GTM for Early Stage SaaS | Co-founder @ Datapad | SaaS Growth Advisor | Reforge | 1x Exit |

I’m a marketer, 2x entrepreneur with 1x exit, and helped companies to go from 0 to 8 figures.

My achievements:

- Built 2 VC backed startups with one exit

- Built a 7 figure productized marketing agency

- Became a mentor in top accelerators such as: 500, Plug and Play, Techstars

- Got to work with the portfolio companies of amazing investors such as A16z, Craft Ventures, YC

- Built a podcast with 20k downloads in a year-figure

- Transformed my body more times than Christian Bale ☺️

John Ozuysal

SEO and AEO agencies are dead

I replaced my $15k/mo agency with Claude Code.

Here is what my agent does:

- Creates content strategy around topics such as "ultimate guide to xyz" or "what is xyz" - zero defendability for AI search 

- Optimizes each post with [some made-up name] framework

- Found my ICP in 5 seconds, even though I couldn't figure it out for a year 

[screenshot of the flow] - I have no idea what any of this does. Neither does the person who built it.

We used this agent for 6 months, and below are the results from the AI search

[screenshot of Google Search Console]

And yes, we are tracking AI search from GSC, so all the AEO tools are unnecessary

I spoke with a CMO of Series B B2B SaaS last week about their AEO

He was furious.

"ChatGPT is telling people we're too expensive for small teams." - not correct at all

We pulled up the sources AI was citing.

Competitor blog posts. Reddit threads from 2021. A review site that hadn't been updated in 18 months.

His first instinct?

"We need more PR. More brand mentions. More visibility."

No. You don't.

That's not your problem.

Your problem is you never created content that answers the questions buyers are actually asking.

Best tools in your category. Alternatives. Comparisons. Use cases by company size.

You left that to competitors and review sites.

So now they're the source. Not you.

You're not invisible. You just handed the microphone to everyone else.

Early-stage companies have the opposite problem.

AI genuinely doesn't know they exist yet.

PR and brand mentions actually matter there.

But for you?

Create the content that answers buyer questions.

Become the source AI cites.

Stop letting competitors control your narrative.

TLDR: Assess your current situation before you invest in any AEO-related activity

---

If you want us to build a free AEO roadmap for you, apply from the link on my profile

Your buyers trust ChatGPT more than your sales team.

That's not an insult. That's just how people make decisions now.

They ask AI for recommendations. They get a shortlist. They do follow-up questions. By the time they land on your site, they've already decided whether you're a contender.

But here's the problem:

Most B2B SaaS companies have zero control over what AI says about them.
AI is citing outdated competitor blog posts. Old Reddit threads. Review sites that haven't been updated in over a year. And it's confidently presenting that information as if it's current.

I've seen AI tell buyers a product is "too expensive for small teams" based entirely on a competitor's comparison post from 2022. Completely inaccurate. But that's what the buyer heard.

So how do you take back control?

You become the source.

Step 1: Identify the 20-30 buying questions your ICP is asking AI right now. Turn your paid search keywords into questions.

Step 2: Ask those questions yourself. Look at what AI cites. What source types? Who gets mentioned?

Step 3: Fill the gaps. If AI cites a listicle, get on that listicle or create a competing one. If it cites a forum thread, go give a real, transparent answer. If it cites a video, make one.

Step 4: Optimize your help center so it answers every specific feature, integration, and use case question a buyer could ask in a follow-up.

Do this consistently for 6 weeks, and you'll see the shift.

The brands that control their AI narrative now will own their category later.

I think AI search visibility trackers are useless 

Why? 

Because I keep seeing AEO case studies with screenshots of the search console

I guess we are all missing something because my GSC is not giving me AI search visibility data 🤣 

Sad thing is, some of these posts are getting 500 comments

We are running an AI search sprint free for 3 SaaS companies

👇

We're opening up 3 free pilot slots to show you exactly where you stand on AI search and what to do about it.

Here's what you'll get:

- A full AI search audit of your brand vs your top competitors

- Your 30-day AI search content strategy + the brand mentions you need to build

- Your first revenue-focused content — written and ready to publish

We hand-pick the companies. We're not looking for volume. We're looking for fit.

That means Series A B2B SaaS. $1M+ ARR. A category worth owning. And a team that will actually execute on what we hand them — because we're not interested in doing great work that sits in a Google Doc.

Q2 2026 cohort has 3 spots.

If you think you're the right fit, apply from here: https://tally.so/r/442j4A

I haven't been to a graveyard in years.

Turns out I didn't need to, I just needed to open LinkedIn.

People here love the Kill Channels:

RIP Email. 

RIP Agencies. 

RIP Content. 

RIP Thought Leadership. 

RIP Ads.

At this point, everything's been declared dead at least 100 times.

And yet... somehow they all keep showing up to work on Monday.

Haven't invested in AEO yet? 

Don't start with content 👇

Start with a diagnosis.

Before creating any content, figure out whether the issue is visibility, representation (citation control), or both.

Later-stage companies usually already have visibility. The risk is how they’re being represented.

 AI search often pulls from competitor blogs, old Reddit threads, reviews, and third-party posts that don’t reflect the company’s current narrative.

The first step is to identify the URLs influencing AI answers and audit them for accuracy.

In parallel, build earned content quickly so AI systems learn from the company’s own materials, not someone else’s.

Earlier-stage companies typically have a visibility problem and a representation problem.

Start by mapping the prompts you want to win, then identify which URLs currently influence those prompts (often listicles and Reddit threads).

From there, focus on earned visibility by participating in those conversations and getting included where influence already exists.

Once there’s more budget, expand into creating content designed to compete for broader, category-level prompts.

We just increased AI search visibility for a B2B SaaS client by 100% in 30 days.

Want to see how we did it?

You can't. The case study doesn't exist. I made it up.

But you'd have believed it, right? Because you've seen 15 posts this month saying almost exactly that.

Here's the problem: a lot of people claiming to grow AI search visibility are backing it up with Google Search Console screenshots.

It does not tell you how often your brand appears in AI-generated responses. 

It does not tell you what AI systems say about you. It does not measure anything that would reasonably be called "AI search visibility."

Posting a GSC screenshot as proof of AEO results is either a misunderstanding of how this works or a deliberate misdirection aimed at people who don't know the difference.

If someone is showing you clean dashboards and confident attribution, ask them which tool produced it and how it works.

If the answer is a Google Search Console screenshot, walk away.

4 types of competitor-focused content I use to generate pipeline for SaaS

👇

1. Competitor vs You

You must own this story. If a prospect types “[competitor] alternative” into Google and only sees their page, you already lose. Create clean “You vs Competitor” pages that talk in revenue, churn, onboarding time, not vague feature lists. Show how you reduce risk, cut time-to-value, or lift expansion revenue.

2. Competitor alternatives

These people are in market now. They already pay for a tool. They just hate something about it. Create list posts like “7 alternatives to [competitor] for remote CS teams” and rank for those terms. Include your product in the list, show screenshots, add simple pricing context, and link to a focused trial or demo page. This brings high-intent trials fast.

3. Competitor comparisons

Big brands fund your pipeline. Use their demand. People search “[competitor A] vs [competitor B]” every day. Write posts and pages like “[A] vs [B] vs [You]” and speak to a specific ICP: “best for product-led teams”, “best for agencies”, “best for low-ACV SaaS”. You ride their brand search while positioning your product as the right fit for a clear segment.

4. Competitor use case content

Show how to do a key job in competitor tools, then show the simpler version in your product. “How to build a QBR dashboard in [competitor]” → then you show it takes 9 steps there and 3 in your app. If a competitor cannot support that use case, say it clearly and own the gap. This is where many of your best switch deals come from.

----

If you want us to generate a free AEO report, check the link on my bio !

Your competitors keep showing up in ChatGPT.

You don't.

Here's what nobody in the "AI SEO" space is saying clearly enough:

The AI doesn't care that your landing page ranks #1 on Google.

When someone asks "What's the best [your category] tool?" — ChatGPT isn't reading one page and picking a winner. You can be a source, but this is not the same as being "visible."

It's pulling from everywhere. Forums. Video platforms. Review sites. 

Knowledge bases. Third-party articles.

Then it stitches all of that together into a single answer.

Your competitor shows up in a roundup article. They're recommended in a forum thread. Someone made a walkthrough video about them. 

Their knowledge base answers a niche feature question.

That's 4 mentions across 4 different source types.

This is the game now. You have to build citation layers, stacking your brand's presence across the source types that AI models actually pull from.

Here's how to start:

- Take your best converting-value paid search keywords or highest converting organic keywords, or even better, ask your customers how they searched for you.

- Ask Claude to turn this into buyer prompts. For each prompt, check what is being cited, and what kind of sources? Whose mentioned?

- Then build your owned content and earned content strategy based on this information.

- If the AI is pulling from a listicle comparing your competitors, go create your own listicle and also get included in that one. 

- If it's citing a forum thread where someone asks about your category, go give a real, helpful answer from your actual team. If it's referencing a video walkthrough, make one.

Match the source type that's already winning the citation. Don't guess. Mirror what's working.

Treat it like a proper experiment. Pick 10questions to intervene on. Leave 10 untouched. Track the results over 6 weeks.

This is exactly how we run AEO experiments at House of Growth - AI Led Growth Agency

Companies running this playbook are seeing AI-referred traffic convert at dramatically higher rates than traditional search. 

And most of your competitors still think this is "too early" to worry about.

I see people bragging about creating blog posts with Claude code for AEO

Sad thing is, they are still creating blog posts such as:

- What is [topic]

- Ultimate guide to [topic]

You clearly have no idea how AEO works, otherwise you wouldn't create these and call them "AEO" focused posts

Why you don’t show up in AI search?

Here’s the simplest answer:

You have no content.

And nobody knows, mentions, or talks about your brand.

That’s it.

AI systems don’t “discover” brands magically.

They reflect what already exists on the internet.

Once you accept this, everything else makes sense.

Only then do details start to matter:

Entity optimization
Query fan-outs
Topical authority etc..

Andrew Bolis

Influencer (700+ Brand Collabs) 🧠 AI & Marketing Consultant 📢 Former CMO 📩 DM for Influencer Partnerships ➡️ Follow for AI & business growth tips.

⭐ Brand Partnerships & Influencer Marketing: I partner with companies to promote their products to my 464k followers across LinkedIn, X/Twitter & Email Newsletter. I've previously partnered with Notion, HubSpot, Upwork, ClickUp, Miro, Semrush, Instantly, Clay, Lemlist & Gamma.

💬 DM me "COLLAB" to learn more!

---

⭐ AI & Marketing Consulting: 

I help companies leverage AI to optimize their marketing and sales. 

● Generate more qualified leads and sales opportunities
● Close more deals and shorten your sales cycle
● Grow your revenue while cutting costs

💬 DM me "AI" to learn more!

---

⭐ My Career Highlights: 
● $210M in attributed revenue from marketing campaigns
● 15 yrs of marketing leadership experience (Mngr/Dir/CMO)
● Drove revenue growth from Series A to E stages at startups
● Built & led global teams of up to 20 people across NA & EU
● Managed global expansions (NA, EU, LATAM) & acquisitions
● Established product as a Leader in Gartner Magic Quadrant
● Focus: Demand Gen, Digital Mktg, Content Mktg, Sales Dev
● Verticals: SaaS, MarTech, EdTech, Supply Chain & Logistics

Fractional CMO, Marketing Consultant & AI Strategist

I help companies leverage AI to optimize their marketing and sales. 

● Generate more qualified leads and sales opportunities
● Close more deals and shorten your sales cycle
● Grow your revenue while cutting costs

💬 DM me “AI” to learn more!

Visit my website (at top of my profile) for free resources.

- - -

My previous consulting gigs and contract work:

💼 Fractional CMO & Head of Marketing at The Virtual Hub (July 2023 - September 2023)

The Virtual Hub provides virtual assistants and offshore staffing services for businesses. It's a 350-employee company that's bootstrapped and profitable. 

💼 Marketing Strategy & Growth Consultant at Upshift (March 2023 - May 2023) 

Upshift connects people with businesses in need of extra staff. Upshift is trusted by 1600+ businesses across 25+ cities for staffing hourly workers. 

Upshift customers: Compass Group, American Airlines Arena, InterContinental Hotels Group, Six Flags, Victoria's Secret, Cedar Fair, Delaware North, Hard Rock Hotel & Casino, Hyatt, Kroger.

💼 Fractional CMO / VP of Marketing at Packback (February 2023 - April 2023)

Packback is an EdTech company that uses AI to help educators implement high-quality teaching methods at scale. 

Packback customers: Michigan State University, Maricopa Community Colleges, University of Illinois Urbana-Champaign, SUNY - The State University of New York, Ivy Tech Community College, FSCJ - Florida State College at Jacksonville, HACC, UNT - University of North Texas, Minnesota State, Miami Dade College.

Top 10 Free AI Courses to Upgrade Your Skills. 

Learn from Harvard, Microsoft, Google, and more.

No payment required to build skills & advance career. 

Master AI, prompting, and automation all in one place.

Save list for later (click three dots at top right → Save).

Here’s the full list with direct links below:


⚙️ AI Fundamentals & Core Concepts

1️⃣ Harvard – Introduction to AI with Python
➟ Learn the core logic behind AI using Python.
🔗 https://lnkd.in/gX2_ZCq7

2️⃣ Microsoft – AI For Beginners
➟ A simple path to build a strong foundation in AI.
🔗 https://lnkd.in/gbyGV3Ni

3️⃣ Google – AI Courses
➟ Master core AI and ML tools with Google experts.
🔗 https://lnkd.in/gbSqTX8x

4️⃣ DeepLearning.AI – Generative AI for Everyone
➟ Learn how generative AI creates text, visuals, and ideas.
🔗 https://lnkd.in/d95ZQneP

5️⃣ LinkedIn – Generative AI Courses
➟ Short, practical lessons to upskill with LinkedIn learning.
🔗 https://lnkd.in/gS_Kqr7u


🧩 Prompt Engineering & Applied AI

6️⃣ Vanderbilt – Prompt Engineering for ChatGPT
➟ Learn prompt design techniques for ChatGPT optimization.
🔗 https://lnkd.in/gCUiZuU5

7️⃣ DeepLearning AI × OpenAI – ChatGPT Prompt Engineering for Developers
➟ Learn advanced prompting for real-world developer projects.
🔗 https://lnkd.in/dMpn5Jb2

8️⃣ edX – AI Applications and Prompt Engineering
➟ Build hands-on AI projects using prompt-based techniques.
🔗 https://lnkd.in/gmqHeQU5

9️⃣ AWS – Foundations of Prompt Engineering
➟ Master prompt writing basics using AWS AI tools.
🔗 https://lnkd.in/gUPZN5B5


🌍 AI Ethics & Real-World Impact

🔟 UC Davis – Big Data, AI, and Ethics
➟ Learn the ethical side of AI and responsible data use.
🔗 https://lnkd.in/gviZqRKD


Start learning AI today to future-proof your career.

📌 Learn 30 free AI tools in 30 days: https://bit.ly/48woPL4  

👉 Follow me Andrew Bolis for more and 🔄 Repost this to help others learn AI

Basic AI knowledge is essential in today’s workplace. 

Here are the top 12 AI terms you need to know. 

(remember to 🔖 save this for later) 

1. LLM: Predicts and generates human-like text.

2. Transformer: Helps AI understand context and relationships.

3. Prompt Engineering: Writing inputs that guide AI clearly.

4. Fine-Tuning: Custom training for industry-specific tasks.

5. Embedding: Turns words into numbers for comparison.

6. RAG: Pulls real info before generating answers.

7. Token: Small text units AI reads and counts.

8. Hallucination: Generates believable but false information.

9. Zero-Shot: Solves tasks without prior examples.

10. Chain-of-Thought: AI explains its reasoning step by step.

11. Context Window: Limits how much AI can process at once.

12. Temperature: Controls randomness vs. precision in output.

In the age of AI, no matter your role or function…

Knowing these terms is no longer optional.

Save it. Share it. Speak AI clearly.

📌 Learn 30 free AI tools in 30 days: https://bit.ly/48woPL4 

👉 Follow me Andrew Bolis for more and 🔄 Repost this to help others learn AI

Harvard University is offering its top courses 100% free.

No application. No fees. No prior skills required.

These 12 courses are free, online, and open to everyone:


1. Introduction to Computer Science

Learn foundational computer science concepts and programming in languages like C, Python, and JavaScript.

https://lnkd.in/g3PJt6V5

- - -

2. Introduction to Artificial Intelligence with Python

Explore AI concepts including search algorithms, machine learning, and neural networks using Python.

https://lnkd.in/gKTUCzCQ

- - -

3. Web Programming with Python and JavaScript

Build web applications using Python, JavaScript, SQL, and frameworks like Django and React.

https://lnkd.in/gfdnP_c8

- - -

4. Understanding Technology

Gain a broad understanding of how computers and the internet work, covering hardware, software, and security.

https://lnkd.in/gqmjkaC2

- - -

5. Introduction to Game Development

Learn principles of 2D and 3D game development using languages like Lua and C#, and tools like Unity.

https://lnkd.in/gTaws5EC

- - -

6. Introduction to Cybersecurity

Understand the basics of cybersecurity, including securing systems, data, and software.
 
https://lnkd.in/gG8_KdVh

- - -

7. Data Science: Machine Learning

Learn machine learning techniques to build predictive models and understand their applications.

https://lnkd.in/gaHYe8zj

- - -

8. Data Science: Productivity Tools

Master tools like Git, Unix/Linux, and RStudio to enhance data science workflows.

https://lnkd.in/gQGkTpTM

- - -

9. Leaders of Learning

Examine how people learn and how to lead learning environments effectively.

https://lnkd.in/ghAq82se

- - -

10. Introduction to Data Science with Python

Apply Python programming to analyze data and solve real-world problems.

https://lnkd.in/gn7Xzfjc

- - -

11. Introduction to Programming with Scratch

Learn programming fundamentals using Scratch, a visual programming language.

https://lnkd.in/gUQW5Zdy

- - -

12. Introduction to Databases with SQL

Understand relational databases and learn to use SQL for data management.

https://lnkd.in/gTZieFqQ


Learn in-demand skills, earn certificates, and boost your career.

📌 Learn 30 free AI tools in 30 days: https://bit.ly/48woPL4 

👉 Follow me Andrew Bolis for more and 🔄 Repost this to help others learn new skills.

All the AI buzzwords can be confusing. 

Here are simple definitions to understand AI. 

[ save 🔖 this post for later ]

Here are 28 AI terms even a kid can understand.

1. Artificial Intelligence – A computer brain that helps and learns.

2. Machine Learning – AI learns by studying examples.

3. Deep Learning – AI learns step by step in layers.

4. Neural Networks – AI parts work together to solve tasks.

5. Model Architecture – The setup for how AI learns.

6. Training Data – Info AI uses to get smarter.

7. Pretraining – AI reads first to get ready.

8. Fine-Tuning – Extra training after basics.

9. Reinforcement Learning – AI learns from rewards or mistakes.

10. Overfitting – AI memorizes too much and messes up.

11. Natural Language Processing – AI reads and talks like us.

12. Context Window – AI remembers just the recent words.

Find more terms in the infographic. 
AI doesn’t have to be complicated!

📌 Learn 30 free AI tools in 30 days: https://bit.ly/48woPL4  

👉 Follow me Andrew Bolis for more and 🔄 Repost this to help others understand AI

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