Ramli John

Author of Product-Led Onboarding (+30K copies sold) | First Round Fast Track Mentor | Content Director at Appcues.

⭐️ Follow me for helpful tips to onboard, delight, and keep your customers coming back to your product.
📔 Author of Amazon #1 bestselling book "Product-Led Onboarding." 👉 𝙎𝙀𝘼𝙉 𝙀𝙇𝙇𝙄𝙎, Founder of GrowthHackers.com: "Product-Led Onboarding is 𝐦𝐮𝐬𝐭-𝐫𝐞𝐚𝐝 𝐟𝐨𝐫 𝐞𝐯𝐞𝐫𝐲𝐨𝐧𝐞 embarking on the critical activity of improving their user onboarding." 


⚡️ I use my multi-disciplinary skills in marketing, design, and software development to help product-led SaaS companies analyze their whole customer's journey and funnel to identify growth opportunities to 2-3X their MRR. 

Often, that means designing and implementing experiments to increase activation rate (trial-to-paid or free-to-paid conversions), decrease churn rate, or increase average revenue per user (ARPU)

If you asked my friends and colleagues how they would describe me, they'd say I'm resourceful, proactive, and entrepreneurial

►► CONTACT INFO
▷ Send a connection request
▷ Write me a note at ramli [at] ramlijohn.com

Founder

A weekly show and newsletter for marketers looking to level up their marketing and career. I interview world-class marketers to uncover the secrets, strategies, and frameworks behind their wins. In each episode, guests reveal three things:  (1) a marketing power-up,  (2) a real-world example of that in action, and (3) a power-up that’s helped them take their career to the next level.

Ramli "RJ" John

When your product team skips user research (and just builds fast with AI)... 🤡


AI lets you ship in days, not weeks. But without user research, speed just gets you to the wrong place faster.

A product leader was about to ship a feature last week. AI-assisted code. Cloud deployment ready. Built in 3 days.

Then someone from customer success flagged something: "This solves a problem our users stopped complaining about 6 months ago."

One conversation. Saved weeks of wasted effort.

We can build faster than ever. AI tools, cloud code, vibe coding—the speed is real.

But speed without direction is just efficient wandering.

The real question isn't "Can we ship this?"

It's "Should we?"

That's where user research becomes non-negotiable.

Here are 5 ways to quickly validate ideas before you ship:

1. Run a 5-second test on your concept (does it communicate what you think it does?)
2. Send a quick survey to your target segment (10 questions max)
3. Do 3-5 unmoderated usability tests on a prototype
4. Interview 5 users who match your ICP (even 15-min calls work)
5. Card sort your information architecture before building navigation

None of these take weeks. Most can be done in days.

Tools like Lyssna make this even faster. You can recruit from 690K+ vetted participants, run moderated or unmoderated tests, and get results before your sprint ends.

Speed is a competitive advantage.

But only when you're building the right thing.

What's your go-to method for quick validation?

PS. Save this for the next time you're tempted to ship something fast without validating it first. Future you will thank you.

Join the AI Product Leaders Summit on 3/24 at PLSummit.ai. Founder @ Delight Path. 2x best-selling author. New book “Eureka” now available. Author of “Product-Led Onboarding” (+40K copies sold).

The AI Product Leaders Summit is back on 3/24 with 15 speakers. 500+ product leaders already registered. Join free: https://lnkd.in/gWfqMNZN

Every speaker is actively building AI products or leading teams through AI transformation right now. No theory. Just what's actually working (and what flopped).

The lineup:

→ Deepti Pradeep  and her team (Adobe) on how Photoshop got 100k+ of users in 30 days by launching inside ChatGPT
→ Jacob Bank (Relay.app, ex-Google Gmail/Calendar) on the 3 AI agents every product leader should "hire"
→ Mickey Alon (Foldspace AI) on Agent-Led Growth—when your product does the work for users
→ Christine Itwaru & Katy Nardozzi (Userflow) on dogfooding their way to better product decisions
→ Joe Formica (Lyssna) on where AI misleads product decisions (and how to avoid it)

Plus two expert panels:

→ Angela Sze (Sr. Director of Product at Fullstory), Shannon Vettes (CEO/CPO at Usersnap), Lauren Schuman (VP of Product Growth at Close) on shipping AI features without losing customer trust
→ Betsy Shaak (VP Product Voxpopme), Greg Leach (Sr. Director at 7shifts), Partho Ghosh (VP Product @ Uberall), and Priyanka Sahni (Product Lead at Meta) on how product teams are using AI to cut the busywork

Here's what you'll walk away with:

1. How Adobe turned ChatGPT into a growth channel (and whether you should too)
2. Which AI agents actually save PMs time vs. pure hype
3. How to ship AI features without confusing users or breaking trust
4. Where AI creates blind spots in product decisions

March 24th. 10 AM - 3:30 PM ET. Virtual. Free.

Register for free: https://lnkd.in/gWfqMNZN

What's the biggest challenge you're facing with AI products right now?

PS. Tag a product leader who needs to see this. They'll thank you for it. 😊

It's been 2 years since I've had a podcast show. Tomorrow, that changes! Product Leaders Lab by Delight Path drops at 8 am ET. 🎉


I waited because I didn't want another show. I wanted something that actually aligned with what I'm building—a media and community brand for product leaders.

The first episode is "The AI Adoption Pressure."

Your team is scrolling LinkedIn, seeing posts about AI replacing jobs. Leadership is pushing hard on adoption. Everyone's overwhelmed. No one knows where to start.

Two product leaders faced this exact moment. Same pressure. Completely different approaches.

Greg Leach (Sr. Director/GM of Expansion Revenue at 7shifts) built a cross-functional AI committee. Volunteers from every department. Monthly demos drawing 100+ people. Department budgets for experimentation. Bottom-up learning across the entire company.

Joseph King (Sr. Director of Product at Crucial Learning) took a different path. His team invested in sending four leaders to Kellogg for AI certification. Frameworks first. Leadership alignment before company-wide rollout. Top-down, methodical approach.

Both worked. But for very different reasons.

This episode breaks down what each leader did, why they chose their approach, and what you can learn from both paths.

No generic advice. Just real decisions, real trade-offs, and real outcomes.

🎧 Search "Product Leaders Lab" on YouTube, Spotify, or Apple Podcasts.

Tomorrow. 8 am ET. See you there!

The Product Leaders Lab podcast show drops 2/24. 🎉 I can't wait to share real stories from product leaders. Here's a sneak peek at what's coming in Season 1:

→ Greg Leach (Sr. Director of Expansion Revenue @ 7shifts) - How creating an AI adoption committee with 15% of his company reduced automation tasks from hours to minutes—without hiring a single AI expert.

→ Michelle Green (Director of Product @ Cohley) - Why showing designs to customer success before they're "completely baked" saved her team from building the wrong AI feedback flow.

→ Christine Itwaru (VP of Product @ Userflow) - What happened when her "hands-off approach" to build trust led to the biggest launch failure of her career—and how she recovered.

→ Matt LeMay - How he recovered from a feature launch failure and how his team showed him grace.

→ Joseph King (Sr. Director of Product @ Crucial Learning) - How this product leader cut through the AI noise—turning curiosity into capability and education into strategic advantage.

→ David Pereira - Why stepping back from product decisions as a new leader felt like giving up control—until he realized his team was his product now.

→ Shannon Vettes (CPO @ Usersnap) - How she made the biggest bet of her career only 6 months into her leadership role with an AI feature that changed the trajectory of the company.

→ Netali Jakubovitz - How she created an entirely new role called "Prompt Ops" to scale AI across her platform without drowning her team.

And many more. I'm still recording episodes for Season 1.

The Product Leaders Lab by Delight Path is not another interview show. Here's how it works:

One tough scenario. Two veteran product leaders who've lived it. Completely different approaches. Documentary-style editing (20-25 min, not 60+ min rambling).

If you're a VP, Director, or Head of Product with a defining leadership moment you want to share, DM me or tag them below. I'm looking for more guests!

Launching Tuesday, February 24, 2026. Stay tuned!

Building a community for product leaders (VP and Director-level). Founder @ Delight Path. 2x best-selling author. New book “Eureka” now available. Author of “Product-Led Onboarding” (+40K copies sold).

Most product onboarding fails because of "click tax." More clicks = higher drop-off. AI can fix this. Here's how...


First, here's what the traditional flow could look like:
→ Click on Document Templates
→ Pick a template
→ Update the template
→ Save and send

4 steps. Each one adds cognitive load. In B2B, it's worse. You've got multiple personas with different expertise, different outcomes they're chasing.

One-size-fits-all education doesn't work.

AI can fix this. The shift: Don't educate → generate.

Instead of teaching users how to navigate your platform, help them generate the outcome directly.

Anvil did this. Now users just describe what they need: "Create a template for a B2B SaaS purchase agreement."

Then they watch it get built. Custom-made for them.

From 4 steps to 2. From education to generation.

Tools like Foldspace AI are making this possible without custom code. Your team doesn't have to build an agentic experience from scratch.

This is where activation is headed. Less hand-holding. More instant value.

How are you using AI to reduce click tax in your product?

Product Leaders Lab show drops next week. And honestly? It's never been harder to be a product leader.

The pressure to ship AI features. The endless stakeholder alignment. The decisions that keep you up at night.

Product Leaders Lab by Delight Path is where real product leaders share how they handled their toughest moments.

The decisions.
The tradeoffs.
The consequences.

Featuring stories from leaders at Google, Spotify, and more.

No theory. Just real leadership.

📅 First episode drops February 24

🎧 Follow & subscribe:
YouTube: https://lnkd.in/g2FsrjUb
Spotify: https://lnkd.in/gWwS-Rv8
Apple: https://lnkd.in/gAzQJb7Q

See you there.

Building a peer community for product leaders (VP and Director-level). Founder @ Delight Path. 2x best-selling author. New book “Eureka” now available. Author of “Product-Led Onboarding” (+40K copies sold).

Episode 1 of Product Leaders Lab is officially LIVE. 🎉 Leadership is pushing AI. Your product team is overwhelmed. They're watching what you do next. What do you do? 

Two product leaders faced this exact moment. Same pressure. Completely different solutions.

Greg Leach (7shifts) built a cross-functional AI committee. Volunteers from every department. Monthly demos drawing 100+ people.

Joseph King (Crucial Learning) was one of four leaders from his company who joined the Kellogg School of Management's AI certification. Frameworks first. Leadership alignment before rollout.

Bottom-up vs. top-down. Both worked. But for very different reasons.

This episode breaks down what they did, why they chose their approach, and what you can learn from both paths.

🎧 Search "Product Leaders Lab by Delight Path" on YouTube, Spotify, or Apple Podcasts.

💬 Drop your biggest takeaway in the comments.
🔁 Share this with a product leader feeling the AI pressure.

PS. Thank you to the founding partners of the Product Leaders Lab: Userflow, Lyssna, and Foldspace AI. They've made this possible and whole 10-episode season possible.

PMs have been waiting on devs to build prototypes for decades. That's changing with Claude Code. So, I'm hosting a free workshop about it.

Jerome Valdez (Head of Product Design at Plotly, 20+ years experience) will share his process for building AI prototypes with Claude Code and Cursor—the tools he uses daily to ship working prototypes in hours, not weeks.

In this session, product managers will learn how to:

→ Validate ideas before committing engineering resources
→ Test concepts with users and stakeholders faster
→ Stop waiting for dev capacity to explore new directions

Jerome's tested Replit, Bolt, Lovable, Gemini, Windsurf, and more. He'll show you which tools actually work (and which don't).

This isn't theory. It's a live demo of his real workflow.

📅 Thu, Feb 26, 2026
🕛 12:00 PM EST (1 hour)
💻 Virtual (Zoom)
💰 Free

239+ product folks have already signed up.

Sign up for free here: https://lnkd.in/g5dGd3qB

Can't make it live? Register anyway, and I'll send the recording. 

But, you'll miss the live demo and Q&A.

See ya there!

A product leader recently told me their team spent 6 hours a week just looking at dashboards. Not fixing things. Not improving onboarding. Just checking metrics to see if something broke.

"We have all this data," she said. "But we're always reacting, never ahead of it."

This tracks with what I'm seeing across product teams.
You've got analytics. You've got dashboards. You've got behavior data.

But you're still playing detective, manually hunting for what changed, why it matters, and where to fix it.

So, when I saw FlowAI Insights by Userflow, it caught my attention.

It flips the monitoring model. Instead of you watching dashboards, it watches your flows and flags what needs attention.

Drops in completion rates. The exact step causing friction. Only the high-impact stuff.

Then it links directly to where you fix it.

The part I keep thinking about: teams are catching issues before users complain. Spikes in errors, step drop-offs—the silent killers that usually take weeks to surface.

Less time analyzing. More time improving.

Honestly, this feels like where product ops is headed. Proactive instead of reactive.

Are you spending more time monitoring than actually fixing things?

If you want to check it out: https://lnkd.in/g7msgNFg

ChatGPT isn't just a tool anymore; it's a growth channel. It's how Adobe got 100K+ new users in 30 days. They're sharing exactly how they did it...


Most product leaders are asking: "How do we add AI to our product?"

Adobe asked a different question: "How do we get our product INTO AI platforms?"

That reframe led to one of their boldest growth bets.

They launched Photoshop inside ChatGPT. Six weeks. Ungated. No login required.

Here's the shift that matters:

Instead of treating AI as a feature to bolt on, Adobe treated AI platforms as the new top of funnel.

Think about it:

→ Millions of people already inside ChatGPT daily
→ Zero friction to try Photoshop (no login, no paywall)
→ Users discover Adobe where they already are

This isn't about adding AI to your product anymore.

It's about getting your product in front of AI users.

Want to hear the full story?

Deepti Pradeep (Sr. Director of Product Management, Growth at Adobe) is sharing the decision, the trade-offs, and what they learned—along with her team members Anthony Lewis (Principal PM) and Shalini Ahuja (Senior PM, Photoshop).

They're speaking at the AI Product Leaders Summit I'm hosting.

📅 Tuesday, March 24 | 10 AM - 3 PM ET
💻 Virtual. Free.

Register here: https://lnkd.in/gWfqMNZN

What AI platform could be YOUR distribution channel?

🚀 Only 3 days to go! The first episode of Product Leaders Lab drops this Thursday! 🎙️ Don’t miss it, follow us and turn on notifications so you’re ready!

#ProductLeadersLab #Countdown #ProductManagement #LeadershipJourney #TuneInThursday

AI isn't optional anymore. It's the future of your business. But forcing it with memos and hoping it'll stick? That’s a recipe for failure. 

Building an AI-ready culture starts with genuine support, not just mandates. What’s your biggest challenge with AI adoption? Drop your thoughts below.

🎥🎧 Stream the full episode on YouTube, Spotify, and Apple Podcasts! 

#AITransformation #LeadershipTips #FutureOfWork #BusinessGrowth

Your biggest product launch just flopped. Do you protect your team or fix the product first? What do you do? Here's what Christine and Matt did...

Christine Itwaru (VP Product and Design at Userflow) knew two hours in. She immediately went into "mama bear" mode—told her PM to shut out Slack, took the heat herself, and shielded her team while they fixed it.

Matt LeMay (Product Advisor and Author) watched their Bitly relaunch get publicly destroyed. Roger Ebert posted about how terrible it was. People threatened to burn down their office! It took months before they could pivot.

One moved in hours. One struggled for months. Both eventually recovered.

This episode breaks down:
→ How to protect your team when everything's on fire
→ Why setting success criteria BEFORE launch saves you from rationalizing failure
→ When to fix fast vs. when a full pivot is the only path forward

🎧 Stream the full episode on YouTube, Spotify, and Apple Podcasts. 
Search "Product Leaders Lab by Delight Path."

💬 What's the most common reason you've seen product launches fail? 
Drop it in the comments.

🔁 Share this with a product leader who's been through launch hell.

—

Thank you to our partners for supporting the show:

🏆 Userflow: Guide users, answer questions in the moment, and continuously improve product adoption—all without writing code.
🙋‍♀️ Lyssna: Create research studies, recruit the right participants, and gather feedback to shape products users truly love
🤖 Foldspace AI: The AI Operator that turns your SaaS AI-first in days. Their embedded agent understands your users' intent and executes it on their behalf. 

—

My favorite quote from this episode: "Someone's threatening to come to our office and burn it down. Should we delete that or keep it?" — Matt

People rush to add ChatGPT features or AI tools, expecting instant wins. But without a clear strategy, those features often flop after months of effort.

What's your biggest concern with AI adoption right now?

🎥🎧 Stream the full episode on YouTube, Spotify, and Apple Podcasts!

#AIstrategy #ProductGrowth #BusinessInnovation #TechTips

Two years ago, we thought AI would take our jobs. Turns out, standing still is what actually will.

I talked to Joseph King, Sr. Director of Product at Crucial Learning, about how his team went from fear to treating AI as a collaborator.

But here's the part that stuck with me:

His company had an AI strategy. It just sat in a Slack channel nobody checked.

Teams didn't know the company's actual stance on AI. So they guessed. Or did nothing.

The fix wasn't complicated. Document it. Share it. Make it visible.

Most companies aren't failing because they lack an AI vision.

They're failing because nobody knows it exists.

Does your team actually know your company's AI stance? Or is it buried somewhere?

🎥🎧 Stream the full episode on YouTube, Spotify, and Apple Podcasts. Search "Product Leaders Lab."

Meet Ramli John, the host shaping Product Leaders Lab and bringing product leadership to life! 🚀 Watch, engage, and leave a comment with your questions!

#ProductLeadersLab #MeetTheHost #DelightPath #LeadershipStories #ProductInsights

Wes Bush

Product-led coach helping founders scale from 6 to 8-figures in product-led revenue. Author of the bestselling book, Product-Led Growth.

Over the last 9 years, I’ve worked hands-on with 400+ SaaS companies, helping them unlock $1B+ in self-serve revenue through Product-Led Growth (PLG).

Six years ago, PLG was a choice.
Today, it is table stakes.

Recently, Brex published a list of the 50 fastest-growing software companies.
ALL of them have a PLG motion.

If you want to win in the SMB or Mid-Market space, you cannot survive without PLG in 2026.

What separates the winners is not whether they have PLG.
It is how strong their PLG motion is.

The best PLG motions showcase value in minutes and expand rapidly without adding headcount. Weak PLG motions get stuck in linear growth.

That is what I help founders fix in three ways:

➡️ Is PLG is right for you?

I wrote the bestselling book, Product-Led Growth: How to Build a Product That Sells Itself, to help you determine if PLG is the right strategy for your business. 

You can read it for free at ProductLed.com/Book - my treat!

➡️ What’s the best approach to scale up PLG?

After two years of research and working with hundreds of companies, I discovered the 9 essential elements that separate PLG success stories from the rest. 

I break it all down in The Product-Led Playbook.

You can grab a copy at ProductLed.com/Playbook, or watch my free masterclass to see the entire process in action: ProductLed.com/Masterclass

➡️ Ready to scale up?

If you’re ready to scale and need hands-on help, our ProductLed Implementers are here. They aren't consultants - they are experienced PLG operators who want to roll up their sleeves and work alongside your team to help you address your biggest growth bottleneck, whether that's getting more users to sign up, upgrade, or get to value.

Since we only work with a handful of clients at a time and guarantee growth, you must apply to work with us at ProductLed.com

Let’s turn your product into a growth engine and scale your business the product-led way. 🚀

CEO & Founder

We help you build a successful product-led business.

Start with our free ProductLed Masterclass 👉 productled.com

We asked 60,000 people: “who’s the best PLG operator you know?” 

and we researched who are (or were) behind the world’s best PLG companies (think early-days Slack, Notion, Miro, Etc.). 

Here are the results (2026 world rankings): 

#1 - Elena Verna
#2 - Giancarlo 'GC' Lionetti
#3 - Merci Victoria Grace
#4 - Melissa Tan
#5 - Wes Bush
#6 - Lauryn Motamedi
#7 - Laura Schaffer
#8 - Casey Winters
#9 - Jacob Bank
#10 - Kieran Flanagan
#11 - Leah Tharin
#12 - Ben Williams
#13 - Salvador Torres
#14 - Anton Osika
#15 - Carrie McMahon
#16 - Patrick Campbell
#17 - Esben Friis-Jensen
#18 - Ramli John
#19 - Bryan Ng
#20 - Kyle Parrish
#21 - Melissa Ross
#22 - Josh Sookman
#23 - Tommy Fink
#24 - Henrique Cruz
#25 - Casey Hill
#26 - Hila Qu 曲卉
#27 - David Barron
#28 - Mario Araujo
#29 - Kyle Poyar
#30 - Brian Balfour
#31 - Kate Syuma
#32 - Shaun Clowes
#33 - Meghan Gill
#34 - Michael T.
#35 - Shuo Wang
#36 - Eitan Helman
#37 - Raaz Herzberg
#38 - Shane Murphy-Reuter
#39 - Hiten Shah
#40 - Sam Crowell Richard
#41 - Jon Noronha
#42 - Etgar Bonar
#43 - Yaakov Carno
#44 - Aggelos Mouzakitis
#45 - Andrew Capland
#46 - Adam Fishman
#47 - Ravi Mehta
#48 - Jiaona "JZ" Zhang
#49 - Albert Cheng
#50 - Maor Shlomo
#51 - Francois Bondiguel
#52 - Sian Townsend
#53 - Brian de Haaff
#54 - Jules Walter
#55 - Amol Avasare
#56 - Arik Marmorstein
#57 - Dave Boyce
#58 - Sean Ellis
#59 - Rachel Hepworth
#60 - Jessica Gilmartin
#61 - Aaron Cort
#62 - Adam Robinson
#63 - Jason Fried
#64 - Alex Turnbull
#65 - Yasser Elsaid
#66 - Guillaume Moubeche
#67 - Nicolae Rusan
#68 - David Okuniev
#69 - Jan Oberhauser
#70 - Karim Atiyeh
#71 - Mickey Alon
#72 - David Barrett
#73 - Gary Brewer
#74 - James Hawkins
#75 - Nils Schneider
#76 - Daryna Kulya
#77 - Kurt Mackey
#78 - Koen Bok
#79 - Drew Banin
#80 - Patrick Thompson
#81 - Chris Bach
#82 - Melissa Kwan
#83 - John Foreman
#84 - Ryan Singer
#85 - Krithika Shankarraman
#86 - Pedro Magriço
#87 - Nick Chong
#88 - Harley Finkelstein
#89 - Hugh Molotsi
#90 - Ilan Rabinovitch
#91 - Jim Gochee
#92 - Neil Rahilly
#93 - Dylan Fox
#94 - Steffen Tjerrild
#95 - Ben Edelstein
#96 - Mauricio Idarraga
#97 - Carina Fonseca
#98 - Nick Rico
#99 - Fredo Tan
#100 - Rodrigo Fernandez
#101 - Justin Gallagher
#102 - Adam Jarczyn

Couldn’t tag everyone on this post. In the comments! 

Who do you know that’s not on this list, but should be? 

Let me know below 👇

For the last 3 months, I asked 10,000+ SaaS people who the world’s best PLG operators are. Here are the 2026 rankings.

(You won’t have to comment below to get it.)

Also on this page: the world’s top 100 Product-Led companies.

How did we rank?

For operators, we used:

• Votes from our PLG community of 60,000+ people
• Nominations from senior operators and founders we know
• Our own research (looking at tactical PLG accomplishments. For example, Laura Schaffer scaled DigitalOcean's self-serve cloud adoption. Carrie McMahon set up the sales-assist motion at Coda, etc.)
• We looked at who the operators behind the top 100 PLG companies are and where they work

For companies, we ranked based on:

• Revenue per employee (adjusted for funding, meaning we penalized companies with ARR lower than total dollars raised)

For example, Gamma (#2) reached $100M in revenue with 50 people and has a world-class AI-enabled PLG motion.

• Stellar PLG motion (do they have a world-class PLG motion?)
• Scale (have they reached massive scale with a self-serve offering?)

You can also filter companies based on whether they are AI-native or have reached WARP speed (0–100M in 24 months or less).

Why did we spend 100+ hours putting this together?

So people know what excellence looks like. Where the edge of innovation is in PLG. Who to look up to.

Which companies’ onboarding flows to get inspiration from. Who to learn from and get inspired by.

You can find the rankings at productled(dot)com/top-100.

You can go vote or nominate your favorite operators right now. We’ll regularly update the rankings so they reflect reality, and weigh votes based on voters’ actual PLG and SaaS experience.

Where I need your help → This includes many of the well-known “all stars,” but we’re now building a second list highlighting “your favorite operator’s favorite operator.”

The behind-the-scenes builders. The ones who may not be as visible but absolutely deserve recognition.

Who’s that person in your org? Tag them below 👇

Here's the link: productled.com/top-100

I have to give a shoutout to Nathan Latka. Without his public data, the funding-adjusted RPE would have been a massive pain to calculate.

Genspark AI reached $155M ARR in 10 months but I still got stuck getting to  value when I onboarded.

Here’s my full teardown of their PLG motion, and what I would change to get to $1B if I was in charge of self-serve growth 👇

DM me to get the full 10-minute Loom of me onboarding and giving feedback.

Oh, and Wen S. is coming on the pod. Stay tuned.

Genspark AI - PLG Teardown

Right now, founders have two choices.

One, they can pretend like they're living under a rock with their product, even if they have strong product-market fit right now. Or two, they can realize that product-market fit evolves faster than ever before with AI.

Let’s say you’re running a $45M business.

Growth is steady.
Churn is manageable.
Customers are happy.

On paper, everything looks solid.

But AI is compressing time.

If someone enters your category and delivers the same outcome in a fraction of the time, the equation changes fast.

The issue is → is your product still the fastest path to value?

That’s where the hard decision shows up.

Do you keep optimizing the current product?

Or do you build the version that makes your current product feel slow?

I’ll be direct: You should build the version that replaces you.

Design the AI-native experience that gets users to value dramatically faster.

Because if you don’t, someone else will.

And when they do, growth shifts quickly.

You’ll notice churn creeping up.
You’ll run experiments.
You’ll tweak onboarding.
You’ll adjust pricing.

But if the core workflow is slower, optimization won’t save you.

So the choice becomes simple.

Ultimately, these are the two choices you have to make:

1. Adapt or die: You must decide to disrupt yourself.
2. Be disrupted: Continue as you are and face the consequences.

That’s the decision.

I’m going to be blunt.

This was the best interview we’ve ever recorded.

Because Wen S. (COO + co-founder of Genspark AI) doesn’t talk in startup clichés.

He explains, in plain language, how a 50-person team hit $100M ARR in 9 months, then $155M ARR by month 10… with almost no marketing until after $100M.

Here are the ideas I can’t stop thinking about.

1) People want the job done. Period.

Wen said something that reframed the whole category for me:

People look for information because they need to finish something.

That’s why Genspark shifted the goal from “answer questions” to “finish work.”

2) Their “secret sauce” is boring, but effective: output quality.

Genspark put 99% of their energy into one thing: make the output so good you can ship it.

Work you can use right away.

That obsession is what made word-of-mouth do the heavy lifting early.

3) They refused to spend on marketing.

Most startups pour fuel on distribution early.

Genspark avoided ads on purpose.

Only after they crossed $100M ARR did they say: “Okay. This must be real. It’s time.”

4) They made a Super Bowl ad in 10 days (10x’d growth).

Yes, they ran a Super Bowl spot.

But the part that matters is they made it happen in ~10 days.

Script and creative generated using Genspark.
Shot fast.
Shipped fast.

Traffic jumped 10x overnight.

5) “Focus on one thing” is becoming bad advice.

In the old world, building multiple products meant multiplying teams and coordination.

In the AI-native world, you can reuse the same context across outputs.

People don’t want 12 tabs and 8 subscriptions. They want one place where context carries across everything.

6) How 50 people ship like 500.

Wen shared that 90%+ of their code is written by AI.

Instead of a classic org chart (frontend team, backend team, DevOps, design), they built a platform and kept ownership tight.

7) Why AI companies are hitting warp speed growth.

Adoption comes from two directions at once:

Bottom-up: individuals try it and get value immediately.
Top-down: leadership feels urgency and formalizes adoption.

If you aren't growing at warp speed, attend WARP Week from March 2nd to March 7th.

Save your spot: https://lnkd.in/gQfq4hYd

8) The real proof is revenue.

A consultant who used to spend weeks coordinating research and building decks now pays $25/month, gets the grunt work done in days, keeps more margin, and serves 5–6x more clients.

9) Their only advice to founders: obsess over the product.

If you have a great product, people will notice.

Stay paranoid. Keep shipping. Keep raising the quality bar.

That’s the game.

👉 Listen or watch the episode:
https://lnkd.in/geRJEhTk

“60 seconds to value? That’s impossible for my product.”

I hear this every time I talk about WARP.

Here’s what I tell them:

Cursor writes complex code in seconds.

Midjourney creates complex art in seconds.

Lovable builds entire applications in seconds.

These aren’t simple products. The difference is who does the work.

Old way: “You do the work and get X result.”

New way: “Tell me what you want done. Boom, it’s done.”

Even if you can’t hit 60 seconds today, what if you went from 3 days to 5 minutes?

That’s still a massive moat. And the window to capture it is now, while users are still actively trying new tools.

Wait until everyone has settled on their defaults and the cost of winning that same user goes up 10x.

That’s what we’re building in WARP Week.

Starts Monday. Link in comments.

I spoke with a $50M ARR founder yesterday.

He said something I haven’t stopped thinking about:

“We have product-market fit right now. But that’s PMF pre-AI.”

Let that sink in.

Most users aren’t deeply loyal.

They’re accepting the friction because there hasn’t been a dramatically better option.

If someone builds a tool that delivers the same outcome in 60 seconds instead of 30 minutes, switching becomes obvious.

And here’s the part founders don’t like to admit:

That company is being built right now.

Today.

Very likely by someone who understands your category inside out.

I’ve been studying what I call WARP speed companies.

The ones going from zero to $100M ARR in under 12 months.

They share a pattern.

Zero friction to value.

Users reach their first meaningful outcome in 60 seconds or less.

That’s the new bar for product-market fit in the AI era.

The question is no longer “Do people want this?”

It’s “How fast can they experience the outcome?”

Because speed to value is becoming the moat.

So the real question is simple.

If AI is going to compress your workflow, will you be the one compressing it?

Or will someone else?

10 months ago, Wen S. launched Genspark.

Today, it’s at $155M ARR with ~50 people.

For the first time, he shared exactly how they did it:

1. They didn’t build a better chatbot.

They rebuilt “work.”

Instead of answering questions, Genspark focuses on finishing tasks: decks, models, briefs, decisions.

2. They let individuals pull the product in.

Adoption started bottom-up.

Employees used it because it was immediately useful. Then leadership stepped in to formalize it.

3. They refused to spend on marketing until after $100M ARR.

No big ad budgets.

No artificial fuel.

If it grew, it had to be because the product earned it.

4. They made a Super Bowl ad in 10 days.

After product-market fit was obvious, they took a high-leverage swing.

Traffic jumped 10x overnight.

5. They built a 50-person team that ships like 500.

Over 90% of their code is AI-written.

Weekly releases.

70+ models orchestrated under the hood.

As Wen said, the entire team’s obsession is output quality.

Not features!

The formula is clear → Get users to real value fast. Make the output so good they can ship it. Keep raising the bar every week.

Individuals adopt.

Companies follow.

Growth compounds.

That’s what AI-era product-market fit looks like.

🎧 Listen to the full breakdown: https://lnkd.in/geRJEhTk

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The Battle

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