On Saturday evening, I came across a video that genuinely unsettled me.

It was a 2023 interview where journalist Nilay Patel pressed Substack CEO Chris Best with a deceptively simple question: If somebody shows up on Substack and says all brown people are animals and they shouldn’t be allowed in America, you’re going to censor that (right)?

Chris Best’s response: “So we do have a TOS that has narrowly prescribed, uh, things that are not allowed.”

That’s it. The whole exchange is painful to watch. Kudos to Nilay Patel for standing his ground.

That video sent me down a rabbit hole. Turns out, Substack has had a documented Nazi newsletter problem since 2023, from newsletters using overt Nazi symbols and trafficking in Great Replacement theory.

A timeline worth knowing

n November 2023, journalist Jonathan Katz published a piece in The Atlantic titled “Substack Has a Nazi Problem.” It documented newsletters openly using swastikas and promoting white supremacist ideology. Within weeks, nearly 250 Substack writers signed a collective protest letter questioning why leadership chose to promote and allow the monetization of white nationalist sites while still moderating spam and pornography.

Co-founder Hamish McKenzie’s official response, issued on December 21, 2023, was that Substack would continue to platform and monetize Nazi newsletters because “censorship makes the problem worse” and “open discourse” is the most effective way to “strip bad ideas of their power.” Several prominent writers left the platform in protest. Others defended the decision as a necessary commitment to free expression.

This is the statement they made:

Statement from Substack management - Reddit

In early 2024, after mounting backlash, Substack removed five publications that endorsed Nazi ideology, but explicitly stated they would not change their content policies and would not proactively search for or remove neo-Nazi or far-right extremist content. Co-founder McKenzie minimized the impact of those removals, noting the accounts had no paid subscribers and a combined total of roughly 100 active readers. The message was clear: this was optics management, not a values shift.

By June 2024, nearly 40 fascist, white supremacist, or far-right publications were identified to be still operating and actively monetizing on the platform. Far-right authors had simply learned to use Substack’s own terms of service as a guide, rebranding their rhetoric to avoid explicit calls for violence, while continuing to use Substack’s payment and recommendation infrastructure to grow their movements.

Where Substack stands today

In January this year, Substack banned several accounts that were against its policy (mainly those that were creating fake paid subscriptions to boost their ranking on the best seller boards.)

Source: Chris Best Substack

Substack continues to stand against those that trample the freedom of speech and expression tenets. This was their statement when journalists were arrested in January:

Source: Substack

Source: Chris Best's Substack

But despite that the hate continues. In Feb 2026, a coalition of women and LGBTQ+ writers released an open letter documenting what they called a "systemic failure" to protect them from abuse including rape threats, racial slurs, and deepfake pornography threats flooding their inboxes and comment sections. Trolls were easily creating new accounts to circumvent blocks. Substack's reporting systems were described as fundamentally broken. UK MP Joani Reid announced plans to contact Substack, stating that antisemitism and gendered violence were "spreading with impunity" on the platform.

Why I am a hypocrite

I am writing this piece on Substack. I am fully aware of the irony. Moreover, I am still on Meta channels (Facebook, Instagram, WhatsApp) despite them also dialing back their policing on hate speech.

Meta announced last year that it is abandoning independent fact-checkers in the U.S., replacing them with a “Community Notes” model, and has lifted restrictions on topics like immigration and gender identity, framing this as undoing “mission creep” in its moderation systems.

So yes, I am a hypocrite. But I stay on Meta for a purely personal reason: living far from friends and family, it’s my primary way to stay connected to them. Even though I barely use Facebook or Instagram, I have not yet left it. The stakes of leaving are higher, and I am honest enough to admit that.

My footprint on Substack is much smaller, making it easier to leave with much lower stakes. This same logic is why I never started on X or engaged with Grok, I simply do not want to begin building on a platform that does not believe in moderating opinions that cause hate, instigation of violence, or the belief that one class of people is superior to another.

Why I am leaving

Let’s be honest. I am a small guppy in this pond. I have a mere 200 subscribers and it doesn’t matter whether I stay or go. But I feel deeply uncomfortable being part of a system where a privileged tech bros allow for harmful content to exist without any real pushback.

Hate is such a powerful emotion that causes adverse actions and real harm. Whether that is hate against brown people or Jews or Palestinians or LGBTQ+ or women or even the denial of the Holocaust, hate causes real harm. Not taking a stance against it allows the hate to exist.

I find it difficult to justify staying on a platform that is okay propagating it. Hate in most cases is directed at minorities. Hate is mostly about punching down. And that is not freedom of speech or expression rather weaponization of a platform.

Where does the line lie between freedom of speech and the ability to cause harm to people, and what role do content platforms play in this? Substack claims “we let the readers decide what they want to read,” but at the same time, they’re quite comfortable making money off newsletters that advocate or apologize for genocide and violence.

I do agree on the tenet that freedom of expression is either absolute or it doesn’t exist at all. But just like our freedom of expression doesn’t allow us to murder someone, doesn’t allow us to use physical violence — why do we allow the propagation of violent ideals? Why is punching down acceptable in a society where it could eventually lead to violent action?

No atrocity in history started with someone immediately deciding to expel violence on another person. It started with the ideals. It started with the belief that they were superior, that they were in the right. This belief was then propagated across echo chambers until those ideals became actions.

For me, the difference between Substack and other flawed platforms really lies in the ability to acknowledge that there is a challenge. If the CEO doesn’t even want to acknowledge that this is a problem, that’s the core of the issue. And for me, that’s not good enough.

There are two ways to fight hate: engage in dialogue and educate, or walk away. The problem with dialogue is that the people peddling hate are seldom willing to hear another point of view. Given the current political climate and the destruction we are watching unfold in the world, it feels hollow to continue on a platform whose key priority is protecting the right to express over human life and harm.

So I am walking away.

I mainly write on LinkedIn and Substack (Medium too, but it is mainly a rehash of my Substack content with a new title.) What I find interesting is the contrast between the content that works on LinkedIn versus Substack. Being a content marketer, I aggressively track the metrics of engagement and growth in followers/subscribers across both platforms.

The finding that surprised me most when I ran this audit was just how different it is from LinkedIn. Substack still accepts a lot of generic advice via notes, which LinkedIn has definitely stopped encouraging or rewarding. That contrast alone made pulling the data worth it.

So here it is. An analysis of my 108 notes and this is what I found.

How I organize my notes

I categorize each note I create based on three elements:

Theme: Marketing theory, Opinion, Personal Experience/Story, AI theory, Observation, Other

Stance: Contrarian, Reflection or Reflective, Regenerative
Note: You can read about Contrarion vs Reflection content here -I analyzed my LinkedIn posts

Media: Link, No media, Image, Meme, Video

This classification helps me create notes that match my positioning and also helps me discover what types of notes work better than others. It is a simple system, but running it across 108 notes reveals patterns you cannot see post by post.

The honest caveat before the data

Every time I run this exercise, the imposter syndrome looms large. I am afraid of failing or performing poorly or just chasing algorithmic clout. There is something slightly absurd about analyzing your own content the way you would analyze a client’s content (you see the gaps clearly, and the gaps are yours.)

I am sharing this data because it is useful, not because I have solved the puzzle.

Five learnings from 108 notes

1. 42

Maybe Douglas Adams was onto something when he wrote The Hitchhiker’s Guide to the Galaxy and claimed 42 was the answer to the Ultimate Question of Life, the Universe, and Everything.

In my case, 42 words is the median word count of my top 15 performing notes. I have excluded some outliers (which I will explain further below.) I found that the length of notes matters. The 21–50 word range is my grow-th (pun intended) engine.

Long notes are not a death sentence, but only for one content type: personal stories. My 100+ word notes that perform well (25–52 likes) are all raw personal stories: quitting my job, financial anxiety, the Spryngbase month-2 update. The content earns the length.

2. When you write Marketing theory, be Contrarian

This is the most actionable single fix in the dataset. Marketing theory + Contrarian averages 10.11 likes. Marketing theory + Reflection averages 6.36 likes. Same content type, different tone, 59% gap. The audience responds when I challenge something, not when I guide them.

“Here’s how to think about your ICP” lands worse than “Most B2B teams treat their ICP like a time capsule.”

Note: You can read about Contrarion vs Reflection/Reflective content here -I analyzed my LinkedIn posts

3. Likes, comments, and subscribers come from three different kinds of posts for me

In my case, they are not the same metric and they should not be optimized the same way:

• Likes come from AI theory and insight-dense notes

• Comments come from personal vulnerability with specifics — job exit, financial anxiety, Spryngbase chaos. My top 2 comment notes are both raw “here’s what’s actually happening” posts, not marketing theory

• Subscribers come from community/connection posts and AI theory hooks. One “connect me with” note drove 69 subscribers alone

I just don’t want to overuse one theme and let the algorithm decide my content purely. I want to experiment with different elements of my positioning. But conflating these three metrics is leaving all of them on the table simultaneously.

4. “Most [group] [misconception]” is my most reliable opening formula

Four notes open with “Most” and average 12.75 likes. “Most early tech founders treat Sales & Marketing like a mysterious engine.” “Most founders and marketers need 2–3 AI workflows, not 15 tools.” The structure is replicable: name the group, name the wrong belief, land the diagnosis in 35–50 words. I have used it 4 times. That underuse is its own data point.

5. Engagement and views are softening — but the cause is content mix, not content quality

My last 20 notes averaged 8.1 likes versus 9.55 for the prior 20. The reason is visible in the data: more Opinion and Observation notes (my two weakest themes at 6.83 and 5.20 average likes) and fewer AI theory notes in recent months. The fix is simple, write more of what already works.

I know, however, from being active on LinkedIn that “what works” keeps changing. So I don’t want to go down the rabbit hole of creating the same type of content indefinitely.

The desire to experiment and create new things is real. The data is patient about this. The content quality is there. The mix can be better.

A note on measurement

I am not sure how many people even think about their content in these metrics. For most people it is just about being consistent, and that is completely fine. Not everything needs to be analyzed so intently.

I do it because it is a professional hazard of being a content marketer. Measurement is everything.

In fact, my most valuable content type is the one I post least

AI theory + Reflection is my best-performing combination at 16.2 average likes across only 5 notes. Compare that to Marketing theory, where I have published 27 notes averaging 7.11 likes. Most of my volume is going toward my third-best content type.

Why haven’t I leaned into it more? I just don’t want to let the algorithm purely dictate my content. AI is a trend for the next few years to come before it becomes normal — but my personal brand and positioning shall remain. The Spryngbase work gives me an endless supply of AI theory material. I am sitting on it and not always using it. That is a deliberate choice, not an oversight.

To try and balance out more with content that works and that doesn’t, and to try and understand what your subscribers want from you by directly talking to them — that is the actual work underneath the numbers.

108 notes just signals consistency. For me it is just about keeping on going and trying out different things.

If you want a head start

If you are building a B2B SaaS or AI presence on Substack Notes, these 13 templates give you the framework without the reverse-engineering. Based on the patterns above, for just $1. The note that brought me 120 subscribers is in there too.

Get the templates

The world will be better tomorrow.

This is a conversation space exclusively for subscribers. I’ll post questions and updates that come my way, and you can jump into the discussion.

Join chat

How to get started

1. Get the Substack app by clicking this link or the button below. New chat threads won’t be sent sent via email, so turn on push notifications so you don’t miss conversation as it happens. You can also access chat on the web.

Get app

2. Open the app and tap the Chat icon. It looks like two bubbles in the bottom bar, and you’ll see a row for my chat inside.

3. That’s it! Jump into my thread to say hi, and if you have any issues, check out Substack’s FAQ.

“Money can definitely make anyone’s vision blurry.”

I said this to my co-founder somewhere between week three and week four of conversations with a government entity (in Belgium) about AI adoption.

Story-time!

Three weeks ago, Spryngbase (the company I am building/co-founding/developing - choose your verb haha) spent a significant chunk of time in those conversations. The management was excited. The employees however were resistant. And somewhere amidst the multiple discussions, we realized we were being hired to be something we had explicitly decided not to become.

A change management consultancy.

The marketer in me was screeching. Abort! Abort! This is not our positioning. Our positioning: we help SMEs understand AI by bringing employees along for the journey. The focus was on empowering employees with knowledge, keeping it vendor-agnostic, making the whole thing feel less like a corporate mandate and more like a skill they actually want. Change management consulting? That’s a different job. A respectable one. Just not ours.

And yet, the co-founder in me was leaning toward yes. Every cent matters in the first year.

Subscribe now

Money, money, money, ain’t it funny… in a rich…

What makes this dilemma so insidious? The basic fact is that it would be a rational decision to take the contract. It came from our network, so sales overhead was low. The revenue could cover a month of runway. And honestly? We were curious. Could our thinking stretch to fit this context, even if the client wasn’t a perfect fit?

We mapped the scenarios.

Option 1: Take the contract, deliver AI consulting, get cashflow.
Option 2: Stay true to our product, walk away, protect positioning.
Option 3: Build some hybrid solution that magically does both (startup delusion, my favorite flavor.)

The real choice is always binary. You’re either building something repeatable, or something custom. Trying to combine both creates chaos. Confused, we turned to LinkedIn and Substack for help.

Some incredible feedback from the LinkedIn and Substack community members got us re-evaluating our decision. Multiple internal discussions ensued. Option 3 it is. We framed it as a controlled experiment. An outlier this deal shall be, not a pivot.

(Note: I have blurred the names and photos for privacy reasons but if you would like to show some appreciation to our advisors from our social media community feel free to do it here - LinkedIn & Substack)

Should I stay or should I go?

Most startup advice bifurcates into two camps: stay focused or take the money and iterate. Neither is useful when you’re sitting across from an enthusiastic client who genuinely believes you can help them.

The sharper question however is this: How much does this revenue cost us in positioning clarity?

This question acts as an internal compass that tells your team what you are, what you’re not, and why that distinction matters when the next decision arrives.

If you’re a marketer reading this and thinking “I don’t have a startup, this isn’t for me.” I’d push back on that.

How many times have you been asked to adapt messaging for a customer success story that doesn’t fit your positioning, because the founder needed the case study? To build a campaign targeting an audience segment you’d never prioritize, because this quarter’s numbers needed padding? To write sales enablement material for a product vertical that’s strategically irrelevant, because someone upstairs saw an opportunity?

The pressure to compromise brand consistency for short-term revenue is not a startup-specific experience.

And I empathize with both sides, genuinely. Founders aren’t wrong to need revenue in year one. Marketers aren’t wrong to protect long-term brand coherence. The conflict is (fortunately or unfortunately) the structural feature of early-stage business that nobody warns you about with enough specificity.

Yes, and?

When we stripped away the noise and the guilt (yes, guilt, because this felt like it contradicted something we’d written down together as founders), we realized we were subconsciously running three tests. We’re making them explicit here, because they’re more useful than the binary everyone else is offering.

Test 1: The Fit Test. Does this client’s core problem align with the problem we set out to solve? For Spryngbase, the answer was a qualified no. Employees resistant to change imposed from management represents a structural problem. Not really a technological one.

Test 2: The Direction Test. Does solving their problem move us toward or away from where we want to go? We could see the shape of a solution, essentially something that eased the change management burden, bridged excited management and resistant teams. We could build that. But that company would be a change management consultancy with an AI wrapper. Know your specific distortion risk before you start.

Test 3: The Scale Test. If we said yes to ten clients like this, what company would we be? One misaligned client feels manageable. Ten of them? Not really. This choice, compounded over time, becomes your positioning whether you chose it or not.

Run the Scale Test early. It’s surprisingly good at cutting through the noise.

A bird in the hand

We’re taking the engagement. It covers runway for a month, it came from trust, and we’re genuinely curious about what we’ll learn from a client at the far edge of our positioning. But we’re doing it with our eyes open (extremely cognizant of the risks). We have also considered the cognitive overhead of working with a non-ICP client while simultaneously trying to find the ones who actually fit.

The bird in hand is real. We’re glad to have it. Although, we’re not pretending it doesn’t come with strings.

Spryngbase is building the simplest way for European SMEs to adopt AI by empowering the employees who’ll actually use it. This is Episode 01 of the Spryngbase Diaries, one messy decision at a time.

I’m a Marketer and even I think LinkedIn is cringe.

I post maybe 2-3 times a week when every LinkedIn guru insists I should be posting daily or at least 4 times a week. I’ve also succumbed to ‘writing’ (generating?) AI slop that made me wince when I reread it. I am, in many ways, part of the problem I’m about to describe.

The thing about LinkedIn is, it keeps me coming back. And if you’re a founder who’s been avoiding this platform because the whole thing feels performative and slightly unhinged, trust me I get it. I really do.

This is a guide for people like us.

Subscribe now

I Hate You/I Love You (LinkedIn)

LinkedIn and I have a love-hate relationship. Let me be specific about what bothers me:

1. The AI slop epidemic. I wrote one of these posts myself, a post about B2B startups pouring resources into marketing. It was fluff. Some of the experiences I had, did form the basis of this post but overall it was a whole lot of words, not a lot of substance. I caught myself becoming the thing I mock, and it was humbling. The results reflected it.

2. The excessive exposure. People sharing things that simply don't belong in a professional environment. I'm not talking about vulnerability here, but rather about people oversharing and somehow linking it to their profession. There's a difference between being honest about your struggles and treating your feed like a Twitter feed.

3. The grind culture worship. “I wake up at 4am and work 18-hour days and here’s why you should too.” The hustle brags. People using burnout as a humble brag. I have news for the posters who do it: IT’S NOT INSPIRING! Abort! Abort!

You can totally believe that this is the right way for you to work but bragging about it on a social media platform? Yeah! No! Don’t do it!

And yes, the classics from r/LinkedInLunatics: the “I fired my best employee and here’s what they taught me” stories, the humble brags about private jets while claiming to be “just like you,” the engagement bait that insults everyone’s intelligence.

I could go on. You know what I’m talking about.

The Climb (Founders)

Founders have it particularly hard. The most common barrier I see is resistance to be vulnerable.

Founders are generally willing to talk about their product. Their brand. The company mission. But their daily activities? Their actual thought process? The failures and pivots and moments of doubt? That is trickier to share.

The paradox is that this is exactly what works on LinkedIn. LinkedIn is a social media platform where people want to learn more about you. Not your product features. Not your company’s latest press release. You.

This is difficult for most founders. The emotional barrier for founders is being honest and candid (truly candid). The practical barrier is being consistent, maintaining a streamlined way of extracting content from your actual life, and holding yourself accountable to showing up.

That’s astonishing when you think about it. And terrifying. And why so many founders either avoid the platform entirely or retreat into safe, forgettable corporate-speak that generates zero engagement.

The Real Thing (Great Founder Brands on LinkedIn)

There are people with engaging personal brands, these are people whose content I genuinely look forward to seeing. What separates them from the lunatics?

Yasser Elsaid is a great example of how to build-in-public while making people excited about your company’s journey. He shares his goals, his team’s updates and his own experiments.

Marie Martens does build-in-public content about her brand’s journey, from growing it bootstrapped with a small team to reaching $4million ARR. It’s real, and you learn something from every post.

Amlan Suryabanshi focuses on consistency and his personal journey. It’s simple. It’s engaging. It’s showing up regularly with honest observations.

The common thread? Honesty, consistency, and real substance over performance.

None of them are trying to go viral. None of them are using engagement bait or posting motivational platitudes. They’re just... being themselves, systematically, over time.

It sounds simple. It’s not.

I Confess

I should be honest about where I actually am with all this.

I am not consistent. I post less than I should, and I know it.

I use AI to help me (a lot!) But I’m also cognizant of making sure I continue to write myself, to keep my own thinking sharp, to use the words and phrases that are mine. AI is a tool, and a thought partner, but it is most definitely not a replacement for having actual thoughts.

It’s not always easy to come up with new ideas. I try to use different sources for inspiration, and I document every idea that sparks something in me (even if I don’t know what to do with it yet.)

The content extraction process is ongoing and imperfect.

Right now, I’m working on building the personal brands of my co-founders at Spryngbase alongside my own. It’s a strange position to be in tbh, helping others show up authentically while still figuring out my own approach. But maybe that’s the point. Nobody has this fully figured out.

Take Action

LinkedIn is cringe when people aren’t being real.

The humble brags, the AI slop, the grind culture worship, the excessive exposure—it all stems from the key idea of being impressive rather than honest.

But if you show up honestly (even if it is inconsistent) that is what will set you apart. The best content creators are not necessarily more talented at creating content; rather, they are more willing to be honest, vulnerable, and consistent.

I’m still working on this. You probably are too.

If you’re a founder trying to figure this out, I’m doing the same thing publicly at Spryngbase. No promises I’ve cracked the code, but at least we can be inconsistent together.

You’ve seen it. The LinkedIn comment that reads like a chatbot had a stroke. The Reddit reply that’s 400 words of nothing. The cold email that is so obviously AI-generated that you delete it before the second sentence.

We’re drowning in AI-generated content that sounds exactly like… well AI-generated content. Prospects know it. You know it. We’re all exhausted by it.

The AI Sales Lab

I test every AI tool and tactic for sales. I share what actually moves the number, not just what sounds good on LinkedIn.

By Florian | The AI Sales Lab

Florian and I have spent months experimenting with AI in go-to-market functions. He’s been building sales story systems. I’ve been working on brand narratives. This article is what we learned when we stopped blaming the AI and started fixing our process.

Most AI-generated outreach fails for a simple reason. The AI has no context about your unique value proposition, your customer’s actual pain points, or the competitive landscape you operate in.

You’re essentially asking a writer to craft compelling sales messages about a product they’ve never seen, for customers they’ve never met, in a market they don’t understand.

The output reflects exactly what you’d expect from that scenario.

AI tools today are trained on vast datasets of “good” content. They basically reproduce patterns from that training data. Every tool converges toward the same style, the same structure, the same voice. Uniqueness diminishes. Differentiation disappears.

When everyone uses the same AI to create the same type of content trained on the same dataset, everything starts sounding identical.

Foundation First: Build Your Story Before You Scale It

Before you write a single AI prompt, you need a coherent story system. We use Donald Miller’s StoryBrand framework as our foundation because it forces clarity about who you serve and why you matter.

The framework is this:

Let’s translate that into practical terms:

• Character: Your customer (not you, not your product)

• Desire: What they want to achieve (internal, external, or philosophical)

• Villain: The specific force causing their problems

• Guide: Your brand (showing proof points and category expertise)

• Plan: Your methodology for solving their problem

• Action: Clear next steps you want them to take

• Failure: Consequences of inaction

• Success: Outcomes when they follow your approach

This is an example for Substack filled out:

This becomes your narrative anchor. Every piece of AI-generated content should reinforce this story, not contradict it or dilute it.

Context is Everything: Build Your 3P Engine

Stop feeding AI generic keywords and vague instructions. Build a contextual foundation that gives AI the strategic reasoning it needs.

Your 3P Engine consists of:

Pain: The strategic pain points your customers face. Not surface-level irritations. Deep, costly problems that executives lose sleep over. Include the “why now” behind these pain points. What’s changed in their market, their operations, or their competitive landscape?

Persona: The psychological drivers of different buyer roles. A CFO cares about risk mitigation and cost optimization. A VP of Sales cares about ramp time and pipeline predictability. A CMO cares about attribution and brand equity. Don’t give AI the same messaging for different personas.

Proof: Your micro-case study database. Build a repository using this formula: [Company Type] + [Specific Challenge] + [Your Solution] + [Measurable Outcome] + [Timeframe].

Example: “Series B SaaS companies struggling with 45% sales rep churn implemented our onboarding system, reduced churn to 12% within 6 months, and cut ramp time from 4 months to 6 weeks.”

These become your reasoning foundations that help AI understand which pain points matter most for which personas, and which proof points will resonate in specific contexts.

Structure: Constrain AI With Proven Frameworks

Creativity without constraints produces chaos. Force AI to use proven narrative structures instead of freestyle generation.

For outbound emails: Use the Context-Value-CTA framework.

• Context: Trigger observation that shows you understand their situation

• Value: One specific pain point you can solve

• CTA: Permission-based ask, not aggressive pitch

For discovery calls: Use the Hypothesis Model.

• Take their stated benefits and invert them to find hidden problems

• “You mention fast deployment. That suggests you’ve dealt with implementation delays before. What went wrong?”

For product demos: Use Tell-Show-Tell.

• Tell: Recap their specific pain point

• Show: Demonstrate the exact feature that solves it

• Tell: Recap the business impact of this solution

These frameworks act as guardrails that keep AI focused on proven conversion patterns rather than wandering into generic territory.

Scale Through AI Interviews

Once you have your story foundation, your 3P engine, and your structural frameworks, you need a repeatable process for creating content at scale.

Templates produce template-sounding content. Instead, build an interview system.

Feed your AI project all the background context: your story system, your 3P engine, your frameworks, your proof points (and other relevant documents such as positioning, brand book, persona profile etc.) Then instruct AI to interview you about the specific content you’re creating.

Force AI to ask 5-7 strategic questions about the topic. Answer those questions in your own voice. Type your answers or record them as voice notes and transcribe them.

This approach captures your actual thinking, your unique perspective, and your authentic voice. AI then structures that raw material using your frameworks, maintaining consistency while preserving authenticity.

This works for webinar scripts, video content, email sequences, sales decks, or any content format. The interview ensures your perspective drives the content, not AI’s generic patterns.

Encode Your System for Consistency

The final step is making all of this repeatable and consistent. You need to encode your story system so AI references it automatically in every output.

We embed specific instructions in our Claude Projects that reinforce the core narrative and challenge AI to evaluate its own output. This self-evaluation forces AI to consider narrative consistency, audience fit, and strategic positioning rather than just generating technically correct content. Your encoding should reflect your unique lore.

My positioning is about building expertise transparently while calling out performative aspects embedded in LinkedIn culture and AI consulting. Your encoding will reflect your market position, your differentiation strategy, and your audience psychology.

So this is what my system is encoded with:

AI can do everything…but

AI can structure your story, scale your messaging, and maintain consistency across channels. It cannot create emotional resonance.

AI doesn’t know what keeps your customers awake at 3am. It doesn’t understand the frustration of implementing yet another tool that promises transformation and delivers incremental improvement. AI hasn’t felt the relief when someone finally explains a complex problem in simple terms.

You have. Your story system must capture that emotional reality. Your 3P engine must reflect genuine empathy, not algorithmic pattern matching. Your frameworks must guide toward human connection, not just conversion optimization.

The AI story system we’ve outlined isn’t about replacing human insight with machine efficiency. It’s about encoding your hard-won expertise so AI can execute your strategy at scale without diluting what makes your perspective valuable.

Feed AI strategy, context, and constraints. It will give you consistency, scale, and efficiency. But the story itself? That’s still yours to create.

The AI Sales Lab

I test every AI tool and tactic for sales. I share what actually moves the number, not just what sounds good on LinkedIn.

By Florian | The AI Sales Lab

Grow-th by Shreya Vaidya

Marketer | Storyteller Building Spryngbase, writing about founder realities, marketing experimentation, and why most B2B SaaS advice is b*llshit.

I spent five years as a marketing generalist at a scaleup. The key focus was always content, content, content.

Content was my religion. Content for SEO. Content for lead magnets. Content for “visibility.”

Pre-AI (i.e. ChatGPT making AI accessible), this was a tedious task - you had to work with your designer and your copywriter and your technical marketer to make sure your content was ready and your campaign was fit to be launched. Lots of manual work and scope for errors; on the flip side the quality was better and creativity was still abundant.

Then AI arrived, and suddenly we could produce more. So naturally, leadership wanted more. “Let’s do 100 blog pieces a month.”

“About what?” I thought.

Just because we could say more didn’t mean we had more to say. But I convinced myself otherwise. Of course we needed more content - I mean more content is always better.

Here are the three lies that kept me comfortable with being a content factory (Bonus: And how I finally broke free.)

Lie #1: “We Need to Be a Thought Leader”

Listicle + Contrarian Opinion + Product Pitch = Brand Growth?

The logic isn’t faulty. Publishing positions you as an expert.

Except thought leadership requires actual thoughts. Controversial concept, I know. 🙃

Most content is recycled consensus—the same “5 Tips for [Thing]” that everyone else published last Tuesday (I am also guilty of the same at times.) I mean with AI slop, your prospects are drowning in generic content.

Real thought leadership is expensive, opinionated, and often uncomfortable. Most companies desperately want the reputation without any of the risk.

One question you need to ask yourself is “Would anyone pay for you to share your content, opinions, and thoughts?” If not, why would they sacrifice their attention—the most valuable currency they possess—to consume it?

Lie #2: “All Publicity is Good Publicity”

Content = Visibility = Brand awareness. Right?! Right?

I told myself this while chasing initiatives completely disconnected from what we actually sold. Some people take this too far. Lately, I’ve seen the emergence of “rude content” (and quite frankly downright ridiculous content) as a trend. Why anyone would associate their personal and business brand with this garbage is beyond me. I sincerely hope this dies quickly.

Credits: Frank Sondors and Nicole Jeans on LinkedIn.

Awareness without intent is worthless.

Most B2B buyers don’t discover vendors through blog content. They find solutions through peers, analysts, and highly specific problem searches. Your random thought piece about “the future of work” isn’t moving anyone closer to a purchase decision.

And while posting consistently is good advice, there needs to be a central narrative thread. Each piece should build a cohesive story in your buyer’s mind. A series of disconnected ideas isn’t a content strategy.

Having said that, it is nice to have a campaign once in a while that is just for fun and helps put your brand name front and center in the eyes of the market.

Lie #3: “These Engagement Metrics Look Great!”

Impressions + Clicks ≠ Revenue.

They’re interesting indicators of resonance and relevance, but they are not barometers of success.

Brand is important, absolutely. But pipeline contribution is the main goal of GTM. Any lead that comes directly to your website is a win for your entire go-to-market team—not just marketing’s vanity dashboard.

The most successful content marketers I know track one metric religiously: How many sales conversations started since we launched this content initiative?

Everything else is ornamental.

What Great Content Actually Does

So what’s the alternative to comfortable lies?

Connection. Great content connects. It either brings out a bold personality that makes people pay attention—like tl;dv’s irreverent brand voice—or gives away genuine value that builds community, like Tom Orbach’s approach.

Credits: tl;dv(Renee Shaw, Tomas Budin) & Tom Orbach

Real content mobilizes people. It makes them stop scrolling, lean in, and think: “This person gets my problem.”

To be honest, most of us would be better off publishing one genuinely useful piece per month than flooding the internet with forgettable noise.

Start asking harder questions about what your content is actually doing for your pipeline. Work along with your sales, customer success, and product teams to effectively translate customer problems into enticing content pieces.

I have recently begun an experiment on LinkedIn, using my face in one post every month. About 3 months ago, I cringed at that idea.

Not because it was bad—it just made me uncomfortable.

Ironically, these posts have been my best performing posts everrr...

The strange thing is that the stuff that makes you uncomfortable is exactly what works (most of the time, especially if you’re not a jerk about it). Predominantly because this is the content that cuts through the noise.

Subscribe now

An Analysis of My Content in the Last 4 Months

I maintain a record via a Google Sheet of all the posts I’ve made since October. (I’ll mainly be talking about LinkedIn since my Substack is very recent—follow me here.) Previously I used Taplio for analytics and post scheduling, which was also helpful. But I find it simpler to manually enter the data and upload it in a custom Claude project to give me the patterns.

This is what an analysis of 23 posts from Oct 2025–Jan 2026 says.

Three factors consistently drove performance:

1. Personal Experience/Story + Image = 2,164 avg impressions, 42.2 avg engagement (comments + likes)

2. Reflection Tone = 51% more engagement than Contrarian tone (I will explain what this means in the next section)

3. An image of me = My top 2 posts (3,931 and 2,442 impressions) featured an image of me.

What Actually Changed

Change 1: Adding My Face (Despite Hating It)

Before: Marketing theory posts with generic graphics

• Average impressions: 672

• Average engagement: 9

After: Talking about my experiences with candid photos

• Average impressions: 1,673 (+149%)

• Average engagement: 30.5 (+239%)

The discomfort. The cringe… ugh I hate seeing my own face on LinkedIn. It feels performative and narcissistic. But of course, being a marketer I follow the data. And the data doesn’t lie: My top post (3,931 impressions, 66 engagements) is a picture of me in a park talking about how I have been working and keeping busy while technically being ‘unemployed.’

Another interesting comparison is between the best performing post without an image of me and the best performing post with an image of me. There is a giant gap between the two in terms of impressions and engagement.

Change 2: Taking a Reflection Approach Rather Than a Contrarian One

LinkedIn has evolved a lot. There were a few key types of content that were popular on LinkedIn from 2021–2024. These were mainly Contrarian or Regenerative content.

Contrarian content is when you take a strong (sometimes controversial) stand against the wave of commonly believed truths. For example: “LinkedIn is going to die in 2027.” This is followed by either an elaboration of the strong opinion itself or a softening of the original point made. They’ve been very effective at grabbing attention and have been a key part of what a lot of LinkedIn creators have used to attract eyeballs and engagement.

Regenerative content is the other format that has worked—i.e., “Comment ‘Claude’ to get my list of Claude prompts.” Basically posts where you have to engage or act to get something of value in exchange. I was never a fan of this type of content, tbh. It feels a bit manipulative.

But as people started using these tactics more and more, LinkedIn users grew fed up. Lately I’ve been noticing that personal stories and reflective content has been resonating a lot more with my LinkedIn audience, at least. I also feel more comfortable expressing my view on something rather than declaring something the objective truth—which is what contrarian posts tend to do.

Contrarian invites argument. Reflection invites conversation.

What This Means for You

This isn’t just about me. Personal brands categorically outperform company brands on LinkedIn. As per Wynter’s research from 2024, 77% of B2B buyers engage more with content from a person versus a company.

I’m not suggesting you become an influencer. That’s the opposite of my point. Moreover I am unsure about how long the trend of ‘putting your own picture up to grab attention’ is going to last.

But in any case if you’re building thought leadership, your face and your authentic experiences matter more than generic advice. Break down the wall of believing that B2B needs to be a certain way. Today, everyone is looking to connect with a person and a brand—and having a personal brand is ultra crucial if you want to build something meaningful for your business.

Marie Martens (Co-Founder of Tally) does this brilliantly for Tally on LinkedIn. Tally also has a great presence on Reddit. They listen to user feedback and engage with them. Their business is truly human to human.

The same can be said about Jess Cook from Vector. She allows her audience to get a sneak peek into the marketing decisions that Vector takes by way of her podcast (cleverly titled This Meeting Could’ve Been a Podcast).

The days of contrarian content are well gone. If you want to be relevant on LinkedIn today then focus on sharing your experiences, focus on meeting new people and learning from them.

People care about stories, so give them one to care about.

Alice Xerri recently wrote about expert-led content becoming the backbone of B2B credibility in 2026. If you’ve worked in SaaS marketing over the past few years, you know that founder brands aren’t nice-to-haves anymore. Showcasing the expertise of your organization and founders has become extremely crucial.

I experienced this firsthand, between 2021–2024, we ran campaigns that alternated between broad topics (think “2022 landscape of AI in product innovation.”) These campaigns were great for lead volume, but terrible for lead quality. We also ran solution-focused pieces featuring actual internal expert perspectives. Although the volume play was tempting, it was the expert-led content that actually got us the leads we wanted.

Nobody Reads Your White Papers

A stat that I came across recently that shocked me was that 40% of B2B marketers cite their top challenge as ‘creating content that prompts any desired action’. Nearly half the industry is publishing content hoping that somewhere, somehow, someone might care?

AI was supposed to solve the content problem. And in a sense, it has: 87% of users report improved productivity with AI (as per CMI’s 2026 B2B Content and Marketing Trends Report) Additionally, 12% of marketers admit that content quality has actually decreased since implementing AI. Brilliant. We can now produce mediocrity at an industrial scale.

Has content evolved into an industry that exists primarily to justify its own existence?

Content is visible work. Unlike the invisible labour of strategy, anyone can see you’re “doing something” when you publish three blog posts a week. Publishing cadence becomes a convenient proxy for productivity. Traffic is a vanity metric disguised as success. And the machine keeps humming along, consuming budgets and generating… what exactly?

Content agencies are judged by volume produced.

SEO consultants by keyword rankings.

Marketing teams by publishing cadence.

The incentives are magnificently misaligned at every level. Everyone’s optimizing for metrics that have zilch to do with whether anyone bought anything. The “thought leader” title has never been easier to claim or less meaningful to hold.

Welcome to 2026, where we’ve mass-produced average content.

Buyers Are Getting Pickier

The Wall Street Journal recently reported that brands are desperately seeking storytellers. Meanwhile, CMI’s 2026 research shows that whilst AI-powered tools lead budget priorities as identified by 45% of marketers, there’s a significant return to events and experiential marketing (33%) and owned media (32%).

Regarding thought leadership, nearly every B2B marketer (96%) says their organization creates it, but only a minority of marketers report broader employee participation (beyond the marketing team.) I do believe that this is crucial to use thought-leadership as a business differentiator.

The most effective channels for B2B thought leadership, as per CMIs report are:

1. LinkedIn (76%)

2. Email newsletters (54%)

3. Speaking events and webinars (52%)

These are all channels that reward genuine expertise and an authentic voice. LinkedIn in particular serves as a means to compound credibility. That is, if you publish consistently and provide intelligent insights, your authority accumulates.

The irony of this situation is that despite “team skills and capabilities” being cited as a top driver of effectiveness by 53% of marketers, human resources (salaries and training) are the lowest budget priority for 2026. Only 9% of marketers cite this as a top priority (in contrast to 45% of marketers who cite AI as the top priority).

Let that sink in.

Rethinking B2B Content Marketing

Right, enough criticism. When does content marketing deliver genuine business results? Here’s the breakdown based on my own experience:

Condition 1: You Have a Genuine Story to Tell

This entails a genuine, differentiated narrative that your audience cannot get elsewhere.

The checklist:

• You’re a strong storyteller who brings novel insights, not recycled industry consensus

• You have a point of view strong enough to differentiate (and possibly alienate, yes that is healthy) a section of users

• You provide access to information or perspectives your audience can’t find elsewhere

• You’re willing to say things that might be controversial within your industry

• You possess deep domain expertise

Condition 2: Your Sales Cycle Requires Education

Some products sell themselves in a single conversation. Most B2B solutions don’t.

Content works when you have:

• Complex products with long evaluation periods where buyers need to understand capabilities

• Multiple stakeholders requiring different information to secure buy-in

• Technical buyers who do extensive research before engaging sales

• A genuine information gap that your content fills (not just generic category education)

Does your sales team regularly say “I wish I had something to send prospects about X”? That’s real content demand. That’s where your resources should go. Everything else is optional.

Condition 3: High-Intent Keyword Opportunities for High Awareness Solutions

If your solution has high awareness in the market (for example a CRM) and you are not predominantly using commercial intent keywords, you may need to reevaluate your content. This is where SEO stops being a vanity project.

What you need:

• Search terms in your category that demonstrate genuine buying intent

• “Best [solution] for [specific problem]” queries that exist in meaningful volume

• Search intent for queries that matches your actual buyer profile

Example: “CRM for real estate teams under 50 agents” has intent. “What is a CRM” does not. Only one query among these comes from someone evaluating solutions.

Start owning buyer-intent searches.

The Evidence for AI Human-Led Content

Having experienced this firsthand since 2021, I’ve watched how founder expertise and employee thought leadership can drive pipeline and enhance brand value. Now that I’m working on my own company (Spryngbase) and operating as a freelance marketing strategist, I’m seeing it play out even more clearly on platforms like LinkedIn and Upwork.

As AI-generated misinformation proliferates, buyer scepticism intensifies. Buyers today are demanding “hard proof” and human validation before engaging with vendors. They’re not looking for more content rather for more credibility.

This creates an opportunity for B2B companies willing to invest in genuine expertise.

What can you do to enhance credibility?

1. Identify your genuine differentiators: What insights emerge from your actual client work? How are they different from competitors or substitutes?

2. Involve broader employee expertise: Your marketing team can’t manufacture thought leadership alone. Your founders, technical leads, and customer success teams hold the insights buyers crave.

3. Measure business impact, not engagement theatre: Track pipeline contribution, conversation starters, and qualified lead generation — not impressions.

4. Build compound credibility: Focus on platforms like LinkedIn where credibility compounds over time.

5. Create content sales actually wants: Work backwards from what closes deals and try to connect it to what grabs attention (i.e. trends etc.)

If you’re ready to build content that actually converts:

• Audit your last 10 pieces: How many prompted a sales conversation?

• Interview your sales team: What content do they wish existed?

• Identify ONE high-intent keyword opportunity you can credibly own

• Publish nothing for 2 weeks while you develop an actual POV

Feeding the Publishing Beast

Most B2B content marketing doesn’t work because it’s designed to demonstrate activity, and generate reports with impressive-looking but ultimately meaningless metrics.

The companies that win at content marketing are doing something fundamentally different: they’re treating content as a strategic asset, not a publishing quota. They’re investing in human expertise. They’re building genuine thought leadership whilst others are chasing keyword rankings.

The choice is yours. You can join the content industrial complex, publishing prolifically and achieving very little. Or you can build a strategic content engine focused on the only metric that matters: does anyone care enough to do business with you?

Because here’s what I’ve learned: buyers don’t want more content. They want better answers. They want genuine expertise. They want someone who understands their specific problem and can articulate a credible solution.

Give them that, and content marketing works brilliantly. Give them anything less, and you’re just adding to the noise.

A bit about me: I am Shreya and I help B2B SaaS companies build content engines that drive pipeline. The data in this article is drawn from CMI’s B2B Content Marketing and Trends report for 2026.

Have you tried creating blog creating agents or landing page creators with AI agents? What’s the one thing most of these outputs have in common? They usually tend to be:

Bland. Repetitive. Lacking personality.

AI can do some things really well and some others not so much.

Where AI Actually Delivers

AI doesn’t create your brand voice (but it can amplify it.) AI is an accelerator not necessarily a builder. AI delivers really well in the following usecases:

Content Scaling (Not Creation)

• Amplifies your existing voice and messaging frameworks

• Generates A/B test variations at unprecedented speed

• Personalizes content for different customer segments

• Transforms single pieces into multi-channel campaigns

Customer Intelligence (With Quality Data) Want to predict customer churn? Identify upsell opportunities? AI excels here — if you have well-documented customer data:

• Meeting notes and interaction history

• Proper CRM activity tracking

• Systematic data collection processes

Operational Acceleration

• Handles routine customer interactions

• Executes multi-sequence email campaigns flawlessly

• Distributes content across channels systematically

• Generates performance reports automatically

Where AI Falls Flat

Strategic Architecture AI can’t decide what story your company should tell. It can’t choose your market positioning or identify your unique competitive advantages. These require human judgment, market intuition, and strategic thinking.

Creative Breakthrough Your most powerful marketing moments come from unexpected angles, cultural insights, and creative leaps that AI simply cannot make. Breakthrough campaigns require human creativity and market timing intuition.

Relationship Dynamics B2B sales happen through trust, credibility, and human connection. AI can support these relationships but cannot build them. Complex buying processes require human navigation.

Market Timing Intelligence Understanding when to enter markets, pivot messaging, or capitalize on trends requires human judgment that AI cannot replicate.

The Strategic Integration Framework

Architecture Before Automation

Treat AI integration like building critical software infrastructure. You wouldn’t start coding without system requirements, right?

The Foundation Stack:

1. Positioning Layer: Clear value proposition and market differentiation

2. Messaging Framework: Consistent voice across all touchpoints

3. Customer Journey Architecture: Mapped touchpoints and conversion paths

The Human in the Loop Model

• Human Focus: Strategy, creativity, relationships, judgment calls

• AI Focus: Execution, optimization, analysis, scale

• Integration Layer: Systematic processes connecting both strengths

Build feedback loops that improve AI outputs over time while maintaining brand consistency and strategic alignment.

Brand Growth with AI

The importance of setting up a quality brand growth system involves understanding the critical components required for the system to work. This begins with a strategic AI audit, where you ask 3 critical questions:

1. Is my positioning crystal clear before I scale it?
   (Unclear messaging = Incorrect amplification = Lots of customer confusion)

2. Do I understand my customer journey architecture?
   (AI optimizes existing systems, it doesn’t fix broken ones)

3. What decisions should always remain human? (Positioning, pricing, market entry — never automate these)

Before automating anything with AI, ensure you can explain your positioning, ideal customer, and value proposition clearly and concisely. If your strategy isn’t crystal clear to humans, AI will just help you fail faster and at a greater scale.

The simple way to put it is that AI is your marketing accelerator, not your marketing brain. Get the brain right first.

Approach AI marketing like any critical system implementation. Requirements first, architecture second, then systematic scaling.

The companies winning with AI marketing aren’t replacing strategic thinking — they’re systematically amplifying it. They use AI to execute carefully architected strategies at scale, not to create those strategies.

Pro Tip: The best AI marketing systems are built like the best software architectures — with clear requirements, systematic processes, and continuous optimization cycles. Treat your marketing infrastructure with the same precision you’d apply to your most critical code. 💡

Ready to build marketing systems that amplify your strategic advantages?

Originally published at https://grow-tharchitect.comon October 15, 2025.

Subscribe now

“I’m a marketer and even I think LinkedIn is cringe.”

I say this often, usually to founders who are finding every possible reason not to post on LinkedIn. Truth be told, they’re not entirely wrong. LinkedIn can feel like theatre. The platform is full of humble brags masquerading as vulnerability. And yes, posting about yourself does feel uncomfortable.

My take: If creating content doesn’t feel at least 20% uncomfortable, you’re probably not saying anything worth reading.

Whether it is talking about yourself or linking a current event to your product or putting up a picture of yourself on LinkedIn — It all feels cringe at some point. Here are the most common objections I hear and my take on them.

Objection 1: “It feels like marketing theatre”

I get this. The line between professional platform and personal storytelling has completely dissolved and LinkedIn Gurus are here for it.

“Authentic” content is celebrated, but being authentically vulnerable (especially about failures) is genuinely uncomfortable for founders who already face enough scrutiny.

The Shift: Stop making ‘authenticity’ your only goal. Instead, think about resonance. Your buyers don’t need your deepest emotional confessions; they need to know they’re not alone in their specific business challenges.

The Opportunity: Every founder deals with the same chaos: notes you make after a customer discovery call, product decisions you make at 3am, and Excel sheets that track your product feature requests from customers. These can serve as marketing gold for your LinkedIn.

When you share your 3am Slack message that changed your product strategy, you’re not being vulnerable for vulnerability’s sake. You’re demonstrating systematic thinking to buyers who are drowning in generic solutions.

People (including your buyers) want to hear and see other people’s stories. Mainly, they just want to know that they are not alone (and sometimes, yes they also want to be entertained — refer: r/linkedinlunatics.)

Objection 2: “I don’t have time for this”

Fair enough, your priority is running a business and LinkedIn feels like this cringe-worthy platform where people just prop themselves up. You’re already answering the same customer questions repeatedly, explaining your differentiation on every sales call, handling objections via email.

The Shift: LinkedIn isn’t additional work, it is quite simply, documentation of the work you are already doing. Just made scalable.

The Opportunity: Consider the math:

• Average founder spends 10–15 hours/week in customer conversations

• A good percentage of those conversations cover the same 5–7 topics

• One LinkedIn post takes 20–30 minutes and reaches 500–5,000 people

The anticipated result is that when a potential buyer schedules a demo already familiar with your thinking, your sales cycle compresses. Plus, that one post can become evergreen sales collateral, objection handling, and even a topic for a whole webinar.

Objection 3: “I don’t know what to post. How do I know which posts actually works?”

You don’t. You don’t know which posts work until you actually try doing it. Yes, sometimes you’ll post and get two likes. (It still happens to me.) But honestly? Is your goal collecting likes? Or do you hope to increase brand awareness and improve pipeline quality?

The Shift: Stop asking ‘What performs on LinkedIn?’ It doesn’t matter. You need to know what matters to your customers. Think about “What conversations am I already having with my ideal customers?” and how this could be relevant to multiple customers.

The Opportunity: Specific and niche content is much more likely to generate business outcomes than content that is highly liked. Your systematic thinking about niche problems attracts precisely the buyers who need your systematic solution.

Always focus on quality and relevance over optimising for likes.

Objection 4: “Why Spend 2 Hours/Week on LinkedIn When I Could Build a Product?”

Making product tweaks feels productive because it’s comfortable. Putting yourself in front of your market feels risky because it invites criticism.

The Shift: You need to realise that product development without market visibility is just expensive software engineering. Your systematic thinking IS your competitive advantage, if and only if your market knows it exists.

The Opportunity: B2B buyers don’t wake up searching for your product category. They wake up with problems that eventually lead them to solutions. By consistently demonstrating how you think about their problems, you become the obvious choice when they’re ready to buy.

The DDD Framework: Demo, Document, Drill

So now that you know why you need to post more on LinkedIn, how do you begin going about it? Instead of generic LinkedIn advice about “being authentic” or “providing value,” here’s a systematic approach you can use:

Demo: Show Your Product Process

What This Means: Showcase or demo the chaos you’re already managing.

For example:

• Notes from customer discovery calls that changed your assumptions

• The spreadsheet tracking product upgrades based on customer requests

• Decision frameworks you use for prioritization

• The conversation that shifted your GTM strategy

Buyers are interested in you first; your business second. Demonstrating systematic thinking in real time builds credibility that no case study can match.

Document: Turn Decisions Into Growth Experiments

What This Means: Frame every strategic choice as a hypothesis you’re testing, then share results transparently.

For example:

• The technology investment that saved 40% processing time (with before/after metrics)

• The customer problem that pivoted your roadmap (with decision criteria)

• The “obvious” solution everyone else is missing (with reasoning)

This positions you as someone who makes evidence-based decisions, not someone following startup theatre scripts. It’s catnip for buyers tired of vendor marketing.

Drill: Pre-Handle Objections Via Content

What This Means: Every startup founder hears identical objections. Turn your daily objection handling into systematic content series.

For example:

• “How is this different from [competitor]?” → Comparison framework post

• “We don’t have budget for another tool” → ROI calculation methodology

• “Can’t we just build this internally?” → Build vs. buy decision matrix

Buyers are already asking these questions internally. By addressing them proactively, you compress sales cycles and qualify prospects before they even reach out.

Create Your First Post

This week, try this specific approach:

Demo one process: Share your notes from a customer conversation that changed how you think about your market.

Document one decision: Explain a choice you made this week (product, strategy, GTM) like it’s a growth experiment, including your hypothesis and early results.

Drill one objection: Address the most common objection you heard this week, but as a strategic analysis rather than a defensive response.

Aim for the 50–200 people in your ICP who see systematic thinking and think: ‘This founder gets my problems.’

Success on LinkedIn?

Successful founders treat LinkedIn as systematic demand generation infrastructure, not as a marketing channel. They’re not trying to go viral. It is as simple as that. Their goal is to appeal to their customers by systematically documenting the thinking that makes them exceptional operators. By doing this they aim to make their way of working and thinking accessible to buyers who need precisely that kind of systematic thinking applied to their problems.

Your buyers on the other hand, are on LinkedIn looking for stories to connect with. They are seeking people who can solve their problems. And by just showing up you can help them remember that your software or company is available in the market when they urgently need to fix the problem they encounter.

LinkedIn feels uncomfortable because you’re fighting against every instinct that helped you succeed as a founder: focus on product, avoid attention, let results speak for themselves. But in B2B markets where buyers are drowning in identical-sounding solutions, systematic thinking documented consistently is the new competitive moat.

Start with one post this week. Demo, document, or drill. Make it uncomfortable enough that you feel slightly exposed. That’s how you know you’re saying something worth reading.

Bonus: LinkedIn also makes it must easier to do a cold outreach. Especially when the buyer is part of your network and is somewhat familiar with you or has seen your posts pass by.

Ready to build systematic demand generation without marketing theatre? Subscribe for frameworks on turning founder chaos into competitive advantage

.

Why does this happen? Well simply because Excellent Product ≠ Smashing Pipeline

Let’s create a new blog post landing page webinar

Most early tech founders treat Sales & Marketing systems like a mysterious engine that will automatically start working if you try hard enough.

I have news for you: that’s not how systematic growth works. Wing-it marketing culture is the single biggest enemy of systematic growth. Good GTM (go-to-market) systems require patience, experimentation and scaling. It’s a systematic process that responds to the same logical frameworks you use in development. The difference is you’re now engineering human behavior instead of code behavior.

The most common reasons I have seen early-stage B2B Saas Companies fail to build a strong pipeline always boils down to five key things.

The good news? They’re all fixable.

Problem 1: You’re Speaking German While Your Customer Speaks Italian

Your website proudly says “Reduce API Latency. Optimize Your API Performance.”

Your customer hears noise.

What they need to hear: “Load your reports 3x faster. Spend less time waiting and more time making decisions.”

Understanding your customer’s language and changing your message to make it less technical sometimes holds the key to higher conversions.

I want you to go back to your website and social media and audit your entire customer-facing content. If a non-technical person can’t understand the value within 10 seconds, you’ve lost them.

After the audit you need to implement this framework. For every technical feature, create three communication layers:

• Executive Summary: Business impact in one sentence

• Manager Translation: Operational benefits with specific metrics

• Technical Deep-dive: For the engineers who actually implement

The simple truth is your customer-facing messaging needs clean, intuitive interfaces that abstract away technical complexity until users need those details

Problem 2: You Don’t Need More Than 7 words

While it might be tempting to list down the complete set of features on your website, the truth is your customer doesn’t really need to know that.

Instead of “Enterprise-grade API infrastructure for automated workflow orchestration,” try “Build reports that actually work.” Then layer on complexity for technical buyers who want the details.

If you need more than 7 words in your headline to explain what you do, you’re overthinking it.

Here’s what you need to do:

1. Start with the problem you solve (not how you solve it)

2. Test your message on someone completely outside your industry

3. If they can’t repeat it back accurately, simplify further

4. Create technical appendices for buyers who need proof

This isn’t “dumbing down” your message — it’s providing clarity to your customers.

Problem 3: You Are Not Following the 15% Marketing Investment Rule

If less than 15% of your daily effort goes toward marketing, your pipeline will dry up regardless of product quality. I notice a lot of founders spend most of their time perfecting features and doing small demos within their network instead of actually spending time on creating wider brand and product awareness.

Here’s generally what I like to propose to new founders when it comes to dividing their time and money.

Resource Allocation Framework:

• Product Development: 28–50%

• Marketing: 12–20%

• Sales: 20–30%

• Operations: 10–15%

• Strategic Planning: 5–10%

I, of course, don’t mean that you need to spend a lot in the beginning but if you are willing to spend money on building a new product then maybe also think about investing in a system that will help build new clients and pipeline. Marketing isn’t an expense — it’s infrastructure to help you build growth. You wouldn’t run your product in production environment without a sandbox. Why run your business on hope instead of systematic demand generation sandbox?

Problem 4: The Junior Marketer Trap

A lot of startups suffer from a lack of budget, resorting to hiring a full-time junior and hoping they will deliver instant results. The truth is, junior marketers need time to learn, to experiment, to fail and grow. Most importantly junior marketers need mentorship.

You wouldn’t let an intern design your architecture (not without sufficient training atleast.) So why not give enough support to your junior marketer?

To help your startup succeed, give them the right tools, frameworks and expertise. Partnering them up with a senior mentor on a monthly or quarterly basis would also be a good business investment.

A tip when making your first marketing hire is to always look for keen problem solvers with a hunger for learning who are enthusiastic, diligent, take initiative and are open to taking risks and challenging you.

Problem 5: Becoming a Value Factory

It is important for you to realize that while you’re building feature #17, your competitors are explaining why feature #3 matters. That is where the difference between becoming a feature factory and a value factory lies.

Every hour spent on incremental improvements is an hour not spent on market education and brand creation. Ask yourself: “Will this feature increase customer willingness to pay by 20% or more?” If not, focus on communicating existing value first.

Value Communication Framework:

1. List all your new features in development and list customer value as well as overall improvement to the product that will eventually lead to customer value

2. Document current feature impact with specific customer metrics

3. Create systematic case studies showing quantifiable results

4. Build educational content that connects features to business outcomes

5. Test messaging effectiveness before building new features

Engineering Your Go-to-Market

Apply the same systematic thinking that made your product great to building predictable revenue growth.

Week 1: Audit all customer-facing messaging for clarity

Week 2: Establish marketing time allocation and budget baselines

Week 3: Document existing feature value with customer metrics

Week 4: Create systematic content production process

Finally, your product isn’t failing because it’s not good enough. It’s failing because you’re treating revenue generation like an afterthought instead of a systematic process.

The most successful technical founders I work with treat marketing like building sound infrastructure — with clear architecture, measurable performance metrics, and continuous optimization.

Stop hoping great products market themselves.

Want systematic frameworks for turning your technical excellence into predictable revenue growth? I help B2B SaaS founders build demand generation systems that scale. Connect with me on LinkedIn — Click here.