is actually doing online bakery (look for terms like “show now”, “delivery”, etc.)

   3. Draft a cold email

4. Store the results in Google Sheets so you can use them immediately

The end result?

You’d get something like this. And once this is built, you can schedule it to run daily or weekly… giving you a steady, predictable stream of leads without manual effort.

Agentic Workflow Improvements

Agentic workflows aren’t something you set once and forget.

99% of the time, you won’t get it right on the first try.

That’s where evaluation and iteration of your workflow becomes very important.

For example in this workflow, I noticed that

• Using an LLM to identify emails from the rendered HTML wasn’t reliable → better to use a dedicated email-finding API (like hunter.io).

• Some scraped results were already existing Airwallex customers → run them through your CRM’s API to filter and keep only net-new customers.

Wrap Up

It was a really cozy event. Packed, but in a good way. Lots of genuine conversations, people sharing what they’re building,

I honestly learnt a lot just from talking to everyone. The questions, the small chats after the session, the random “hey, I’m trying this too” moments.

Events like this remind me why community matters so much in a post-AI world. None of us have everything figured out, but together we move a lot faster.

Thanks again to everyone who came up to chat. Hope to see you all at the next one.

PS: Here’s the link to my deck if you want to look through it.

So business owners and solo marketers doing it all themselves can skip the guesswork… and copy what actually works.

→ I drop one of these 10xPlaybooks 🚀 every week. Don’t miss the next.

John

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She’s one of the few marketers I’ve met who doesn’t just tinker with AI tools. She builds AI workflows, codes her own MCP servers, and thinks deeply about where AI & marketing is really heading.

Since then, we’ve had long, unfiltered conversations about AI and marketing. And every time, her perspective stood out: blunt, strategic, and refreshingly free of hype.

Some of my favorite AI-related posts from Alex on LinkedIn:

• A masterclass in storytelling

• MCP Guide

• It’s all about strategy

That’s why I asked Alex to share her thoughts in this Q&A, so more people can hear the way she thinks about AI & marketing.

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Question #1: Why do you think strategy is the real moat for marketers in the AI era?

Alex: Strategy is the baseline.

But it’s not the only thing. What makes marketers defensible in the AI era is the combination of strategy, curiosity, taste, and empathy.

• Strategy matters because if you don’t understand the problem you’re solving, the audience you’re solving it for, and what people actually expect, no tool or workflow will save you.

• Curiosity is critical because AI changes so fast. If you’re not experimenting and asking new questions, you’ll fall behind.

• Taste and empathy separate the noise from what’s valuable. Audiences already filter out generic “AI slop.” To create content that resonates, you need human judgment, taste, and the ability to put yourself in the customer’s shoes.

So yes, strategy is the moat, but it only works if you combine it with curiosity and taste.

That’s what will separate great marketers from everyone else as AI makes execution cheaper and easier.

My Thoughts: 

I think strategy comes from an innate grasp of marketing fundamentals. The stuff you only build by solving with real problems, not with shortcuts.

The thing about AI is it tempts marketers with an easy way out. You can skip the understanding, get a decent answer fast, and move on. But it’s exactly that hard work, the failures and the experimentation that builds real strategic thinking, 

Question #2: Does AI make it harder for younger marketers to build strategy?

Alex: Yes and no. Nobody sat me down early in my career and taught me “strategy.” I learned it by jumping into tactics, failing, then breaking things down and realizing what worked and what didn’t. That trial-and-error process is what builds strategic thinking.

The risk with AI is that younger marketers may skip that process. They can get answers fast, but they lose the struggle that usually forces deeper understanding.

That’s why leaders have to step in. It’s our responsibility to expose younger marketers to strategy:

• Explain the “why” behind decisions (why we chose this playbook, why we ignored that channel).

• Show them how positioning and messaging are built, not just hand them a tool.

• Give them space to experiment. To think, problem-solve, and find their own answers.

AI can accelerate parts of the work, but without mentorship, I think that junior marketers risk staying stuck in tactics.

My Thoughts: 

I used to be a very tactical marketer, always hunting for inefficiencies in the market we could exploit for quick results. The problem is, those gaps never last. You end up chasing short-term wins instead of building something sustainable. 

Learning strategy is what allows a marketer to shift from quick wins to building something sustainable.

Question #3: What does a strategy-first approach to building AI workflows look like?

Alex: When it comes to AI automation, it's easy to confuse strategy with complex workflows, but those tend to backfire.

Those complex no-code workflows look shiny, but they break easily, waste time, and often require developer skills anyway.

A strategy-first approach starts with the problem: what are we actually trying to solve? From there, it’s about choosing what’s worth automating and what isn’t.

That usually means starting small:

• Using tools you already have (like Gemini inside Sheets) to save hours on analysis.

• Building lightweight workflows that solve one real bottleneck.

• Automating only once you know it works in practice.

Chasing end-to-end agents that promise to "replace your marketing team" won't get us far. But stacking small, reliable wins that align with our strategy will.

My Thoughts: 

For me, strategy in AI workflows starts with one question: what specific problem are we solving?

The workflow should exist only to solve that problem. Nothing more.

Most of the time, that means the workflows aren’t complicated. They’re focused, singular, built to solve for X and only X.

Question #4: Part of strategy is focus. With new AI tools every week, how do you decide what’s worth exploring?

Alex: "Shiny tool syndrome" is real. With endless updates on new tools, features, models, and "no-code" workflow templates, it's too easy to be distracted.

The way to stay focused is to start from first principles: what actually makes a difference for your marketing strategy and pipeline? Strategy means deciding not just what to do, but what to ignore.

That often means doubling down on smaller, proven wins such as plugging AI into Google Sheets to analyze thousands of rows of data, instead of chasing the latest tool.

Focus is a discipline: ignore 90% of the noise and go deep on the 1–2 things that create real impact.

My Thoughts: 

I’m a lot more selective with AI tools now. When I first started, every new launch felt like a “game-changer,” and I wanted to try them all.

But after spending time building actual AI workflows, my approach has shifted. 

Today, I look at tools on a needs basis. If I’m repeating a task often, that’s when I’ll look for an AI tool to augment it, not before.

Question #5: If AI makes execution a commodity, what else besides strategy gives marketers an edge?

Alex: If AI commoditizes execution, the edge won’t come from a productivity and efficiency boost, as everyone will have that.

The edge comes from what AI can’t replace: taste, empathy, and authenticity.

• Taste: knowing the difference between high-value content and generic “AI slop.” Audiences are already filtering out posts that feel machine-written. Marketers with taste will know how to steer AI to produce quality that resonates.

• Empathy: being able to put yourself in the customer’s shoes, understand what actually matters to them, and translate that into campaigns.

• Authenticity and community: people will crave human-to-human connection more than ever. Live events, founder-led brands, and communities will become some of the strongest differentiators.

So beyond strategy, the moat is human judgment and the ability to build real trust. That combination is what will separate marketers who thrive in the AI era from those who get drowned out.

My Thoughts: 

It’s funny how things change. I started my marketing career right when social media was taking off. Back then, brands were ditching human-to-human connection to go online.

Ten years later, we’ve gone full circle in the age of AI. 

Wrap Up: A Marketer’s Real Moat

The future of marketing won’t be defined by who tries the most AI tools. It will be defined by who uses them with focus, judgment, and strategy.

That’s Alex’s core message: AI is just the accelerator.

The real moat comes from how you think, what you choose to ignore, and the edge only humans bring… Which is taste, empathy, and authenticity.

Big thanks to Alex for sharing her candid perspective!

PS: Do follow Alex on LinkedIn for hype-free AI use cases for marketers and GTM teams, which she shares regularly.

So business owners and solo marketers doing it all themselves can skip the guesswork… and copy what actually works.

→ I drop one of these 10xPlaybooks 🚀 every week, don’t miss the next.

John

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Today, she’s one of the top AI educators on YouTube with 75,000+ subscribers and some of the most practical AI marketing content I’ve seen.

Videos that helped me the most:

• You’re using Perplexity Deep Research Wrong

• This NotebookLM + Perplexity Workflow Will Cut Your Research Time by 50% (or More)

• Turn Claude to Powerful AI Agents, Automate 50% of Your Work

I asked Grace for her honest take on what’s really changing and how marketers can adapt and stay relevant.

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Question #1: How real is AI really impacting marketing jobs?

It’s very real. AI is impacting every industry and role, not just marketing. But marketing was one of the first to be affected, because so much of it involves content creation and data analysis.

Especially in content marketing and social media, AI can now brainstorm ideas, generate basic drafts, and create high-quality visuals.

Not only do industry research studies show more use of AI in marketing functions, but I see this from my own observations working with brands.

The 3 most impacted areas are:

• Content creation - Brands are more aware and actively learning how to incorporate AI in marketing tasks, especially those repetitive and tedious creative design tasks which used to take them hours or rely on external agency’s help. They can now do them in-house. The efficiency gain is so real.

• Market research - AI is now heavily being used to speed up market research and collect market data, building quick research reports and gathering sources. This is a real time-saver for most marketers.

• Data analysis - AI can be so useful in analyzing data and getting insights faster, and quickly propose hypotheses for spotting opportunities. But this is also an opportunity area where I see a gap at the moment. Brands are not yet structurally utilizing these into their daily workflow, which to me is a big missed opportunity.

Take the example of paid advertising - AI is automating bid management and audience targeting, and marketers can now focus more on other high-impact strategic tasks.

But while AI can speed up lots of groundwork, sound strategy and relationship building need to remain human. For example, digital growth consulting can't simply be done using AI. It takes good judgment to understand what would work best for the brand with its specific growth needs, and this is something AI can't do alone - it requires human experience to make good judgement.

The role of marketers is shifting significantly. The biggest opportunity I see for marketers: Leverage AI to analyze patterns, extract hidden insights, propose ideas, and do groundwork which used to take a big chunk of their time. Then spend more energy on strategy planning and focusing on building a trustable and memorable brand in the AI age.

This transformation is happening in months, not years, especially considering how fast AI is changing.

The future for marketing must be AI + Human.

Question #2: What skill will matter most for marketers to stay relevant with AI?

Besides developing strategic use of AI in marketing, one of the most important skills is good judgment. It will make the biggest difference in a marketer’s career progression.

Good judgment comes from critical thinking, reflection on past experience, active learning, verification skills, and self-awareness - all of which shape your unique way of thinking.

Judgment can’t be easily taught or “simply learned”, it is a skill that takes time and can’t be fast-tracked, which makes it difficult for AI to replicate, as it is built from years of experience, learning, and critical reflection.

The best marketer or smart AI users will be the ones who know when to trust AI and when to rely on their own human judgment.

Anyone can generate professional-sounding AI content or propose a strategy. But only those who can evaluate ‘this part is useful, this part is wrong’ will get ahead.

That’s also why I can’t fully automate my consulting work. AI can handle a lot of prep, but it’s still up to me to make the final call and propose solutions that will actually work for the client in the real world.

Judgement will be also what companies or employers value more, they won’t just value a marketer who knows how to use AI which is a table stakes, but also they value marketers who have their own judgment and are able to judge if AI's suggestions make sense or not while having their own input.

Aside, I recommend readers can check out this video about the critical skills to equip in the AI age to stay relevant:

🧠 John’s thoughts: That’s where strong marketing fundamentals matter. They give you the judgment to know what’s “good” or “bad” in what AI produces.

Question #3: How is AI making a real impact in your consulting work?

Since a big part of my role involves organic growth strategy consulting, these are 3 specific ways that AI is making a real impact.

1. Research acceleration for strategy development

What used to take me weeks of market research and competitor analysis now happens in days. Most AIs have deep research features that pull out market data to synthesize insights, so this is a huge time-saver for me to focus more on delivering more comprehensive strategy recommendations faster.

And again, a good strategy needs good judgement, so this is something still can’t be outsourced completely to AI.

2. Content strategy

AI has unlocked the ability to help clients to build their content strategy faster by fast-tracking competitor insights and unlocking deeper audience insights.

And not just content strategy, but also the actual content creation, where some of my clients are using more AI in their social media content creation e.g. generating video voice over, building content drafts which had significantly saved up their time.

3. Data interpretation and actionable insights

AI helps me quickly identify patterns in all sorts of data: market data, client performance data..etc that would take hours to analyze manually.

I can spot content gaps, seasonal trends, and optimization opportunities much faster, leading to more targeted and effective growth strategies.

So what used to be 80% research and 20% strategy is now flipped - AI handles the groundwork so I can focus on the strategic thinking that actually moves the needle for clients.

🧠 John’s thoughts: Using AI for marketing research has been the biggest time unlock for me. What used to take weeks now happens in days or even hours.

Question #4: How do you use AI in your YouTube content workflow?

What AI truly helps with is the content research process, which used to take me a lot of time. Tools like NotebookLM and Perplexity now help me quickly build a basic understanding of new AI topics by gathering different sources.

AI changes too fast to keep up with everything. Before, it took much longer to understand new concepts. Now with AI, I can build understanding much faster, then focus more on hands-on testing and verification.

Also, it allows me to understand what are the common areas that are being talked about in a specific topic, which I can identify any content gaps much faster than manual research and find unique angles to differentiate.

This is similar to SEO and content optimization, but AI takes the process to another level.

I do use AI like Claude to build content, outline draft or propose ideas like video titles, but again, 99% of the time the draft will still need to be revised and enhanced, as AI won’t have the same judgement as you, so this is a process that highly involves AI + humans in order to create truly distinctive and outstanding content.

I have built different projects on Claude to do specific repetitive tasks for my content creation process, e.g. drafting thumbnail ideas, descriptions, which save me time in building the first draft, while I can always enhance and fine-tune based on the initial drafts.

My advice for new creators?

1. Start by using AI to help with research and initial content structuring. Using AI to speed up your background research on content topics that are already resonating with your target audience in your niche.

2. Pick some of the biggest or greatest creators and study them with AI, what are the chosen topics, the content gaps, their audience comments that indicate what they like or dislike, what are the success patterns? Anything you can learn from them?

3. Use your own critical judgement to make the final call, never just rely on AI generated insights, and always have your unique insights and aim to develop your own style.

Question #5: What are your top 5 AI tools for marketing?

I personally have a minimal AI tech stack and I intentionally keep it lean, because more tools only make the outcome less effective, particularly when now most AI are becoming more powerful with more advanced features. Some of the top used AI right now:

• Claude - My go-to for strategic thinking and complex content development. Best at helping structure ideas, doing precise analysis, refining content angles, and providing nuanced feedback. Claude is also excellent in doing strategic analysis for both content and client projects with attention to details.

• Perplexity - Essential for real-time research and market data collection. It helps to speed up the initial content research process a lot, especially when it comes to some new AI or tech concept I am not familiar with or when some big enhancements in an AI model are announced. It’s also perfect for gathering current trends and competitor insights with sources.

• Gemini: I started using Gemini more since the significant upgrade to their Gemini 2.5 Pro, from which I have gotten some great results for all kinds of marketing or research works besides Gemini deep research (it's a really smart model!). Gemini also keeps adding capabilities like building, and integrating with other Google products, which is a huge plus for me. I also use it to analyze large datasets or codesets as it has a 1M-token context window, which has been a great help for my strategy work.

• ChatGPT: I use it whenever I need a second opinion, and I mainly use the reasoning models. ChatGPT's reasoning model is exceptionally logical, and it can be useful for providing subjective analysis, especially when matters are important.

• NotebookLM - Underrated gem for content synthesis. I use it alongside Perplexity, and what I like about NotebookLM is the minimal hallucination compared to other AI tools, making its insights more reliable. I can make sure the insights are gathered only from the quality sources I defined. Great at taking multiple research sources and identifying patterns or initial talking points. Most people overlook this but it's incredibly useful for deep content development and for SEO analysis as well.

• N8n - a trending AI workflow optimization tool that I am increasingly using lately to automate some repetitive processes and make more high-impact workflows.

My advice is always focus on your needs and biggest pain points first, and not just those trending AI tools that you’re using because of FOMO.

You don’t have to develop super sophisticated or a list of AI tools to make the process efficient. Always keep things simple, reliable and start with just one biggest problem first before scale.

🧠 John’s thoughts: Totally agree on the FOMO. I used to want to try every AI tool out there. Now I stick to four or five that solve specific problems in my marketing stack.

Wrap Up: What Will Set You Apart

The future of marketing is not about using more AI tools.

It is about using them well with judgment, strategy, and a clear point of view.

And that’s what Grace’s message really comes down to: AI is a tool. You are the difference.

Thanks Grace! For this opportunity to speak with you.

So business owners and solo marketers doing it all themselves can skip the guesswork… and copy what actually works.

→ I drop one of these 10xPlaybooks 🚀 every week, don’t miss the next.

John

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My session was titled “AI in Action,” and it focused on two things:

First, to show what’s possible. I walked through how AI is already transforming areas like marketing, store intelligence, and frontline enablement. The goal was to spark ideas and show how fast the landscape is shifting.

Second, to bring it down to the ground. I visited one of Singtel’s retail stores ahead of the townhall, mapped the real workflows, and shared two practical AI ideas that could be implemented immediately.

Let me quickly recap a few of the more interesting things I showed during the session.

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1. AI Avatar of Singtel’s Business Director (HeyGen + ElevenLabs)

To kick things off, I wanted to show just how far AI realism has come.

So we created a full AI avatar of Singtel’s Business Director, Daniel Soh and embedded it directly into the Singtel’s Townhall deck.

What I used:

• A photo of Daniel

• A 2-minute voice recording of him speaking in English

What we got:

• A hyper-realistic video of Daniel presenting and it’s fully lip-synced (created via HeyGen)

• His actual voice, cloned using ElevenLabs

• And the surprise: it translated into Mandarin too with synced lip movement

It was a live example of how AI can localize messaging, at scale, in seconds.

2. Built the Entire Deck in Gamma (AI-Powered Slides)

I built the entire AI portion of the Singtel’s Townhall deck myself using Gamma.

Gamma is an AI-powered tool that helps turn rough outlines into clean, structured slides fast.

What it helped me do:

• Turn talking points into full slide flows

• Apply clean, consistent layouts without manual formatting

• Move fast on feedback from the Singtel team

The result?

A polished, professional deck which was created end-to-end in under 60 minutes, not days.

3. How US Retail Chains Use AI to Pick Store Locations (Placer.ai)

I also shared a quick case study from the U.S. where retail chains are using geolocation AI tools like Placer.ai to decide exactly where to open new stores.

Instead of relying on gut feel or old traffic reports, these tools use:

• Real-time foot traffic data

• Mobile location signals

• Demographic movement trends

The result?

More accurate store placements, stronger retail performance, and faster decision-making all powered by location intelligence.

4. Shared Actual Live AI Workflows

I shared a few real AI marketing systems I’ve built that are already running inside live campaigns.

• One helped a company save over $12,000 by automating a process that used to take hours — built in under 10 minutes

• Another enabled a team to scale their ad spend from $30K/month to $250K/month by speeding up creative testing with AI-generated ad visuals and copy

I showed how tools like OpenAI, image generation, and simple automation flows (like the one below) can remove bottlenecks without adding headcount.

5. Mapped a Real Retail Workflow → Found a Quick-Win AI Use Case

Before the Townhall, I visited one of Singtel’s retail stores to observe frontline operations firsthand.

I spent time speaking with the senior sales associate on duty and also asked one simple question:

“What are the tasks you repeat every day?”

The goal was to spot areas where AI could step in to augment speed, accuracy, and customer experience.

One quick-win opportunity emerged clearly: AI Wi-Fi Consultancy.

Here’s the gap:

• Sales associates often spend 5–10 minutes per customer advising on optimal mesh Wi-Fi placement based on home layout, ONT location, and signal strength.

Here’s the fix:

• Use tools like ChatGPT to auto-analyze floorplans and output mesh router guidance instantly using Singtel’s own recommendations.

The outcome?

• Faster consults

• More accurate recommendations

• And a scalable process that doesn’t require more headcount

Wrap Up

Getting to walk the store floor, speak with the frontline team, and then share live demos with the wider group made it feel less like a keynote… and more like a working session that mattered.

Grateful for the opportunity and honestly, I’d love to do more of these.

Helping teams turn ideas into action is where AI gets interesting!

So business owners and solo marketers doing it all themselves can skip the guesswork… and copy what actually works.

→ I drop one of these 10xPlaybooks 🚀 every week. Don’t miss the next.

John

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We kept it simple: five questions, straight to the point.

Some of the use cases Jacob shared made me stop and take notes.

Like how he replies to 1,000 LinkedIn comments with AI, or turns call transcripts into content that actually shapes messaging.

What You Can Steal From This:

• An agent that replies to 1,000+ comments → saves 20 hours a week

• A transcript-to-content workflow → pulls messaging straight from your audience’s mouth

• A founder doing all of the marketing work by himself

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Question #1: What’s your go-to AI model(s) right now and what do you use them for on a daily basis?

Gemini 2.0 Flash is my go-to model for extraction and summarization from long documents. It’s extremely cost effective and has a large context window.

Claude 4.0 Sonnet is my preferred model for writing and analysis.

OpenAI’s GPT 4.1 with built-in search is my favorite for research.

🧠 John’s thoughts: I’ve been seeing more marketers recommend Claude as their go-to model for writing. Worth running a side-by-side test if you haven’t done so already.

Question #2: What’s one AI workflow or agent you’ve built that saved you the most time?

My biggest time savers are my workflows for automatically tracking and replying to LinkedIn comments. My posts often get between 100 and 1000 comments, and I was spending 20 hours per week replying to them all.

Now AI takes the easy 90% and I do the 10% that still require my judgement.

Full workflow in this video below 👇

🧠 John’s thoughts: This exact agent saves him 20 hours a week. Imagine what you’d do with that time.

Question #3: What’s one underrated AI workflow or tool that more marketers should be paying attention to?

Synthesis of customer insights!

If you’re getting recordings and transcripts from an AI notetaker, you need to be using those to generate content and inform your messaging. An AI agent is REALLY good at this.

🧠 John’s thoughts: Understanding your target audience is important. Use an agent to turn those transcripts into messaging angles for your ads, social posts, or even landing page copy. 

Question #4: How has AI changed the way you market Relay.app in practical terms?

I am a one person marketing team (while also being responsible for sales, support, finance, HR, etc), and I’m able to produce quite a lot.

Here are some numbers:

This would not have been possible without AI!

Question #5: What’s one part of marketing you think AI will disrupt most in the next year?

Learning to build AI workflows and agents will be the most important foundational professional skill not just for the next 12 months but for the next 20 years.

Get started building.

🧠 John’s thoughts: I think marketing’s going to look very different 12 months from now. It’ll be about who can control and scale a set of AI agents to deliver real, tangible work.

Wrap Up: Start Now

For those of you on the fence, consider starting now.

Relay.app is honestly one of the most intuitive platforms I’ve seen for trying your first agent build.

Build your first agent. See what 20 extra hours a week feels like.

So business owners and solo marketers doing it all themselves can skip the guesswork… and copy what actually works.

→ I drop one of these 10xPlaybooks 🚀 every week, don’t miss the next.

John

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