Founder/CEO @ LEANSTACK | Bestselling author and founder

I have bootstrapped several products to millions of users and worked with thousands of early-stage entrepreneurs worldwide - helping them systematically find repeatable and scalable business models using my battle-tested playbooks. 

Instead of:
-Spending several months building a product you hope people will buy.

Imagine a world where you:
- Spend several weeks defining a product you know people will buy.

For aspiring or early-stage founders:

If you’re looking to bootstart your idea, consider joining my 30-day Business Model Design Challenge below: 

You'll learn how to:
- Find or test a big idea worth pursuing,
- Design a business model blueprint,
- Stress-test your idea before investing time, money, and effort. 

Join the next Business Model Design Challenge:
https://runlean.ly/challenge

Ash Maurya

I've been working on something new.

After a decade of teaching Running Lean through frameworks and workshops, I realized something was missing. Founders understood the Lean Canvas intellectually. They could explain Demo-Sell-Build. They got it.

And then they'd go right back to building inside their heads.

The problem wasn't understanding. It was *feeling*. You have to feel the Innovator's Bias before you can overcome it.

So I did something I've never done before.

I wrote a novel.

THE INNOVATOR'S BIAS — a startup novel. Coming April 7th.

Pre-order now on Kindle.

I help founders build business models that scale. Author and creator of Lean Canvas.

These 2 boxes of the Lean Canvas are the outer pillars that carry your business model.

If you get these assumptions wrong, it’s easy to see how everything else in your business model falls apart.

- You end up describing a solution that no one wants (not desirable).
- Even if you build the solution you're already envisioning (feasible),
- No one buys it (not viable).

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The Just Start Manifesto (updated)
==========================
1. Entrepreneurs Are Everywhere.
2. There is No Better Time to Start.
3. Most Products Still Fail.
4. The Number One Reason Why Products Fail: Building Something Nobody Wants. 
5. The Number Two Reason Why Products Fail: Not starting. 
6. You Don’t Need Permission to Start.
7. Don’t Write a Business Plan. Sketch a Business Model.
8. Take Stock of Your Key Beliefs.
9. Take Stock of Your Key Metrics.
10. Take Stock of Your Key Insights.
11. Have Faith in Yourself. Be Ruthless With Your Ideas.
12. Don't Start With an MVP.
13. Not Faux Validation, But Traction
14. Love the Problem, Not Your Solution.
15. Sell Before You Build.
16. Bootstrap Your Way to Early Traction.
17. Focus on Time Versus Timing.
18. Value Your Time Correctly.
19. Avoid Premature Optimization.
20. Practice Right Action, Right Time.
21. Speed of Learning is the Only Unfair Advantage.
22. Speed of Learning x Speed of Execution = 100x Founder.
23. Remove Failure from Your Vocabulary.
24. It’s Time to Act on Your Big Idea.
25. Just Start.

I build systematic frameworks for early-stage founders. Author and creator of Lean Canvas.

The Just Start Manifesto

A feature isn't "done" when the code is shipped.

It's done when it provides validated learning from customers.

But validated learning is still a trailing indicator of what customers want. 

We can do better. 

Demand validation, sell before you build, is a leading indicator of what customers want.

This simple redefinition changes everything about your development process.

Demo-Sell-Build >> Build-Demo-Sell

The Weekend Canvas Exercise

Try this right now. It takes 30 seconds.

Pull up your Lean Canvas. Cover the Solution box with your hand.

Now explain why your business matters.

If you struggle — if the pitch falls apart without the solution — you're building solution-first.

The problem and customer should carry the pitch on their own. The solution is just the delivery mechanism.

I do this exercise every time I update my canvas. It's uncomfortable every single time. That discomfort is the point.

When I built CloudFire, the solution WAS the pitch. "A photo sharing app that..." Take away the app, and there was nothing. The problem wasn't specific enough to stand on its own.

When I built LeanSpark, the pitch without the solution was: "Founders waste months building products nobody wants because they skip structured discovery." That problem stands on its own. The solution is one of many possible responses.

Your problem should be so clear, so specific, and so painful that the audience nods before you ever mention what you built.

Try it. Let me know what you find.

Hot take: AI is making startups fail faster.

Not on purpose. But here's what's happening:

Founders use AI to generate code in hours. Ship MVPs in a weekend. Launch products in weeks instead of months.

Sounds great, right?

Except they're shipping untested ideas at record speed.

The build cost collapsed. But the failure rate didn't. Because the bottleneck was never "can I build it?"

It was always "should I build it?"

AI tools that help you build faster are accelerating the wrong part of the process. You're arriving at the wrong destination — just sooner.

The founders who win in the AI era aren't the ones who ship fastest. They're the ones who think clearest about what to ship.

That means starting with your business model. Stress-testing your assumptions. Running experiments before writing code.

LEANSpark is an AI tool that helps with the part most AI tools ignore — the thinking before the building.

Because the most expensive line of code is the one that solves a problem nobody has.

Free to try. No credit card required.

Every founder I coach thinks their business model is solid. Then we run the stress tests.

The pattern is always the same: strongest on Feasibility. Weak on everything else.

"Can I build it?" Yes.
"Do people want it?" I think so.
"Will the economics work at scale?" ...
"Why now and not 5 years ago?" ...
"What compounds in my favor over time?" ...

Two out of seven isn't a business model. It's a hunch with a prototype.

The blind spots don't kill you on day one. Cracks appear in month 9, and they kill you at month 18 when you've hired a team, raised money, and can't figure out why growth stalled.

What's the dimension you've never stress-tested?

I interviewed 47 customers. All of them said yes.

"Love the concept."
"Would definitely use this."
"When can I sign up?"

So I built it. 9 months. Full product. A photo-sharing app called CloudFire.

500 people signed up. Revenue trickled in. And then I did a 5-minute calculation that I should have done on day one, which proved my model wasn't viable for my business goal. 


47 people told me what I wanted to hear. Zero people told me the truth.

The lesson I carry everywhere now: Compliments are not evidence. Enthusiasm is not commitment. The only validation that matters is someone reaching for their wallet.

Three levels of customer evidence:
1. They SAY they have the problem
2. They SPEND money solving it today
3. They'll COMMIT money to YOUR solution

Most founders stop at level 1 and call it "validated."

Level 3 is where the truth lives.

What's the most misleading validation you've ever received?

Why "Talk to Customers" Is Bad Advice

"Talk to customers" is the most common startup advice. It's also the least useful.

Because HOW you talk to them matters more than WHETHER you talk to them.

Bad customer conversations:
- "Would you use a product that does X?" (Leading question — always gets yes)
- "What features would you want?" (They design your product for you — badly)
- "Is this a big problem?" (They agree to be polite)

Good customer conversations:
- "Walk me through the last time this happened." (Specific, past tense)
- "What did you do about it?" (Reveals actual behavior)
- "How much did that cost you?" (Quantifies the pain)

The difference: bad conversations confirm your bias. Good conversations reveal reality.

The single biggest upgrade is:

Stop asking what people would do. Start asking what they already did.

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Meet the Lean(er) Canvas.

While sketching out a complete Lean Canvas is a great exercise for deconstructing an idea into a business model, here's an even faster ideation tool I use at the outset of all my ideas.

I focus attention on just the two outer boxes of the canvas: Customer segment and Problem.

These are the outer pillars that carry your business model.

If you get these assumptions wrong, it’s easy to see how everything else in your business model falls apart.

- You end up describing a solution that no one wants (not desirable).
- Even if you build the solution you're already envisioning (feasible),
- no one buys it (not viable).

Yes, just these 4 boxes are enough to prompt you to stress test your idea's desirability, viability, and feasibility.

If your idea doesn't pass these stress tests, your channels and unfair advantages won’t offer any respite.

Your business model is doomed.

Most Lean Canvases I see have this problem.

Trying to be two (or more) businesses at once.

I see this pattern constantly:

- Customer segment says "Small businesses AND enterprises"
- Revenue streams lists "subscriptions AND marketplace fees"
- Problem box describes two unrelated pain points

This is split model confusion. And it's the #1 reason for aimless wandering. 

Too many business models makes your canvas vague and you can't test a vague idea. 

The solution: create multiple smaller focused variants with exactly one business model on them. 

Here's how:

1. Detect the split axis
Is the tension in your customer segments? Your revenue model? Your channels? Your solution?

2. Stress-test independently
Run each variant through the same rigor: viability, desirability, and feasibility. The numbers will tell you which model has the most potential.

3. Choose with evidence, not intuition
Now you're not guessing which model to pursue. You're comparing validated data across focused alternatives.

This is the search mindset.

Most founders skip straight to execution with a single, broad model and spend months wondering why nothing clicks.

The best founders explore 2-3 focused models in parallel and converge on the winner fast.

I built this entire workflow into LEANSpark. It detects the split, generates focused variants in parallel, and lets you stress-test each one independently.

Watch it in action 👇

Simple models help us understand the complex. 

Before investing in any company, Warren Buffett and Charlie Munger use a latticework of mental models to evaluate the company. 

If it passes their tests, they move all in. Otherwise, they do nothing and wait.

Evaluating early-stage ideas is no different.

I have settled on 3 universal (product-agnostic) mental models that I use to
- baseline progress,
- prioritize risks, and
- formulate a “right action, right time” next step.

Here they are: 

1. Lean Canvas: Deconstruct an idea using 12 basic building blocks.

2. Traction Roadmap: Chart key milestones using 5 customer-centric metrics.  

3. Customer Forces: Understand customer behavior using 4 causal forces. 

BELIEFS + METRICS + INSIGHTS = BUSINESS MODEL STORY

Entrepreneurship is like a martial art — you can only learn by doing.

But "doing" without a sparring partner means burning months on the wrong thing.

LEANSpark is the sparring partner. Maps your business model, spots risky assumptions, and designs/runs experiments with you.

Free to try. No credit card.

Your Unique Value Proposition has 8 seconds to work.

That's how long first-time visitors spend on landing pages.

Forget complex benefit statements. Focus on the finished story benefit:

❌ "Eye-catching résumé templates"
✅ "Land your dream job"

Get inside your customer's head, not your product features.

The biggest waste in startups isn't money. It's effort spent on the wrong things at the wrong time.

I've worked with founders who worked 80-hour weeks and made zero progress — because they were doing Stage 3 activities at Stage 1.

Brand redesigns when they hadn't validated the problem. Growth hacking when they didn't have product-market fit. Hiring when they couldn't describe their customer.

Every stage has 2-3 actions that matter. Everything else is noise.

What stage are you at right now, and what are your 2-3?

#RightActionRightTime

Right Action, Right Time

We pre-sold 209 customers in 40 days.

Before writing a single line of production code.

Here's the Demo-Sell-Build playbook:

Most founders go Build > Demo > Sell. 

(Without vibe-coding):
Months of building. Then hoping someone buys.

(With Vibe-coding):
Days of building. Then months of trying to get someone to buy.

We flipped it: Demo > Sell > Build.

Step 1: DEMO.
We didn't build a product. We built a demonstration of the transformation. What does your life look like AFTER using this? We showed that. Perfectly okay to vibe-code here without going overboard on product. A demo is NOT meant to be used by customers. 

Step 2: SELL.
Not "would you use this?" — that's a survey.
Not "would you pay $50/mo?" — that's still a survey.
But "pay $150 to get early-access" — that's validation.
209 out of 307 people committed. 68% conversion rate.

Step 3: BUILD.
Now we knew exactly what to build, who it was for, and that they'd pay. No guessing. No hoping. Just executing against validated demand.

The fear: "But what if the demo isn't perfect?"
It doesn't have to be. That's the point. You're testing demand, not polish.

Building is the most expensive way to test an assumption. And yes, even when AI makes building cheaper, building without validation just digs a bigger future-sunk-cost fallacy sand trap. 

A demo costs hours. A product costs months.

The safest career move in 2026 isn't a promotion. It's validating a business model on the side.

Here's the math nobody talks about:

Your employer is actively figuring out how to do your job with AI and fewer people. That's not cynicism — that's their fiduciary duty to shareholders. Every earnings call now includes "AI efficiency gains." You're the efficiency being gained.

Meanwhile, the same AI that threatens your role has collapsed the cost of starting a company by 10x.

What used to require a co-founder, $500K in funding, and 18 months of runway — one person with domain expertise and AI can now validate in 90 days for under $1K.

The risk equation has flipped. But most people are still operating on the old math:
- Old math: Job = safe. Startup = risky.
- New math: Job = someone else controls your future. Validated startup = you control your future.

I'm not saying quit tomorrow. I'm saying: the skills you've built over 5, 10, 15 years in your industry? Those aren't just resume lines. They're founder superpowers.

You already know the problems. You already know the customers. You already know what's broken.

The only thing you haven't done is validate whether someone will pay you to fix it.

That's a weekend experiment, not a life decision.

What's the one problem in your industry that you see every day and nobody is solving well?

Here's a test for your "competitive advantage":

Can someone replicate it in 90 days with enough money?

If yes, it's not an advantage. It's a head start. And head starts disappear.

Things that are NOT advantages:
- "Our team" (good teams can be hired)
- "Our technology" (technology can be rebuilt)
- "First mover" (first movers get outcompeted by fast followers constantly)
- "Our features" (features get copied in weeks)

Things that ARE advantages:
- Network effects that compound (each user makes the product better for all users)
- Proprietary data that grows with usage (every interaction trains your system)
- Brand trust earned through years of consistent delivery
- Switching costs that deepen over time (not artificial lock-in — genuine integration depth)

The pattern: Real advantages get STRONGER the longer you operate. Fake advantages get WEAKER the more competitors enter.

Fill in the blank: "The longer we operate, _________ gets harder for competitors to replicate."

If you can't fill that in, your advantage is a head start, not a moat.

The Math That Changed How I Build

10 experiments at $100 each teach you more than 1 launch at $10,000.

Same total investment. 10x the learning.

The math:
- 10 experiments = 10 data points, 10 chances to be wrong, 10 opportunities to adjust
- 1 launch = 1 data point, 1 chance to be wrong, 1 expensive lesson

Early in my career, I optimized for launches. Big reveals. Grand openings. Each one felt significant. Most of them taught me one thing: I was wrong about something I could have tested for $100.

Now I optimize for learning velocity. How many assumptions can I test this month? Not how many features can I ship?

The founders who learn fastest don't have bigger budgets. They run smaller experiments.

What's one assumption you could test this week for under $100?

How to build your first startup moat.
Most founders don’t have an unfair advantage to start, and that’s okay.

A true unfair advantage is something that cannot be easily copied or bought. And finding one takes time.

The good news is that you don’t need one at the early stages, since all ideas sound a little crazy at first. 

So, embrace your obscurity as a gift and...

First, hunker down and focus on building a compelling Unique Value Proposition before your Unfair Advantage.

Then lean into what makes your compelling Unique Value Proposition truly unique — something different and better…

Turn that into a Counter-positioning strategy -- something incumbents can't copy without hurting their business model.

You’ll have the beginnings of your first unfair advantage.

CEO @ Fotando | Building AI-ready systems for non-technical companies | Founder @ SalesRing

We help non-technical companies use AI the right way: by simplifying their business first.

Most growing companies want to use AI. 

But the business already feels hard to manage.

1. Information is spread everywhere.
2. Processes aren’t clear.

Adding AI on top of that usually makes things worse…  More tools, more activity, but not much actually changes.

That’s why so many AI projects get stuck in “almost there” for months.

 At Fotando, we help non-technical companies simplify how their business works first and then apply AI where it actually makes a difference.

The goal is real change in 8 weeks, not 18 months. 

If AI feels important for your company but also confusing or overwhelming, feel free to reach out.

Happy to have a straightforward conversation and see if this makes sense for you.

Uladzimir Ausianikau

Today I run a 7-figure business.
But in 2020, I got fired for a weird reason:

I got fired for being too direct.
One day I disagreed with an executive.
I thought I was solving a problem.
They thought I was being insubordinate.
Fired the next day…

But in the end, it was the best thing that ever happened to me.

It taught me 2 lessons:
1. Firstly, how to be honest without being rude.
2. But also, I learned that most people optimize for not getting fired instead of solving the actual problem.

They tell their boss what they want to hear.
And that's why projects fail.

I built my entire business on the opposite:
Honesty and transparency.

I want honest feedback from my employees and they expect the same in return.
This way we build faster, and fix problems.

CEO @ Fotando | AI implementation partner for companies stuck between slow consulting and generic AI tools

Some businesses are still stuck in the 2020 consulting model:
- Hire a “Big Four”
- Wait 6-12 months
- Get a strategy deck
- Find vendors to implement
- Hope it works
By the time you're done, the market has moved.

Here's what changed in 2026:

GenAI collapsed the timeline.

Smaller teams can now outperform bigger companies with bigger budgets.

But only if they learn FASTER.

They need to replace the old model:
- 18 months for "digital transformation"
- Analysis that took quarters, not weeks
- Innovation only enterprises could afford

With the new model:
- Fixed timelines instead of open-ended engagements
- Working solutions instead of strategy decks
- Senior practitioners doing the work

The companies getting ahead are the ones learning fastest.

PS: I built a free assessment tool to show you how fast diagnosis actually works. 

Comment "Need assessment"  for access

In 2026, everyone is building “AI agents” for everything.
This makes me think about what Elon Musk said:

“The most common error of a smart engineer is to optimize a thing that should not exist.”

And this is true in businesses too.

I’ve been building products for 10 years.

And here’s a question I always get back to:

“Does this problem need intelligence, or does it need elimination?”

I've seen companies spend months building AI solutions when the real fix was simpler:

- Change 1 step in the process
- Delete the report nobody reads
- Have a conversation with a collaborator

AI shines when it can 5X your process or free up people for higher-value work.

It’s NOT here to add extra work or steps.

So here’s what you should do:

1. Map the process first.
2. Find the constraint.
3. Then ask: What's the simplest thing that fixes this?

Sometimes it's AI but sometimes it's a “delete button”.

PS: That’s why I builtFotando Global. We start with diagnosis, not technology.

Last week I shared my learnings on LLMs on stage.
This revelation made people the most excited:

“In 2026, every company can operate like a high-growth startup with a small team.”

The same small team can now:
1/ Deep dive into operations (marketing, sales, delivery, finance, legal)
2/ Map the bottlenecks and risks actually limiting growth
3/ Build working experiments in days, not months

Now here's the part that excites me the most:
This isn't just for funded startups or big corporations anymore.
These techniques are now available for traditional businesses.

Here’s what it means for you:
You now have access to the same playbook corporations invest millions in.

2026 is going to be wild!

In 1986, Duracell was stuck at $300M revenue.
In 1996, they got acquired for $7B thanks to this martial artist:

David Shaner was an Aikido master.
Duracell hired him in 1986 to solve a problem no one else could.

The battery industry was broken.
- Every brand squeezed suppliers to near-bankruptcy
- No money left for R&D
- Everyone sold identical products

Shaner changed one thing:
“Stop fighting suppliers, partner with them.”

So Duracell made the first move:
- Stopped demanding impossible discounts
- Gave suppliers room to breathe
- Pooled R&D budgets together

They built a battery that lasted twice as long at twice the price. Same cost per hour for consumers. Dramatically higher margins for everyone.

The result?
They built their entire positioning on “longer batteries”.
The revenue went from $300M to $2.3B.
And in 1996, Gillette acquired Duracell for $7 billion.

This story had a great impact on my life.

One line has stayed with me for 20 years:
"𝘙𝘦𝘭𝘢𝘹𝘢𝘵𝘪𝘰𝘯 𝘤𝘳𝘦𝘢𝘵𝘦𝘴 𝘮𝘰𝘳𝘦 𝘱𝘰𝘸𝘦𝘳 𝘵𝘩𝘢𝘯 𝘧𝘰𝘳𝘤𝘦."

Most AI projects follow the same pattern:

- Month 1: kickoff, demos, excitement
- Month 3: "we're making progress"
- Month 6: "almost there"
- Month 12: it quietly disappears

Companies try to add AI on top of a mess.

Random Excel sheets, unstructured Google Drive, no ownership, no SOPs, and no visibility into what's actually happening.

When I jump into an AI project, the real problem shows up in the first conversation:

"Where is the bottleneck in your business?"

Most executives can't answer because they haven’t audited the workflows.

So they end up taking months to automate chaos.

What they should do instead is use a 2-week sprint methodology:

Week 1 - Diagnose before you build
- Map the entire business flow
- Find where work actually piles up
- Define the ONE constraint worth solving

Week 2 -  Build the smallest thing that moves the metric
- No strategy decks. No 6-month roadmaps.
- A working solution tested against real data
- A clear decision: scale, pivot, or kill

Here, the two weeks of learning beats six months of assumptions.

That’s the power of learning from speed.

I’ve been building products for 8 years.
In 2026, GenAI changes the main bottleneck:

The bottleneck isn't execution anymore, it's knowing what to execute.

Because here’s the truth:

It’s easy to execute fast with AI.

So in a post-AI world, speed of learning is the new unfair advantage.

Here are the differences:

1/ Speed of doing
- Speed of doing means spending 6 months building the wrong thing.
- Then starting over when you realize it doesn't work.

2/ Speed of learning
- Speed of learning means spending 2 weeks discovering it's wrong,
- Then pivoting immediately.

This is why 2-week sprints beat 6-month projects.

You find the constraint, build the smallest thing that should move the metric, and see if it works.

- If it does, keep going.
- If it doesn't, you learned something in 2 weeks instead of 6 months.

That’s how you build AI projects in 2026.

A company of around 400 people spent 6 months collecting AI feedback from every department. The CEO looked at the report and said:

"Maybe next year."

The truth was that almost nobody wanted it.

I was speaking with one of their managers when I understood what had actually happened.

A few months before the research, the company had implemented AI in one of their departments. 

The entire team was let go. 
Then they did the same in another.

Every manager who witnessed that, and was then asked "should we use AI in your area?", gave the same answer: NO.

The reports they submitted were detailed: 

• AI is unreliable
• It makes mistakes
• It's too expensive

Every argument was technically defensible. 
None of it was the real reason.

They weren't lying, but protecting their teams.

That company delayed their AI rollout by 8 months because of research they commissioned themselves.

The problem with internal AI diagnostics: the people you ask have skin in the game. 
When their team's jobs are on the line, honest answers become impossible.

When we ran an external assessment, the resistance was fear, not opposition to AI. 

That one finding changed everything: not build a business case for AI, but address what employees had watched happen to their colleagues.

The honest assessment can only come from someone with nothing to lose by giving it.

PS: This is the first thing we establish before any Sprint begins.

My laptop broke during a trip abroad. No replacement, only my phone.
This forced me to do something I'd never done before:

I called my team leads and said: "Run it without me. Here's what I expect. Here's best practice. The rest is yours."

They did.

When I came back, I realized I didn't want to go back to those meetings.

I'd learned something I couldn't un-learn.

A few months later, a different problem appeared : 

1/ Certain decisions only moved when I was in the room

2/ Certain clients would only talk to me

3/ Certain processes had no written rule, just a habit that lived in my head

I wasn't running a business built on systems.

I was the system.

Answer a question instead of documenting it : you become the answer.

Make a call instead of writing a process : you become the process.

Disappear for two weeks, and the company shows you exactly what it can't do without you.

PS: One of first things we do in every workshop is ask founders to map every process that stops when they stop.

No words on Earth can describe my feelings... 87% filled project ...

#Claude come back 😅

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