I help tech startup founders & leaders make more money with my powerful growth, marketing & product strategies ▪ Former Data Consultant to 10% of Fortune 100 ▪ Online Educator to >1.7 MM+ Learners 🎉)

Nearly 20 years ago, I was an engineer buried deep in technical systems and data models.

I saw brilliant startups with game-changing ideas… break down.

Not because the product wasn't great, but because their growth strategy was a guessing game.

That's when I realized: the difference between a startup that survives and one that scales isn't just a better product → It's a predictable, repeatable growth system.

Since then, I've…
● Helped 10% of the Fortune 100 innovate with data and AI
● Trained 2M+ professionals in AI-driven marketing and growth
● Guided startups from zero to scalable revenue, tripling inbound leads, driving 200x user growth in 1 month, and even driving 10,000+ MQLs organically for one VC-backed venture

Along the way, I developed the Marketing Maturity Model → A 3-level framework that takes startups from validation to predictable scale:
1️⃣ Market Validation & Early Sales – Prove demand through real sales before investing in scalable marketing
2️⃣ Brand & Audience Growth – Build structured brand identity and inbound lead generation systems
3️⃣ Scalable Growth & Monetization – Deploy advanced nurturing, optimization, and revenue acceleration

Today, as a Fractional CMO and Growth Partner for pre-revenue to $6M ARR tech startups.

I embed into your team, move fast, and replace costly trial-and-error with data-driven strategies and AI agent-enabled execution that compounds over time.

Because when your growth is systematic, you gain more than revenue → you regain control of your time, your focus, and your runway.

📍 If you're ready to scale without all the chaos:
→ Email me at lillian@data-mania.com or visit my website: https://www.data-mania.com/
→ Follow me on LinkedIn for free, practical, revenue-focused growth strategies
→ Subscribe to my weekly newsletters, from the featured section, for proven playbooks, AI-driven growth frameworks, and AI marketing strategies that are trusted by founders worldwide

Most AI search visibility tools are giving founders a dangerous false sense of security. I tested every major platform I could get my hands on over 6 months. 

... even built my own tools when the paid ones fell short. And here's what I discovered:

Most tools are solving the wrong problem.
They're all asking: "Are you being mentioned?"

But that's not the question that drives revenue.

Think about it like this: If you're a startup founder, would you rather know that your brand was name-dropped 47 times last month, or know that when buyers ask AI assistants for recommendations in your category, your top competitor is positioned as the premium choice while you're listed as "also available"?

Here's how to know if your current approach is leaving money on the table:
▪️ You track citation counts but have no idea what positioning you're getting in those citations
▪️ You celebrate being "mentioned" without knowing if you're being recommended
▪️ You measure visibility but don't know who you're being compared against
▪️ You optimize for showing up, not for being the obvious choice

The frameworks most tools are built on come from old-school SEO thinking. 

They treat AI search like Google in 2015.

But AI answers aren't search results.

When ChatGPT or Claude responds to a buyer's question, they're not showing 10 blue links. They're having a conversation. 

They're making recommendations. They're establishing competitive context.

And if you don't know what that context is, you're flying blind.

After six months of testing, I found exactly one tool that actually shows the competitive landscape: Airefs. 

Not because it tracks more mentions, but because it shows me WHO I'm cited alongside, what tactics are working for competitors, and which partnerships could shift my positioning in AI answers.

Here's what's changing now that I can finally see the full picture:
▪️ I can start optimizing more deeply for competitive advantage. 
▪️ I can see which content patterns were getting competitors recommended over me. 
▪️ I can identify partnership opportunities I'd been completely missing.

For me, the shift isn't from invisible to visible. It is from knowing that I am "mentioned occasionally" to me knowing I am getting "positioned strategically."

If you're relying on dashboards instead of what buyers actually see in AI answers, it might be time for an AI Visibility reality check.

Read the full breakdown: "I Tested Every AI Search Visibility Tool. Here's The One That Actually Changed My Strategy" 👇

Lillian Pierson, P.E.

Fractional CMO & GTM Engineer for Tech Startups ✱ AI Search Expert ✱ AI Marketing Instructor @ LinkedIn ✱ Trained 2M+ Worldwide ✱ Trusted by 10% of Fortune 100 ✱ Author & AI Agent Builder

View newsletter: AI Marketing Systems Architect

☝️ To get the latest growth playbooks that are working in today's market and to hear about the best AI marketing tools (& AI search visibility tools l

Open article: I Tested Every AI Search Visibility Tool. Here’s The One That Actually Changed My Strategy by Lillian Pierson, P.E. • 7 min read

I Tested Every AI Search Visibility Tool. Here’s The One That Actually Changed My Strategy

Early-stage startups struggle to keep their brand voice consistent when they scale content.

Here's the exact prompt engineering framework that solves it 👇

You hire writers. Brief agencies. Try templates.

But nothing sounds quite right.

Here's what most founders miss:

You don't need more people. 
You need a better prompt.

I spent weeks training Claude to write in my exact brand voice.

The result? 

Content that converts like our best sales pages, without me writing every word.

Here's the exact prompt engineering framework I use for myself & my clients:

Step 1: Define Your Baseline Context

Start every prompt with role clarity.

Example: "You are a CMO for tech startups writing to technical founding teams."

This isn't optional. It sets the entire frame for how the AI approaches your content.

Step 2: Upload Your Voice DNA

Don't just describe your voice, show it.

What to include:

→ 6 brand voice adjectives (approachable, practical, conversational, clear, encouraging, expert-yet-humble)

→ Full example posts that converted (at least 20,000 words)

→ Writing rules (like "never use em dashes" or "never write 'It's not X, it's Y'")

The AI needs to see patterns, not just hear descriptions.

Step 3: Layer In Strategic Context

This is where most people stop too early.

Don't just give Claude voice, give it strategy:

→ Your differentiation (what makes you different)
→ Your frameworks (methodologies you use)
→ Your positioning (how you want to be seen)
→ Case studies and social proof

Now the AI isn't just writing in your voice. It's writing from your strategic position.

Step 4: Build Guardrails

Tell the AI what NOT to do.

Example rules:

→ Never talk down to people
→ Speak in a supportive voice
→ Avoid corporate jargon
→ Don't use clichés or buzzwords

These constraints keep output on-brand even when the topic shifts.

Step 5: Test and Iterate

Run the prompt. Compare output to your best-performing content.
Adjust the framework based on what's missing.
Iterate 10-20 times until it sounds like you.

What this actually looks like in practice:

Week 1: Output sounds generic and robotic
Week 2: Getting closer, but missing your edge
Week 3: Starting to sound like you
Week 4: Content you'd proudly publish under your name

If your early-stage startup is drowning in content creation, this framework changes everything.

♻️ Repost this to help founders scale their brand voice.
🔔 Follow me for more AI-powered content strategies.

P.S. What's the hardest part of your brand voice to replicate?

Fractional CMO & GTM Engineer for Tech Startups ✱ AI Marketing Instructor @ LinkedIn Learning ✱ Trained 2M+ Worldwide ✱ Trusted by 10% of Fortune 100 ✱ Author & AI Agent Builder

5 steps to make AI write in your exact voice.pdf

I thought "GTM Engineer" was marketing BS.

A week ago, I rolled my eyes at the term. Another marketer rebranding themselves with a sexier title.

So I ignored it. For months.

Then curiosity got me. I searched the term.

What I found: Nearly 90 active job postings. Over 4,000 monthly searches. Job descriptions asking for "AI automation platforms," "workflow integrations," "data-driven experimentation."

I asked ChatGPT: "Am I a GTM engineer?"

Its response: "Yes. You've been doing GTM engineering for years. You just didn't call it that."

I stared at my screen.

For two decades, I thought I left engineering behind when I pivoted to marketing. But I never did.

I just started applying the same principles to revenue generation. Systems thinking. Root cause analysis. Constraint optimization. Measurement. Iteration.

When that AI consulting startup came to me drowning in freelancer costs, I didn't throw more content at the problem. I built a custom Claude MCP agent integrated with Airtable. Result: $5,160/month saved, 8x faster execution.

When Groe Solutions had zero inbound interest, I didn't start with tactics. I diagnosed the root cause: unclear positioning. Fixed that. First inbound leads within 60 days.

The engineering mindset I developed over 20+ years is exactly what makes my growth work different.

I don't guess. I don't chase trends. I design systems, test hypotheses, measure outcomes, and optimize for repeatability.

While most "GTM engineers" are growth marketers borrowing engineering language, I'm an actual engineer who happens to build revenue systems.
Turns out, there's a name for that now.

Read the full story in this week's LinkedIn newsletter 👇
#GTMEngineering #FractionalCMO

I’ll be honest: when I first heard “GTM Engineer,” I rolled my eyes so hard I nearly strained something. “GTM Engineering,” I thought, “give me a brea

Open article: I Thought “GTM Engineer” Was Marketing BS. Then I Found 89 Startups Hiring for It. by Lillian Pierson, P.E. • 12 min read

I Thought “GTM Engineer” Was Marketing BS. Then I Found 89 Startups Hiring for It.

AI search engines don't just read your SEO blog.

They also read conversations about you.

I've spent the last year guesting on about one or two podcast per month. Not because some growth hacker told me to. Because it felt like the right way to build relationships.

Then ChatGPT started recommending me as a "top fractional CMO for tech startups."

Here's what surprised me: It wasn't just reading my carefully optimized blog posts. It wasn't scanning my meta descriptions. It was also reading podcast transcripts. Interview mentions. Conversations where I explained my actual methodology.

Traditional SEO asks: "Does this page answer the query?"

AI search asks: "Is this person actually an expert in this domain?"

The difference matters.

One backlink says "this page exists." One podcast transcript explains why you're credible, how you think, what frameworks you use.

Google optimized for keywords. AI search optimizes for context.

If you're still treating partnership marketing as a "nice to have" while you dump budget into SEO tactics that worked in 2019, you're building on the wrong foundation.

Partnership marketing isn't fuzzy brand building. It's distributed system architecture for credibility signals.

You're not gaming the algorithm. You're building real authority at scale.

Seeing this shift too?

Be sure to read this week's newsletter to learn how to leverage partnership to drive AI search visibility. 👇

I’ll be honest: when ChatGPT started recommending me as a “top fractional CMO for tech and AI startups,” I had to screenshot it and stare at it for a 

Open article: How I Cracked AI Search Visibility Without Spending a Dollar on Ads by Lillian Pierson, P.E. • 7 min read

How I Cracked AI Search Visibility Without Spending a Dollar on Ads

There are things I deliberately don't share on LinkedIn. 

Here's what and why:

You would rarely, if ever, see photos of my kids here. 

You won't hear about my personal life beyond what's strategically relevant to my work. 

You won't see me in beachwear or poolside "hustle shots" from Thailand.

Here's why.

I've been working at or less than 30 hours per week for over a decade. Living in Thailand. Running a profitable business. Raising a family. And maintaining clear professional boundaries.

Some people post everything. Every workcation snap. Every picture-perfect family camera moment. Every "look how balanced I am" photo. And somehow try to pretend like it's about their business - that's their choice.

But I made a different one.

For me, authenticity doesn't mean oversharing. It doesn't mean pretending something is about other than it is. It means being intentional about what I put out there and why.

I keep my personal life personal because:

𝗦𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝘁𝗲𝗰𝘁𝘀 𝘄𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗺𝗼𝘀𝘁. My family didn't sign up for public exposure. They deserve privacy, even if I'm building in public.

𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹𝗶𝘀𝗺 𝘀𝘁𝗶𝗹𝗹 𝗺𝗮𝘁𝘁𝗲𝗿𝘀. LinkedIn isn't Instagram. Different platforms, different purposes. I'm here to share growth insights, not lifestyle content.

𝗦𝗶𝗴𝗻𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗶𝘀 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰. What you share shapes how people perceive you. I choose to be known for my frameworks, not my luxury villa overseas.

Does this mean I'm inauthentic? No. It means I'm strategic about my authenticity.

You can be real while protecting your relevancy. 
You can be transparent without being unfiltered. 
You can build trust without oversharing.

I share what serves the people I'm here to help.
Startup founders don't need to know what I ate for breakfast. 
They need proven playbooks that drive revenue.

So, while others are posting themselves in their latest low-cut shirt pretending to be working, I'm focused on delivering clarity, systems, and results.

That's my version of authenticity. Intentional. Boundaried. Strategic.

P.S. What’s one thing you deliberately don’t share online?

If you're a tech startup founder (pre-revenue to $4M ARR) and want predictable revenue growth without marketing chaos, this is for you.

Most fractional CMOs create strategy decks that sit in Google Drive. I'm different. 

I build growth systems that generate revenue.

Here are the first 3 things I do when I join a new client:

1️⃣ Revenue Audit in Week 1

I map every dollar you're spending on marketing back to actual revenue.

No vanity metrics. Just ROI clarity.

You'll know exactly what's working, what's broken, and where to double down.

2️⃣ Build Your Growth Engine Blueprint

Using proven playbooks (the same ones that helped clients like Future Sight AR land a $100K contract from a single LinkedIn post), I create your structured, repeatable system.

Not all clients need this, but when they do? It's transformational.

3️⃣ Quick Win Implementation

Within 30 days, we execute the highest-impact tactic.

Like Groe Solutions, who generated their first inbound leads in 60 days after we started working together.

Why this approach works differently:

As a licensed engineer turned growth strategist, I bring the precision of engineering to marketing.

My data-driven systems have generated $7M+ in direct revenue across real-world product launches.

The difference this makes:

→ You stop burning cash on tactics that don't convert
→ Your marketing becomes a predictable revenue driver
→ Growth happens systematically, not by accident

If this sounds like what you need:

You're between pre-revenue and $4M ARR.
You're tired of marketing guesswork and want systems that scale.
You need someone who builds, not just strategizes.

Comment “SYSTEMS” and I'll send you my 30-day Authority Positioning roadmap that shows you exactly how to build credibility for funding conversations and enterprise sales.

P.S. What's costing you more right now: bad marketing tactics or no marketing system at all?

Stop hiring marketers.

Start hiring GTM engineers.

Here's the difference:

Marketers ask: "What campaign should we run next?"
GTM engineers ask: "What system are we building?"

Marketers optimize: Ad copy, landing pages, email subject lines
GTM engineers optimize: Conversion architecture, attribution models, feedback loops

Marketers celebrate: Engagement rates, content performance, follower growth
GTM engineers celebrate: Pipeline velocity, CAC payback, repeatable acquisition systems

Marketers say: "Let's try this new tactic"
GTM engineers say: "Let's instrument this before we scale it"

Most founders hire marketing people when what they actually need is someone who can build a growth system that works like their product engineering team works.

With rigor. With measurement. With repeatability.

That's not marketing. That's GTM engineering.

And if you don't know the difference, you're about to waste 6-12 months and a lot of budget on tactics that don't compound.

P.S. Which side does your team lean toward: Marketer or GTM Engineer?

By Q3 of this year, I was already bringing in 5-figures in revenue from clients who discovered me via ChatGPT recommendations alone.

They didn't find me on Google. They didn't see my LinkedIn ad. They didn't attend my webinar.

They asked ChatGPT: "Who are the best fractional CMOs for tech startups?"

And ChatGPT sent them to me.

Why?

Because I rank #1 in AI search for high-intent B2B SaaS queries.

Not by accident. By system.

Over 12 months, I've systematically optimized for AI visibility: 
→ Tested what moves the needle 
→ Documented what works 
→ Built a repeatable framework

The results: 
✓ #1 rankings across ChatGPT, Claude, Perplexity 
✓ 3x qualified traffic in 5 months 
✓ Highest-quality leads I've ever received 
✓ Zero cold outreach required

Here's what most founders miss:

Your buyers stopped Googling. They're asking AI for recommendations.

If you're not visible there, you're invisible to your best prospects.

The good news? You don't need a marketing team or expensive tools.

You just need a system.

Want the exact framework I used?

Comment "PLAYBOOK" and I'll send you the complete case study showing: 
→ My 5-component AI visibility system 
→ 90-day implementation roadmap
→ What worked vs. what was wasted effort 
→ How to replicate these results

Your next best client might be searching right now.

Make sure AI sends them to you.

Your competitor just hired a GTM Engineer.

You're still trying to figure out if you need a CMO.

Here's what's happening right now:

Leading startups are using AI to automate positioning, predict customer behavior, and scale acquisition faster than traditional marketing teams.

While manual processes slow down growth, AI-driven systems operate continuously, testing, learning, and optimizing around the clock.

This shift isn't emerging. It's already underway.

I've helped generate $7M+ in revenue across AI-driven product launches for startups and Fortune 100 companies. I've trained 2M+ professionals in AI methods. 

I was named a Microsoft Regional Director for being among the top global tech strategists worldwide.

The gap between AI-driven growth and traditional marketing expands daily.

The companies moving now are building competitive startups that will be nearly impossible to overcome in 12-18 months.

If you're a tech startup founder ready to implement AI growth systems:

Comment "FUTURE" and I'll share the 30-day framework for building an AI-driven growth engine.

Don't let your competition automate you out of business.

Early on, I jumped into automation thinking speed was the answer.

I burned weeks building systems that didn't actually solve the problem.

It's through these experiences that I learned three non-obvious truths about navigating AI.

Truth #1: Audit before automating

Never automate based on vibes.

Use a framework like the Growth Engine Audit Gap Map (here: https://lnkd.in/gcR_JXCY ) to identify actual bottlenecks, not perceived ones.

Truth #2: Hire for AI skepticism, not AI enthusiasm

The best people on my teams are those who question AI outputs and push for validation.

They catch errors before they compound.
Blind enthusiasm leads to costly mistakes.
Healthy skepticism builds systems you can trust.

Truth #3: Document your experiments like a scientist

Track what you tried, what worked, what didn't, and why.

This becomes invaluable organizational knowledge that compounds over time.

Most teams treat AI like a shortcut. It's not.
It's a capability that requires deliberate building.

Here's the reality nobody talks about:

You'll feel slower before you feel faster.
You'll question whether it's worth it. Your team will too.

Push through.

The compound benefits after 6 weeks are undeniable, but only if you build systems, not chaos.

If you're building AI into your operations → Start with the audit.

👉 Download the Growth Engine Audit Gap Map to identify your real bottlenecks before you build another system: (here: https://lnkd.in/gcR_JXCY)

P.S. What's one automation you built that didn't work out the way you expected?

3 Brutal truths about AI that every operations leader lear

You don't just build marketing plans. You architect growth. 

That's what a client told me recently.

After taking his pre-revenue startup from complete marketing chaos to their first revenue milestone in under 60 days, he finally understood what sets strategic growth leadership apart from typical marketing execution.

Most fractional CMO engagements focus on hours or deliverables.

The real value lies in architecture, the engineered systems that transform early-stage startups into revenue-generating machines, predictably and without chaos.

That's exactly what happened with Tony's SaaS company. 

When we started, he had invested heavily in product development but had no clear system for acquiring customers.

Here's the 90-day playbook that changed everything:

Days 1-30: Built complete marketing foundation from scratch using structured, data-driven approach

Days 31-60: Grew user base 200x in first month + drove company past first revenue milestone

Days 61-90: Achieved 85x increase in website visitors + built repeatable growth systems

This isn't luck. It's what happens when you bring engineering precision to startup growth.

As a licensed professional engineer turned growth strategist, I focus on structured, repeatable systems that scale startup revenue predictably, without the founder burnout.

Most fractional CMOs operate like consultants. I operate like a co-founder of growth, embedded in your business, moving at startup speed, focused exclusively on what drives revenue.

Because here's the truth: Growth should be engineered, not forced.

Ready to turn your marketing chaos into a revenue-generating machine?

Comment "PLAYBOOK" below and I'll share the specific framework that drove Tony's 200x growth in 30 days.

There are two types of founders right now.

Those building AI into their growth stack.
And those about to get left behind.

I'm not being dramatic. I'm watching this play out in real time.

The founders who are AI-fluent?

They're scaling faster, spending less, and building systems that work without them.

The ones who aren't?

Still grinding. 
Still overpaying freelancers. 
Still stuck in execution mode.

Here's the reality:

AI fluency is now a competitive advantage.

And these 7 platforms are making it possible:

1. n8n

Flexible workflow automation. Build custom AI marketing systems without code.

2. Relay.app

Orchestrates AI agents for multi-step workflows.

Jacob Bank runs 40+ agents for lead scoring and content distribution.

3. Claude

Automates content creation while maintaining consistent brand voice.

Powers everything from summarization to optimization and even interactive tool building.

4. Zapier

Connects 8,000+ apps for AI-powered workflows.

5. MCP (Model Context Protocol)

A context protocol for complex, context-rich AI environments.

6. Gamma

AI design platform for modern consultants.

7. AgentKit

Build AI agents right inside ChatGPT, without a dev.

What this actually looks like:

A fast-growing AI consulting startup was spending $5,160/month on freelancers for content.

We built them a Claude MCP agent + n8n workflow.

Results in 2 weeks:

→ 8x faster content development
→ $5,160/month saved
→ Under 60 min/week of founder time
→ 43% engagement increase
→ 3.5x more qualified leads

This is what The Convergence is about.

Not hustle. Systems.
Not headcount. Intelligence.
Not burnout. Sustainable scale.

The gap between AI-fluent founders and those operating the old way is widening every month.

The tools exist. The playbooks exist. The results are proven.

The only question is whether you're building this capability or ignoring it.

♻️ Repost this if you're building AI into your growth stack.
🔔 Follow me, Lillian Pierson, for more AI-powered growth strategies.

P.S. Which of these 7 platforms are you already using?

7 AI platforms every founder should be fluent in

Many early-stage tech founders struggle with the same problem:

Building credibility fast enough to land enterprise deals, VC conversations, or strategic partnerships.

You've got the expertise. You've got the product.

But you're still the best-kept secret in your industry.

Here's what that actually costs you:

→ Enterprise prospects choosing competitors with better market presence
→ VCs passing because "we haven't heard of you"
→ Strategic partnerships going to founders with stronger visibility

The problem isn't your product. It's your positioning.

That's where The Authority Engine framework comes in.

This is the system I use to help founders go from unknown to recognized industry player in 90 days or less.

No BS and no vanity metrics. Just strategic positioning that opens doors.

Here's how it works:

1. Strategic Positioning and Narrative Building

→ Own a unique perspective in your space.

Stop being another SaaS founder and become THE voice on your category's biggest challenges. We craft your differentiated POV and build messaging that positions you as the go-to expert.

2. Content Engine Development

→ Deploy a multi-channel content system across LinkedIn, blogs, podcasts, and speaking engagements.

This creates omnipresence without burnout. Your insights show up where your ICP is already looking for answers.

3. Media and PR Strategy

→ Leverage guest posts, industry interviews, and conference talks to amplify your reach.

We position you in publications and on stages that your ideal clients already trust.

4. Community Building

→ Build a loyal audience through Slack groups, exclusive webinars, and ambassador programs.

This creates a network effect where your community becomes your distribution channel.

5. Co-Marketing and Partnerships

→ Collaborate with complementary brands to multiply your credibility and reach.

Strategic partnerships give you access to established audiences while positioning you as a peer to other industry leaders.

Why this works differently than random LinkedIn posting or generic PR:

Most founders treat thought leadership like a side hustle.

Post when they remember. 
Chase speaking gigs reactively. 
Hope someone notices.

The Authority Engine is a system.

Every piece of content, every partnership, every speaking opportunity builds on the last.

It's engineered to compound your credibility over time.

The result?

Founders who implement this framework see:

→ Inbound partnership requests from tier-1 brands
→ Speaking invitations without pitching
→ Investor conversations that start with "We've been following your work"
→ Enterprise prospects who already trust you before the first call

If this resonates:

You have a strong product but weak market presence.
You're losing deals to competitors with better positioning, not better solutions.
You need systematic authority building, not random content posting.

Let's talk about building your Authority Engine.

📩 Email me at lillian@data-mania.com now.

I just built a 25-page Deloitte-quality research report in 90 seconds.

Here's the workflow that's replacing days of manual
research with minutes of AI-assisted output:

The old way:

Most founders block out 2-3 days for market research.
Or hire a $2,000 freelancer.
Or try to cobble it together between client calls.

The new way:

Yesterday, I needed a comprehensive report on newsletter growth strategies.

I grabbed my coffee, opened my AI workflow stack, and had a publication-ready report 4 minutes later.

Not a rough draft. A full, structured, properly formatted research report.

Here's where most people mess up: They think "AI = magic." 

They type a vague prompt into ChatGPT, get mediocre output, and conclude AI is overhyped.

That's like using a Formula 1 race car to drive to the grocery store.

The real edge? Having a system.

I don't just "ask AI" for a report. I engineer the inputs so the output is bulletproof.

Before I run deep research, I prep 6 critical elements:

1. Goal - What am I trying to achieve?
2. Context - Why does this matter right now?
3. Sources - Where should the AI pull from? (I get these from Claude)
4. Report Inclusions - What specific sections do I need?
5. Research Plan - How should this be structured? (I bring this from Gemini)
6. Report Format - What's the final output structure?

Then I copy the entire prompt into ChatGPT, turn on deep research, and hit run.

After 4 minutes: 25-page research report, properly cited and logically structured.

But I don't stop there.

I paste the whole thing into Gamma, hit "summarize long text or document," select my theme, tell it I want 20 cards, and hit generate.

Total time: 90 seconds of active work. 4 minutes of AI processing.

This is what I mean by "The Convergence."

It's not about replacing humans with AI. It's about amplifying what startup teams can do when they combine strategic thinking with intelligent systems.

Most startups are stuck in the old playbook - hiring slow, executing slower, wondering why growth feels like chaos.

The visionaries? They're building systems that multiply their output without multiplying their stress.

That's the future of growth. And it's already here. Most people just haven't figured out the system yet.

♻️ Repost this to help founders build AI research workflows.
🔔 Follow me, Lillian Pierson, for more AI-powered efficiency systems.

P.S. What research tasks are still taking you days that could take minutes?

The 3-step GTM audit I run for every $1-5M ARR SaaS I work with.

Takes about 2 weeks. Saves founders 6-12 months of guessing.

Here's exactly what I do:

Step 1: Map what actually exists (not what should exist)

I don't ask the founder what their GTM looks like.
I audit the data.

Questions I'm answering:

→ Where do leads actually come from? (Not where they think they come from)
→ What's the real conversion rate at each stage? (Not the hopeful CRM number)
→ Which channels drive pipeline vs. which drive vanity metrics?
→ Can they connect spend to revenue? Or is it "we think this works"?

Red flags I look for:

→ Multiple definitions of the same metric across different people
→ Attribution set to "first touch only" (which means they're optimizing for strangers, not buyers)
→ No clear line from campaign → lead → opportunity → close

Step 2: Identify the engineering gaps

Most teams have tactics. Few have systems.

I'm looking for:

→ Do they have measurement infrastructure or just dashboards?
→ Can they run an experiment and actually know if it worked?
→ Is there a repeatable playbook or are they reinventing the wheel every quarter?
→ Do they know their unit economics or are they "pretty sure it's profitable"?

The gap is almost always the same:

They're running marketing like a creative team when they need to be running it like an engineering team.

Step 3: Prioritize the rebuild

I don't try to fix everything at once.

Here's the order that actually works:

First: Build measurement architecture (attribution, tracking, clear definitions)
→ You can't optimize what you can't measure

Second: Map the real customer journey (data-backed, not assumed)
→ You can't build a system if you don't know the actual path

Third: Create one repeatable conversion system
→ Master one channel/motion before adding complexity

Fourth: Add volume
→ Only after you know the math works

Most founders want to skip to step 4.
That's why most founders waste budget.

If you're between $1-5M ARR and your GTM feels like chaos, it's probably because you skipped steps 1-3.

Want a teardown like this for your business? DM me 'GTM' and I'll send you the full framework.

Most early-stage tech startups track the wrong metrics.

Impressions. Engagement. Followers.

None of that pays the bills.

Here's what I believe:

If a marketing strategy doesn't directly drive the pipeline, it doesn't belong in your playbook.

This is the foundation of The Convergence. 

We reject vanity metrics and growth theater. 
Every strategy, every campaign, every dollar spent needs a clear line to revenue.

Why does this matter?

Because early-stage founders don't have time or runway for marketing that "builds awareness" without a clear path to conversion. 

You need systems that generate real traction. 
Predictable lead flow. Qualified opportunities. Actual contracts.

Revenue-first isn't just a philosophy. It's survival.

When I work with tech startups, the first thing we do is audit every marketing activity through one question:

𝗗𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗱𝗿𝗶𝘃𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗼𝗿 𝗷𝘂𝘀𝘁 𝗺𝗮𝗸𝗲 𝘂𝘀 𝗳𝗲𝗲𝗹 𝗯𝘂𝘀𝘆?

Most of the time, 60% of what they're doing gets cut immediately.

What replaces it:

→ Structured playbooks with proven ROI
→ Content that converts, not just engages
→ Channels that actually generate qualified leads
→ Systems that scale without chaos

This is what sustainable growth looks like. 
Not glossy strategy decks. Not guesswork. 
Just proven frameworks that map directly to revenue growth.

If you're an early-stage founder who's tired of marketing that doesn't move the needle, this is your reminder: demand more from your strategy. Demand revenue.

Let's audit your marketing through a revenue lens.

📩 Email me at lillian@data-mania.com with subject line "REVENUE AUDIT"

P.S. What percentage of your marketing budget actually drives the pipeline right now?

“AI sped up our execution, but shifted the bottleneck to validation. We now spend 30% building but 70% checking.”

Too many teams think “deploying more AI” = “faster outcomes”. 

The real leverage is in constructing validation nodes, aligned workflows and orchestration systems that keep AI output strategic and reliable.

Want to learn how to shift from tool-stack overwhelm to agent-workflow mastery? 

Read the full interview on The Digital Project Manager. 👇
#AIMarketing #ProjectDelivery #Leadership

Brand & Content Strategist | AI-Enhanced Storytelling & Data-Driven Campaigns

There’s something about a great analogy that quietly shifts how you see your work… ✨

In our conversation with Lillian Pierson, P.E., she offered a framing for AI that immediately stuck with me — one that treats it less like a replacement for expertise and more like a teammate that relies on our strategic direction. 🤝

It’s a refreshing reminder that AI doesn’t erase the role of project leadership; it sharpens it. Lillian dug into how PMs can provide the context, oversight, and critical thinking that AI simply can’t replicate, while still using these tools to accelerate the work that bogs teams down. ⚙️💡

If you’re thinking about how to build a more grounded, human-centered relationship with AI in your delivery workflows, her full Q&A is a great place to start.

 👉 https://lnkd.in/gFXwETfN

#ProjectManagement #DigitalDelivery #AI #Leadership #FutureOfWork

Random GTM bullets while startup teams keep treating growth like a creative project:

Your growth team shouldn't look like an ad agency
→ It should look like your engineering team

You don't need more campaigns
→ You need one system that compounds

"Let's try this tactic" is not a strategy
→ "Let's test this hypothesis with clear success metrics" is

Attribution isn't a nice-to-have
→ It's the foundation of every decision you'll make

Your customer acquisition cost should be a number you know
→ Not a number you're "pretty sure is around..."

Repeatable > Remarkable
→ Every time

If your marketing team can't explain the conversion math
→ You hired the wrong marketing team

Good marketers run campaigns
→ Great GTM engineers build systems

The question isn't "what should we post next?"
→ It's "what system are we optimizing?"

Measurement architecture comes before media spend
→ Otherwise you're just gambling with a bigger budget

Most "marketing problems" are actually systems problems
→ Solved by engineering thinking, not creative thinking

If you can't connect a dollar spent to a dollar earned
→ Stop spending until you can
P.S. What’s the one metric you track daily that actually moves revenue?

A few months back, ChatGPT started recommending me as a fractional CMO when someone asked for "top experts in GTM strategy for AI startups."

I had to screenshot it and stare at it for a minute.

Not because I doubted my work. I've partnered with over 100 companies- AWS, IBM, SingleStore, BMC Software. 

I've built marketing systems that drive real revenue for early-stage startups. 

But here's what threw me: I didn't optimize for this.

I wasn't running an "AI search visibility campaign." I wasn't hiring an SEO agency to plant keywords across the web. 

I was just doing what felt right - guesting on podcasts, hosting founder interviews for my newsletter, showing up in conversations where my expertise mattered.

Then I realized, AI search engines weren't just finding me through my blog. 

They were finding me through transcripts. 
Through interview mentions. 
Through dozens of conversations across different domains where I explained my frameworks in my own words.

I had accidentally engineered my way into AI search dominance by treating partnership marketing like a distributed system problem.

Here's what I mean: 

Every podcast creates a branded mention on a unique domain. 
Every interview includes your methodology, your client results, your specific expertise. 

When multiple sources say similar things about you, AI search treats it as pattern recognition. Social proof at scale.

I wasn't trying to rank. I was building relationships. The ranking was a byproduct of doing the work consistently.

If you're trying to crack AI search visibility, stop thinking about keywords. 

Start thinking about where your target buyers already spend time... and show up there. 

Consistently. With something worth saying.

The system works when you treat it like a system.

P.S. If you want to learn exactly how to build AI-search visibility like this for yourself, I dropped a link to my AI Search Rank course in the pinned comment.

I spent $3,847 on AI tools that ended up in my "Graveyard" folder.

Here's my honest review of what didn't work, and what I use instead that actually delivers:

🪦 Canva AI - Looks amazing in theory, even has a Claude MCP integration. But here's the problem: when you feed it your data to visualize, it runs its own language model over your source content and completely mangles it. Canva is a visual tool, not a writing tool.

What I use instead: Dedicated data viz tools like Gamma, or Claude artifacts for quick visuals that don't rewrite my content.

🪦 CastMagic.io - Promises to be the end-all solution for podcast repurposing. The interface is so clunky, it's actually faster to just build n8n workflows yourself.

What I use instead: Custom n8n workflows for control. Though I'll give them credit: their "free transcripts for life" is exactly what I use them for now.

🪦 Wispr - Voice-to-text across your entire computer. Sounds cool until you realize Siri already does this for free.

What I use instead: Built-in OS features. Why pay for something that's already there?

🪦 Perplexity - Good for quick searches, but if you can't build projects, MCPs, and agents, then just having access to the latest models isn't enough value for me. Plus, Deep Research runs circles around their research capabilities.

What I use instead: Claude with projects and MCPs for customizable workflows + ChatGPT's Deep Research when I need thorough, benchmark-grade analysis.

🪦 Heygen - Those AI avatars still look too robotic for serious business use in my opinion.

What I use instead: Real video or high-quality screen recordings with voiceover.

🪦 ElevenLabs - The voice outputs don't actually sound like the voices they're trained on, and those "emotional inflections" just make it worse.

What I use instead: My own voice or professional voice actors for important content.

The lesson?

Just because it's AI-powered doesn't mean you should use it.

As someone who's built marketing automation systems for Fortune 100 companies and startups alike, 

I've learned that the best AI tools are often the boring ones that just work consistently.

Your AI stack should make you more efficient, not give you more subscriptions to manage.

♻️ Repost this to help founders avoid AI tool overwhelm.
🔔 Follow me, Lillian Pierson, for more honest AI tool insights.

P.S. What AI tool are you paying for but barely using?

taplio

Lillian Pierson, P.E.'s Linkedin Analytics