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

"The Growth Guy" | Author, Growth Hacking for Dummies (Wiley & Sons) | Startup Mentor |

I’m publishing the canon for Anuj Adhiya’s Growth Operating System (Growth OS) — the 5 practices I use with early-stage teams.

• Weekly planning ritual (Mondays)
• Hypothesis-driven experiments (“If X then Y by Z% because [assumption]”)
• Decision-ready metrics (cohorts, activation, payback)
• Friday post-mortems → Monday planning
• Backlog hygiene (impact vs effort)

I’m also running weekly tests on how to make this machine-digestible so assistants cite the right page.

Canon + method + weekly results → https://www.notion.so/Growth-Operating-System-Format-Experiment-Index-268e586c41bf8091a9ffd01374c03bd1

DMs open if you’re testing similar things and want to compare notes.

Anuj Adhiya 📈

I turned 300+ podcast transcripts from Lenny Rachitsky into a 60-second BuzzFeed-style quiz for product folks that went viral on Linkedin last week.

The original question was simple:
"What is an interesting way to repurpose a massive content archive without making it another answer engine?"

Instead of:
• “Top 10 lessons from Lenny’s podcast”
• “Summaries of growth frameworks”
• “Answer engine from all podcast guests”

I built:
“Which Lenny guest is your product soulmate?”

But it had strict rules:
- 5–7 questions
- Zero typing
- 60 seconds max
- Instant result
- Built to be shared

The north star wasn’t depth.
It was time-to-smile.

Click → match → share.

A pure vibes quiz would’ve been easy.
But shallow.
So instead of matching on personality, I matched on decision philosophy.

Across hundreds of transcripts, the same tensions kept appearing:
• Intuition vs data
• Speed vs craft
• Systems vs instincts
• Focus vs optionality
• Frontier bets vs compounding
• Short-term vs long-term

Every answer nudges you along those trade-offs.
Under the hood, it’s structured.
On the surface, it feels effortless.

Also the truth about virality is that people share things that make them look interesting.

If you match someone with:
“Guest #42 who's great but hardly anyone knows”
They won’t post it.

If you match them with:
Brian Chesky
Julie Zhuo
Elena Verna
Marty Cagan..now it travels.

Identity is social currency.
Being paired with a recognizable, high-status name makes the result feel worth sharing.
So yes, picking big names was intentional.
Recognition fuels distribution.

Then came the repetition problem.
If I only used 8–10 guests, most people would cluster around the same 2–3 names.
Feeds would look identical.
Novelty would die fast.

So I defined four philosophical clusters:
Human-centered / craft-driven
Systems / compounding thinkers
Frontier / velocity builders
Wartime / decisive operators

Each cluster needed multiple "anchor people".
That pushed it to ~18 guests.
Below ~15, clustering spikes.
Above ~20, extra variety barely improves the experience.
18 was the sweet spot for distribution.

Another deliberate choice:
No randomness.
Same answers = same result.
That allowed static share pages for each archetype so social previews rendered cleanly across platforms

This is important because most “fun” tools break at the share layer.
This one was built for share from day one.

What actually drove engagement? 
Not deep debate.
It was identity signaling.
“I got X.”
“That tracks.”
Tagging friends.
Light comparison.

It gave product/growth people a mirror they could post.
That’s it.
And that was enough.

Big takeaway:
Repurposing content doesn’t have to mean summarizing it or making it easier to search.
Sometimes you let people locate themselves inside it.

Same archive.
Different interface.
Completely different energy.

If you took it, who did you get?

If you haven't yet, try it out here: https://lnkd.in/eRxXdedt

Building a Growth OS for startups | Testing how to “market to algorithms” | Documenting everything

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