We built the systems to help experts turn their knowledge into stories, and stories into followers. But this process is dependent on how much time and effort you have to create on a daily and weekly basis.

Today, we’re releasing Spotlight Videos. When creating our own content, we thought to ourselves, what is the most effective way to kickstart our community? What is the asset that will keep on giving? What will continue attracting an audience even after this algorithm changes?

Spotlight Videos is the first pinned square on your social media. It is a 60 second video of your journey: who you are, what brought you here to this chapter, and where are you going.

Your Spotlight video serves as a landing page for customers to learn who you are and what your company is about. The first time you meet a new customer, they will already know who you are, because they’ve seen your Spotlight Video. And existing customers, friends, and partners will be reminded of your vision, talking about your story in their inner circles.

This is the first step toward finding your tribe, and connecting with your community as a content creator. We will be releasing Spotlight Videos of some of our favorite cultural leaders on our Instagram @shapeshift.

Spotlight Videos will be rolled out in phases in 2025.

1. Tastemakers (celebrities)

2. Community participation (remixing)

3. Unexpectedness (shock and awe)

But today, this framework is basically irrelevant.

Here’s how content goes viral today:

1. Tastemakers —> Algorithm

2. Community participation —> Hook + Watch time

3. Unexpectedness —> Niches

Back in 2012, YouTube still relied on “tastemakers”, traditional media celebs like Jimmy Kimmel, to kickstart content to the masses.

But then TikTok came along and then COVID which onboarded literally everyone onto short-form social media platforms.

Today, content is uploaded and the algorithm immediately determines if it goes viral, based on click through rate and watch time.

The Algorithm is the ultimate tastemaker AND kingmaker.

Three Waves of Content

So far, there have been two waves of content, and we’re now in the third.

Each wave begins with a tech innovation that unlocks what people already want to do, but previously couldn’t.

Wave 1 | iPhone + Mobile Video (2007-2015)

The iPhone democratized content creation. Anyone with a phone could shoot, edit, and upload video. This created YouTube's golden age and birthed the first generation of internet celebrities.

Wave 2 | TikTok + Algorithmic Distribution (2016-2024)

Algorithms replaced tastemakers. You no longer needed Jimmy Kimmel to discover your content—the platform itself became the tastemaker. Short-form video optimized for dopamine hits and endless scroll.

Wave 3 | AI + Interactive Content (2024-?)

TikTok made it easier to chase dopamine, but people don't actually want to chainsmoke shallow content.

They want to go deeper.

People are naturally wired to binge content. When White Lotus drops, they don't just watch—they consume every piece of related content and want to live inside that universe.

The problem today is creators can't satisfy that desire because they can’t make videos fast enough and can’t actually predict what people want to watch in real-time.

This is where AI comes in.

How Content is Created Today

In the algorithmic age, creators have a tried and true portfolio process:

Create viral short-form content to hook people into your universe of deeper long-form content.

Last year, I met some new grad filmmakers at a coffee shop and asked them what kind of content they watch.

What they shared with me destroyed my brain, but proved that this formula works (the top comment perfectly describes the wtf nature of 46.4M views).

Skibidi Toilet started as a stupid video with a repeating format: dancing heads coming out of a toilet against a catchy music.

But it evolved into a complex cinematic universe with characters and multi-part storylines. Millions of kids are completely absorbed in this world.

Before you dismiss this as Gen Z brain rot, this also the same formula Andy Cooks used to build his platform, first on TikTok and then on YouTube.

"Hey babe, what's for dinner?" became full cooking tutorials, then unscripted podcast-style content where he and "babe" cook and chat.

The framework is: simple hook → character development → expanded universe → parasocial bond.

I think AI-native content will follow this exact pattern, but you won’t have to wait for new episodes to drop.

Generative AI trained on deep content libraries will allow platforms to instantly create content based on what the audience wants to watch
— even before the current video has finished.

The Multiverse Model

When I’m thinking through a business problem, I use ChatGPT advanced voice to role play CEOs and investors that I admire, so I can get their perspectives as if they were on my board.

Of course, these are low-fidelity AI “perspectives”, but imagine what this will look like when there’s MCP access to each leader’s full knowledge base.

David Maisel revolutionized filmmaking when he pitched the Marvel multiverse concept—interconnected characters and storylines that could cross over and expand indefinitely.

The same thing is about to happen with AI creator essences.

Once thought leaders have deep binge banks of their content, users will naturally want to do crossover episodes of their favorite influencers.

There's going to be massive cross-pollination when viewers can remix different bundles of AI creators because like before, it’s something people already want to do.

How to Win the Third Wave of Content

The winners of the AI wave are the ones building comprehensive binge banks of their thinking.

Not surface-level content, but high-calorie explorations of expertise, frameworks, and decision-making.

People like Howard Marks, JJ Redick, and Patrick O'Shaughnessy accidentally created binge banks of training data for LLMs.

a16z is actively investing in this area with key hires Erik Torenberg and Alex Danco.

These leaders are examples of people best positioned to take advantage of the AI wave of content.

In the AI era, thought leadership becomes training data.

Current AI tools like HeyGen and Veo produce obvious, awkward content. We’re seeing a lot of AI slop, not because that’s the ultimate use case for AI, but because the technology hasn’t caught up to user behavior yet.

But Heygen and Veo point to a future where creators will be able to make high quality AI facsimiles of themselves, trained valuable thought leadership.

We’re headed in the right direction, we’re just not there yet.

Key Takeaway: Be the First Mover

The AI-native content platform doesn't exist yet, but the infrastructure you need—comprehensive, high-quality training data—can be built today.

When the next platform emerges, it will dominate distribution just like YouTube did, then TikTok after that.

And the creators with the richest training data will have a dominant first mover advantage.

Thought leaders with deep expertise need to extract as much knowledge as they can now. It's not about likes or impressions—it's about preparing for how content will be consumed in the future.

The third wave of content is coming. You don't want to miss it.

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This is one of the most common questions I get from Shapeshift’s consulting customers (Series A+ founders and their content teams).

In the early days of Shapeshift, I tried really hard to prove that our CEO’s LinkedIn posts directly influenced pipeline.

I took a screenshot every time a prospect DM’d or reshared our content, and even built detailed models to track which LinkedIn users made their way into Hubspot.

Today, I’m still very active in our customer’s sales channels, but I have a much firmer stance that attribution on LinkedIn is a waste of time.

Fundamentally, LinkedIn is a brand play and not a direct response play.

Brand is especially impactful for long sales cycles, which is why we love working with startups doing enterprise sales.

Executives and founders spend time on LinkedIn, perhaps more than any other platform, which makes posting content super effective for finding and nurturing prospects.

You won’t be able to “measure” how much your LinkedIn post contributed to the $10M deal though.

So at it’s core, you just have to believe that creating content will work.

If you’re selling to the enterprise, you need to create content. Don’t overthink it.

How to see if your content is resonating with ICPs

Once you’re posting at scale, however, it’s important to know which pieces of content are resonating with actual customers.

LinkedIn’s algorithm rewards least common denominator content, so following likes alone gives a misleading picture of what your most valuable ICPs really want.

Last week, I described how we “deflate” our LinkedIn reaction counts to only focus on audiences within our ICP.

This is particularly useful at scale, when you:

• Put ad spend behind retargetting or thought leadership ads

• Give your enterprise sales team more signal to close more deals faster

• Train LLMs on your content

Today I’ll show you how you can copy this for your own content team.

ICP alignment: For every LinkedIn post, we run scripts to see if we’re engaging with our ideal customer profile. We look at likes filtered by title, company, and our dream list of key prospects. These are much lower numbers, but far more directionally valuable.

The Shapeshift ICP playbook

For clients who post high quality content every day, Shapeshift tracks the number of ICP likes per post.

The simplest way to do this is using a spreadsheet, with each tab representing a post.

Let’s use one of my recent posts as an example:

In order to get the “real” or actual ICP likes, you need to parse the headings and job titles of everyone who reacted to your post.

For non-technical marketing teams, we recommend:

1. Signing up for HeyReach to automate the scraping of LinkedIn users who reacted to your post.

2. Using Google Sheets to automate the filtering of LinkedIn users —> ICPs

Here’s how to do it step by step:

1. Once you’ve signed up for HeyReach and have connected a LinkedIn account, navigate to the Leads UI (the audience icon on the left-hand nav).

2. Create a lead list from LinkedIn Post (Reactors)

3. Use the URL of your LinkedIn post to generate the Lead list. After a few seconds, Export to CSV to download the list of all people who liked your post.
   

4. Upload this CSV to a directory in your Google Drive.
   

5. Open up ChatGPT and use the following prompt. Upload the CSV downloaded from HeyReach and this image.

Write a Google Apps Script function named processLinkedInCSVs_CustomLayout that:

1. Connects to a Google Drive folder by ID.
2. Iterates over all CSV files in that folder.
3. For each CSV:
   - Names a new Google Sheet tab after the CSV file name (without .csv).
   - Parses the CSV into rows and headers.
   - Normalizes headers to lowercase for matching.
   - Identifies indices for First Name, Last Name, Company, Job Title, Headline, and LinkedIn/Profile URL.
   - Skips files missing any required columns.
   - Defines ICP keywords: [{Keyword 1} ,{Keyword 2} , {Keyword 3}]
   - Excludes rows where the company name contains {Company Name}.
   - Filters rows to keep only those with job titles or headlines matching an ICP keyword.
   - Creates a new sheet with:
     • A summary section in rows 1–4 showing ICP count in cell B3.
     • A header row at row 6: ["Notion Ticket", "First Name", "Last Name", "Job Title", "Company", "LinkedIn URL", "LinkedIn Post"].
     • Data rows starting at row 7 containing the filtered ICP rows.
4. Logs progress for each processed file.
Return only the complete Apps Script code that implements this, with no explanation or extra text.

Here is the csv that the Apps Script will interact with and a screenshot of the expected final output. 

6. Open a new Google Sheet and enable Apps Script under Extensions > Apps Script.
   

7. Paste the code from ChatGPT directly into your Apps Script UI. You can ask ChatGPT to modify the code based on the specific column headers you need for your company.

8. Within your code configure the Google Drive folder ID where you store your HeyReach files. This is just the string at the end of the URL of your folder e.g.
   
1vQq2I-QT9NEg4-9rdCSrmhJeR3agbiFn

https://drive.google.com/drive/u/0/folders/1vQq2I-QT9NEg4-9rdCSrmhJeR3agbiFn
   

9. You’ll also need to tell ChatGPT the keywords to parse for in your ICP’s headings and job titles.
   
   Shapeshift’s keywords are: [“founder”, “ceo”, “marketing”, “VP”, “gtm”]
   

10. Once you’ve tested the Apps Script, every time you add a .csv file to your directory, you’ll have a fresh sheet of ICPs.

Key Takeaway

When you’re building content at scale, make sure you content is optimizing for the right audiences.

In future posts, I’ll talk about how to leverage this rich data to:

• Put ad spend behind retargetting or thought leadership ads

• Give your enterprise sales team more signal to close more deals faster

• Train LLMs on your content

Enjoy your coffee,

Ira

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They have EAs sitting on their LinkedIns and spend time and money in meditation and cold plunges.

These are the customers we want to engage with the most, but they’ve been trained to protect their minds and limit their content consumption. So how do we actually reach them?

I think we have to create content so useful that it earns a must-read slot in the customer’s inbox or becomes a must-listen podcast in their morning routine.

My producer friend, Julia, calls this “high calorie content” — content with so much information density that the customer bookmarks it and finds time for it later.

Even for the most offline people, high calorie content forces its way into your mindshare. It’s information so valuable or perspective so unique that it gets talked about over coffee, shared in company Slacks, and becomes a part of a community’s cultural dialogue.

High calorie attention is a promise of value in exchange for time and attention.

When the promise of value is delivered, the content gets organically shared and talked about.

Social media gives you the wrong metrics to measure high calorie content.

Likes, impressions, and avg view duration reflect the platform’s incentives to keep users on feed so advertisers can monetize attention.

What really matters is whether your content builds trust and attracts a community.

When I work with founders, we measure the caloric density of content in a few ways:

1. Reputation bar: Am I proud to put my name on it?

2. Trusted circle: Do advisors and peers find it genuinely useful?

3. Differentiation: Does it stand out against everything else my customer is reading and listening to?

4. AI Advisor: If I ask ChatGPT to role-play as my customer, what about it is incorrect or missing?

On the distribution side, we also design signals to complement traditional follower and impression metrics:

1. Gong triggers: We set up triggers for specific phrases when prospects or customers mention our LinkedIn content on calls.

   

2. ICP alignment: For every LinkedIn post, we run scripts to see if we’re engaging with our ideal customer profile. We look at likes filtered by title, company, and our dream list of key prospects. These are much lower numbers, but far more directionally valuable.

Because 99% of internet users are lurkers, what we really care about is engaging the loyal core who will tell others about your content.

For every piece of content we make — every podcast our core community listens to — we want them to feel like the promise of value was delivered, so that they look forward to the next one.

Long term, content is about community over virality.

By feeding the core community, high calorie content will find its way to a larger audience.

Ultimately, creating high calorie content is effortful and expensive (I’ve already rewritten this email 5 or 6 times this week). So I think it’s important to remember the why of it all:

1. To build a network of people you want to have relationships with

2. To deeply engage with the material itself (don’t make content about stuff you hate!)

3. To compound surface areas for luck and asymmetric upside

Brand is a bucket where individual drops of trust are earned over time. I think content is still the most effective way to earn those droplets. When you do this over a very long time horizon, that bucket unlocks unthinkable opportunities.

I encourage you to think of content in this way, beyond likes, sign ups, and PDF downloads. Those are nice, but the forest, the big picture is even better than the trees.

Shapeshift is a storytelling agency working with founders and startups.

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As a business, there are two reasons to start a podcast:

1. Excuse to network and build relationships with guests

2. Build a long-term brand and fan base over time

But the biggest flaw of podcasting is that there’s no built-in distribution, which means:

1. Podcasts only spread through word of mouth or by

2. Piggybacking off of trending formats (short-form video) on algorithmic platforms (LinkedIn, YouTube, Substack etc)

Ultimately, the only way to maximize the k-factor of a podcast episode is to extract clippable moments — practical insights and polarizing opinions — from the guest.

These are the stories that listeners will tell their friends over coffee, and are the best candidates to go viral on social media.

Whenever I’m interviewing guests, I try to shape my questions into narratives where I can make the listener feel like they want to stop what they’re doing and to take a note. I’m always trying to get someone to stop driving, pull their car over, and bookmark what the guest is saying.

If my guest is a true domain expert and can speak at multiple layers of depth and specificity, then I know I can tell a story where the listener feels like they’ve gained invaluable knowledge and where the guest feels like the conversation was thoughtful and worth their time.

Here is my essential list of questions to get the best soundbites from a guest.

• What's an outcome that would make this a home run for you?

  • In an ideal scenario, if a customer has finished listening to this, what would you want them to naturally do?

  • What’s the call to action?

  • What is the feeling you want to leave them with?

• What are your controversial opinions or hot takes around your industry’s trends?

  • What trends are BS or fads?

• What are some pain points that you or your peers / your customers are feeling today?

  • In what specific contexts do they experience the pain? What are some specifics?

  • How are you / your peers / your customers solving this problem today?

    • What are the pros and cons of each alternative?

    • If competitors exist, what’s the difference between your company’s approach and theirs? Use this as an opportunity to counterposition your business. What makes you different versus better?

• What is your / your company’s superpower?

• How do you approach doing [ thing that they are an expert in ]

• What’s the 101 crash course on [ thing that they are an expert in ]

• What’s something that people commonly get wrong about [ thing that they are an expert in ]

• What are common critiques of your approach that are true?

• What are some of your rituals or routines that help you do [ thing that they are an expert in ]

• What’s the cost of doing [ thing that they are an expert in ]

Happy interviewing!

Shapeshift is a storytelling agency working with founders and startups.

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