VP Sales | 🚀 Propelling SaaS Companies to New Growth | Lifelong Sales Mentor and Teacher

Education is locked in outdated models while technology races ahead. So I bridge the gap and build the frameworks that define the future of learning.

I’ve spent my career moving between classrooms, boardrooms, and uncomfortable conversations about what actually works in education.

I started as a teacher.
Then, I moved into EdTech sales—helping founders, school leaders, and teams scale products, revenue, and strategy in one of the hardest markets there is.

Along the way, I noticed a pattern most of us avoid naming:

Education doesn’t fail because of a lack of tools.
It fails when motivation disappears—and we keep building systems that ignore that.

We’ve tried dashboards.
We’ve tried content engines.
We’ve tried accountability without agency.

And we keep acting surprised when students disengage.

My work now sits at the intersection of:
•	Learning science & motivation
•	AI-enabled mastery-based learning
•	Go-to-market strategy for education companies
•	Helping schools raise standards without burning people out

I’m especially interested in models where:
• students love school
• learning is deep, fast, and human
• technology gives time back instead of taking it
• and schools can actually sustain themselves

I advise founders, operators, and education leaders who want outcomes—not applause.

I’m the author of The Great Unlock—a practical, contrarian look at how AI can break education’s three biggest constraints and make learning more human, not less.

No hype.
No grownsplaining.
High standards. High support.

If you believe students are capable of more—and that education should finally be built around that belief—we’ll get along just fine.

Karim Kuperhause

GenAI is to education what Ozempic is to obesity: it works, and that's exactly what should worry us.

The OECD just released data showing students with AI access outperform peers on assignments — then score 17% worse on exams when that access is removed. We celebrated the gains. We buried the footnote.

Here's the contrarian read nobody wants: maybe the problem isn't that students are using GenAI wrong. Maybe it's that it's working exactly as designed — and we built the wrong thing.

Ozempic suppresses appetite. It doesn't teach your body to want less. The moment you stop, the hunger returns, often harder than before. GenAI suppresses cognitive friction. It doesn't build the tolerance for difficulty that turns struggle into mastery. The moment you remove it, the gap is worse than if it had never been there.

The pharma industry's answer to Ozempic dependency is: stay on it forever. I suspect EdTech's answer to GenAI dependency will be the same. And for shareholders, that's a great outcome.

But education isn't a chronic condition to be managed. It's a capacity to be built.

The OECD report calls for "pedagogical intentionality." That's the right instinct — but it soft-pedals the harder truth: most GenAI tools aren't designed for learning. They're designed for output. And in a system that still measures output, we'll keep rewarding the illusion of mastery over the real thing.

The students who will thrive in 20 years aren't the ones who learned to prompt well. They're the ones who learned to think — with or without the tool.

We should be building more of those students, not better crutches.

_________________

I curate the future of learning | Helping EdTech founders and Education Leaders co-design the future of learning

Open article: OECD Digital Education Outlook 2026 by oecd.org

EdTech keeps missing the mark because it forgot what sparks intrinsic motivation.

We built dashboards.
We launched content engines.
We celebrated “AI-powered” pathways and personalized workflows.
But the single force we keep skipping is the drive inside the learner-the thing that makes a student push past comfort, take risks, and come back for more.

The thing is --> Features don’t move students. Frameworks do.

Most EdTech still runs on two tired assumptions:
→ If we deliver information faster, learning improves.
→ If teachers and admins track usage, students engage.

Reality is more blunt:
• Motivation isn’t an add-on. It’s the hidden engine.
• AI can automate feedback and personalize next steps-but unless students feel competent, respected, and in control, all you get is short-term compliance.

As a founder and educator, I’ve seen this play out everywhere-from districts with 40+ tools but no learning theory, to “student-centered” systems that optimize for optics not outputs.

GenAI can suppress cognitive struggle (like Ozempic for effort) but it won’t build the grit that mastery requires. If we remove productive friction, we create dependency instead of resilience.

The future of learning must restore agency:
• AI as a thinking partner, not a shortcut.
• Dashboards that raise standards, not just flag attendance.
• Environments where students feel trusted, challenged, and safe enough to risk failure.

Stop designing for speed and convenience.
Start designing for the spark that makes kids choose effort.

If you’re building for the next wave-make sure your AI moves motivation, not just metrics.

Building something? Want something better for students? Let’s connect @hierlearning

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The Great Unlock

Get a preview of my upcoming book at https://thegreatunlock.com/

AI SHOW @ ASU+GSV 2025 Attendee

HierSales is about providing a hierarchy in your sales process. Putting systems in place to consistently grow revenue. We put in place scalable and repeatable sales processes to drive revenue growth for companies in the $1-5M stage.

Most companies are still running outdated GTM playbooks.

Big budgets go into ads, MQLs, and funnels that don’t actually build trust or drive outcomes.

That’s where HierSales comes in.

I help founders and revenue leaders invent their own growth playbook instead of borrowing someone else’s. My methodology is simple but powerful:

Identify → Amplify → Multiply

•	Identify the sparks already driving traction — peer influence, referrals, customer wins.

•	Amplify them through customer champions and authentic founder-led storytelling.

•	Multiply by turning those sparks into repeatable, scalable growth motions (councils, referral loops, influence dinners).

With HierSales, I work hands-on with early-stage and scaling companies to:

•	Run growth ethnography that uncovers where influence really flows.

•	Design influence programs that turn customers into your best sellers.

•	Build 12-week experiment roadmaps to test, validate, and double down on what actually works.

•	Codify it all into a playbook that accelerates growth sustainably.

I don’t just consult from the sidelines. I’ve built, scaled, and sold in the trenches — from teaching in classrooms to leading enterprise sales to scaling EdTech ventures. That practitioner’s lens means I can spot the hidden levers most consultants miss.

If your growth engine feels stuck, or if you’re tired of burning budget on campaigns that don’t convert, let’s talk. Together, we’ll write the playbook that finally unlocks your next stage of growth.

Founder/Fractional VP Sales

“Transform the education of tomorrow, today.”

Provide strategic direction for the Trafalgar-McGill CoLab: https://www.trafalgar.qc.ca/community/colab

Board Member

"I wish you to gasp not only at what you read but at the miracle of its being readable.' - Vladimir Nabokov

The education system is in crisis. Too many students are reaching grade 4 not able to proficiently read at level. This can't go on - children deserve to read and Hoot Reading is on a mission to help every child become a reader.

VP of Growth

“Systems streamline success; they eliminate the need to reinvent the wheel every time.” - J.R. Rim

commonsku is a SaaS platform that enables promotional products distributors to automate and streamline their processes in order to grow and scale their business, including their e-com.

Built entire sales team and sales processes from scratch and went on to Increase client base from 600 to 800 companies propelling transactional revenue from $1B to nearly $2B in 18 months.

VP of Sales

“An organization‘a ability to learn, and translate that learning into action rapidly, is the ultimate competitive advantage.” - Jack Welsh

Clevr helps school districts consolidate and centralize manual forms and workflows into one clevr platform.

Developed and executed go-to-market strategy for landing and expanding into the US K-12 market. Landed in 7 US states and expanded market share which resulted in 45% year-over-year growth as well as landing the biggest client in company's history.

Director of Sales

“Efficiency is doing things right; effectiveness is doing the right things.” - Peter Drucker

Driving efficiency and transformation while reducing the cost of compliance for public sector organizations by providing the Laserfiche Enterprise Content Management platform.

Introduced Laserfiche's digital transformation suite of solutions in new verticals including K12, NGOs and banks. Continued expansion into municipals, hotels and retail. Together, these resulted in a double of revenue year-over-year.

Director, Business Development

“People buy from people they trust”

Help school districts increase student growth by better managing K12 talent through focused talent management software.

Landed and expanded new SaaS solutions into the Canadian K12 market while building out a dedicated sales team and process for Canada.

Account Executive - People Admin

“Systems thinking allows us to see the consequences of our decisions before we make them.”  - Peter Senge

Harnessing the power of research to inform data-driven hiring and increase student achievement. Hit President's Club year-over year as well as becoming the recipient of the Pinnacle Award for highest sales achievement and the Rainmaker award for closing the biggest deals in company history.

Sales Manager - TeacherMatch

“Putting the right people in the right seats is the first step to creating an effective system.” - Jim Collins

Strategically work with school districts from coast to coast to help minimize lost learning days by addressing teacher absenteeism and professional development through the SmartFindExpress software platform. Hit President's Club on my first year and subsequent years thereafter. Landed biggest deal in company history for Canada, locked up the Ontario market and landed and expanded into the Quebec market.

Regional Sales Manager (Canada) - eSchool Solutions

“Building a business is about creating a system that can run and grow without you.” - Robert Kiyosaki

Founder and CEO of the Learning Box which was dedicated to ensuring school success for students in K-12.  Providing individualized instruction based on skill based learning for all core subjects. Went to oversee programs in over 32 schools, 3 learning centres and service thousands of students.

Founder/CEO

“Great leaders understand the importance of developing systems that outlive them.” - John C. Maxwell

As an elementary school teacher for 12 years in this school board, I worked with students from K-6.  I was a lead teacher for school reform and a trained SmartBoard Instructor as well as First Steps Instructor.  My students consistently scored in the top percentile across the entire school board in both math and English language arts.

It's also where I learned many of the skills that made me an exeptional sales professional because teaching and sales are two sides of the same coin.

Elementary Teacher

From ABC to ARR | K12 Education Top Voice | Outcomes. Or. Nothing.

I curate the future of learning | Helping Education Leaders and EdTech Founders co-design the future of learning

Education doesn’t have a teacher problem.
It has a time problem.

For 100 years, we’ve confused time spent with learning achieved.

Seat time. Grade levels. Pacing guides. Coverage calendars.

All built for an industrial economy where:

Memorization = value

Uniformity = efficiency

Falling behind = personal failure

That model didn’t just age poorly.
AI exposed it overnight.

When students “fail,” what they’re really failing is a system that:

Moves on before mastery

Punishes gaps instead of filling them

Optimizes for administration, not outcomes

If your solution still worships time-based learning,
it’s not innovation — it’s nostalgia with better branding.

I analyzed 100 school districts' EdTech strategies.

Most didn't have one.

Not a roadmap. Not a framework. Not a measurable goal tied to student outcomes.

What I found instead were purchasing decisions dressed up as strategy.

Here's what that looks like in practice:

🔻 Pattern #1: Tools without a theory of learning
Districts have an average of 40+ EdTech tools in their stack.
But no one can answer: "How do these tools work together to move a student from where they are to where they need to be?"
📌 One district had 7 different reading platforms across K–8.
Teachers used whichever one they liked.
Result: No coherent progression. No measurable gains. Just subscriptions renewing on autopilot.

🔻 Pattern #2: Procurement masquerading as strategy
The buying process is the strategy.
Compliance boxes get checked. Pilots get approved. Contracts get signed.
But no one asks: "What does success actually look like for students in June?"
📌 82% of the districts I reviewed had no defined outcome metric attached to their EdTech spend.
Result: Millions allocated. Accountability to no one.

🔻 Pattern #3: AI arrived before the question did
Every vendor now has an "AI-powered" something.
And superintendents are being asked to adopt it—by boards, by parents, by state policy.
But the districts rushing to deploy AI don't yet have a clear answer to a more basic question:
"What learning problem are we solving?"
📌 AI without a learning framework isn't innovation. It's noise with a better interface.
Result: Teachers overwhelmed. Admins confused. Students unchanged.

🔻 Pattern #4: Data everywhere. Insight nowhere.
Dashboards. Reports. Benchmark scores. Attendance flags.
Districts are drowning in data and starving for direction.
Without a hierarchy of what matters—and why—data doesn't drive decisions. It justifies them after the fact.
📌 One district had real-time intervention alerts that no one had time to act on.
Result: The system flagged 400 at-risk students. 12 received follow-up.

🔻 Pattern #5: No one owns outcomes
EdTech vendors own the product. Teachers own the classroom. Admins own compliance.
But who owns the answer to: "Are students actually learning more this year than last?"
In most districts, no one does.
Result: Shared responsibility becomes shared avoidance.

Here's what that tells me:
The districts winning on student outcomes aren't the ones with the most tools or the biggest budgets.
They're the ones who started with a clear learning framework—and built everything else around it.

An EdTech strategy without a theory of learning is just spending.

An AI strategy without a theory of learning is just risk.

If you're a school district leader who's done settling for motion instead of progress, there's a different conversation happening at HierLearning

Come find out what a real learning strategy looks like. If it resonates, book a call. We'd love to think through this with you.

HierLearning

"Human Literacy" is the new ROI in the age of AI.
The data is clear, and the "skills gap" is about to become a chasm. 📉

I’ve been diving deep into recent analysis by John Burn-Murdoch and David Deming, and the trend lines are startling. Since 1980, the labor market has shifted aggressively toward roles that require high social skills and high math skills.

As technical tasks become easier to automate with AI, "human" skills—empathy, collaboration, and social intelligence—are the only true differentiators left for high-value work.

But here is the "The Great Unlock" paradox:
While the economy is demanding more human connection and focus, our cognitive foundations are under attack.

Recent data from the Understanding America Study shows a "conscientiousness cliff" among younger generations (ages 16-39):

--> Planning and follow-through? Cratering.

--> Perseverance until finished? On a steady decline.

--> Easily distracted? Skyrocketing.

We are facing a crisis of "supply." K-12 education is still largely optimized for a world of rote memorization and siloed subjects, yet the world our students are entering demands the one thing we aren't teaching explicitly: The ability to focus and connect.

If we don't address this cognitive and social "tax" now, we aren't just failing to prepare students for the AI era—we’re leaving them without the tools to navigate it.

Education leaders: We need to move beyond "AI literacy" and start talking about human literacy.

____________

🚀 Calling all EdTech Founders:
If you are building a solution specifically designed to bolster social-emotional skills, focus, or "human" cognitive traits in K-12, I want to hear from you. We need to bridge this gap before it’s too late.

Drop a comment or DM me. Let's talk about how we can unlock this next generation.

_____________

We finally got the reading curriculum right.

Science of reading. Structured literacy. Phonics-based instruction.

After decades of whole language, we course-corrected.

Now we're finding out it's still not enough.

Neuralign has identified the problem the structured literacy movement hasn't solved yet.

Some children can't access structured literacy... because their brains aren't ready to receive it.

If a child's auditory processing, visual processing, or vestibular system isn't functioning efficiently, phonics instruction falls on deaf ears. Literally.

Reading isn't just about decoding symbols on a page.
It requires the auditory, visual, and vestibular systems working in perfect coordination... at split-second timing.

When those systems are misaligned, no amount of structured literacy moves the needle.
This is the missing piece.

Neuralign's research shows that when you train those three systems simultaneously — before or alongside structured literacy — students improve reading by an average of 50% in 10 weeks. 99% improve by 2+ grade levels after 40 hours.

Those aren't tutoring numbers. Those are transformation numbers.

Here's what every school leader, EdTech founder, and parent needs to hear:
The science of reading got the what right.

Neuralign is answering the why — why some kids still struggle even when the instruction is correct.

The answer isn't better phonics.

It's a brain that's ready to receive it.

Children are limitless.

The only question is whether we're giving them the right conditions to prove it.

______________

Open article: The Most Accessible, High-Tech Reading Intervention. by neuralign.org

The Most Accessible, High-Tech Reading Intervention.

The social media era is ending.

K-12 EdTech is about to make the exact same mistake.

Here's what no EdTech vendor will say out loud:

AI will not make your current EdTech tools better.
It will make them obsolete.

Not because the tools are bad. Because they were built for a different era.
The LMS. The adaptive content platform. The "AI-powered" dashboard your district just renewed.

All of it was designed around internet-era logic:
📦 Broadcast content at scale.
✅ Track completion.
📊 Optimize engagement.
That logic is collapsing.

Here's the risk that will blindside education:

It's not that AI will replace teachers.
It's that full AI personalization — every student on their own algorithmically curated learning path — will quietly destroy the one thing school was always supposed to protect - a shared curriculum.

Social media didn't intend to destroy collective sense-making.
It was the emergent consequence of optimizing for engagement without ever asking: toward what?

EdTech is at the same inflection point. Right now.

🔻 The vendors pitching "fully personalized AI learning journeys" cannot answer one question:
Toward what shared outcome?

If they can't answer that, you don't have a learning strategy.
You have a very expensive feed.

The districts that survive this transition won't be the ones that adopted AI fastest.

They'll be the ones that asked the right questions first:
📌 Which of our tools depend on a student habit loop — and what happens when that loop breaks?
📌 What shared outcomes does our personalization infrastructure route toward?
📌 Are we measuring learning, or are we measuring activity?
📌 Can any vendor show us pre/post data from a district like ours?

This is what HierLearning has been building toward.
Not a platform. Not another AI tool.
A framework for the transition that's already happening.

We just published a white paper laying out the full argument — the structural forces, the specific risks, and what a superintendent-led response actually looks like.

If you're responsible for students — not shareholders — this one's for you.

____________

https://lnkd.in/eBzXeaJQ

We were sold a myth.

Public education was supposed to be the great equalizer. The idea was simple: give every kid the same classroom, the same teacher, the same curriculum — and you level the playing field.

It never worked.

The reality is that educational quality has always tracked wealth. Private tutors, SAT prep, enrichment programs, elite networks — they've always been available to those who could afford them. Everyone else got a 30-kid classroom and a teacher stretched too thin to give any one student the attention they actually need.

AI is about to change that.

I recently came across an article showing how any parent — not a developer, not a tech person — can build a personalized AI tutor for their child in an afternoon. One that knows your kid's learning style. That has infinite patience. That can explain the same concept 10 different ways until it clicks. That's available at 10pm when homework hits and mom and dad are exhausted.

For most of human history, that kind of 1-on-1 intellectual attention was reserved for the wealthy. Aristotle tutored Alexander the Great. The rest of us got lectured at.

That era is ending.

This isn't about replacing teachers. It's about giving every child something that only rich kids have ever had: a dedicated, personalized guide through their own education.

Public education promised democratization and delivered standardization. AI might actually deliver on the original promise.

The question isn't whether this technology exists. It does. The question is whether we'll be intentional about getting it into the hands of the kids who need it most.

________________

deepeducationnetwork.com

How I Built My Kid's AI Homework Tutor | DEEP Education Network

I write about AI in education from a people-first perspective.

The real challenge isn’t the technology.

It’s leading change without losing:

- "teacher trust"
- "professional identity"
- "time with students"

My focus here is on how AI can support teachers, give students more human time, and help leaders move forward without becoming “pro-tech over people.”

If you’re navigating that tension, you’re in the right place.

Teacher dignity should be a success metric for AI.

If adoption increases output but decreases trust, something is wrong.

Progress in education has always been fragile.

It depends on relationships, belief, and professional pride.

AI doesn’t change that.

It just makes leadership responsibility more visible.

Education isn’t broken.
It’s locked.

Locked by a factory model built for synchronization, batch processing, and averages.

Locked by the myth that learning is linear.
(Anyone who’s ever watched a student struggle... then suddenly click... knows better.)

Locked by time—same pace, same path, same calendar for everyone.

AI changes that. Completely.

Not by automating worksheets.
Not by grading faster.

But by unlocking three things education never could at scale before:

🔓 Personalization — an infinite tutor that adapts in real time
🔓 Motivation — learning anchored to interests, not compliance
🔓 Time — mastery on your timeline, not the bell schedule

When those locks fall, everything downstream changes:

• The factory model dies
• Curriculum becomes a knowledge graph
• GPA fades, skills portfolios emerge
• Teachers shift from lecturers → architects
• Students become founders of their own learning
• Mornings = mastery, afternoons = real-world studios
• Learning follows a J-curve, not a straight line

This isn’t theory.
It’s already happening.

I’ve been putting this framework together in my upcoming book, The Great Unlock — a practical, no-BS look at how AI is forcing education to evolve (and why that’s actually great news for students).

📘 Want a preview?
Comment “UNLOCK” or DM me and I’ll share an early look.

The next version of education won’t be a better factory.

It’ll be a studio.

_____________________

No alternative text description for this image

We pretend all parents want the same thing from school.
They don’t.

And that gap matters more than we like to admit.

Not all parents care about academics.

That’s not a judgment.
It’s a reality we keep papering over.

Some parents want:

--> straight A’s
--> elite universities
--> academic acceleration

Others want:

--> a happy child
--> low stress
--> fewer nightly homework battles

And many—quietly—prioritize:

--> reliable childcare
--> social belonging
--> harmony at home

So when debates about “rigor” erupt, we’re often not disagreeing on methods.
We’re disagreeing on purpose.

For some families, high standards signal opportunity.
For others, they signal pressure, anxiety, and burnout.

Schools sit in the crossfire, trying to honor every definition of success at once.
The result?

--> diluted rigor
--> unclear expectations
--> exhausted teachers
--> parents on opposite sides feeling ignored

The issue isn’t that parents disagree.

It’s that we pretend they don’t.

Until we’re willing to ask—and answer—one foundational question, nothing else really changes:

What is school for?

Until that’s clear, arguments about grades, homework, AI, or rigor are just symptoms.

And kids are the ones absorbing the confusion.

If this made you pause, that’s the point.

Students aren’t unmotivated.
They’re rational.

Imagine being told:

You’re behind

You’ll never catch up

And the class is moving on anyway

Of course motivation dies.

The real heroes aren’t “high performers.”
They’re the students and educators who haven’t given up yet — despite the system.

The ones who still believe:

Gaps can be filled

Mastery can be achieved

Confidence is built, not bestowed

Most education products talk about these people.
Very few are built for them.

For years, we’ve misunderstood what’s actually happening when neurodivergent students struggle to read.

We’ve treated it like a motivation problem.
Or a practice problem.
Or worse—a character flaw.

The result?
Shame. Fear. Avoidance. Kids who “don’t like reading” and quietly opt out.

That’s not a coincidence. It’s a system outcome.

The truth this visual makes painfully clear:
Most reading interventions are built around coping, not correction.

Traditional tutoring helps students work around a processing issue.
It rarely fixes the issue itself.
So the cognitive tax stays high.
Decoding drains energy.
Comprehension never really kicks in.

That’s the real bottleneck.

The root cause isn’t effort.
It’s an auditory–visual disconnect—the brain can’t synchronize sounds and symbols fast enough. Every word becomes work. Every sentence a slog.

Neuralign flips the model.

Instead of piling on more reading time, it trains the brain itself.

By targeting auditory and visual processing simultaneously—through multisensory, gamified experiences—it leverages neuroplasticity to reduce the energy drain at the source.

This isn’t “teaching kids to read better.”
It’s preparing the brain so reading stops feeling like pain.

And when that happens, something powerful shows up downstream:

Confidence.
Belonging.
Re-engagement.

Not because we lowered the bar.
But because we finally removed the invisible weight holding students back.

The shift education needs right now isn’t more support.
It’s better science.

It’s time to move from coping to correcting. 

__________________________

The most successful adults approach teenagers the same way great investors approach founders: they back the ones already moving.

Not because they’re cold.
Not because they don’t care.

Because they understand leverage.

Ambitious, self-driven teens:
• ask sharper questions
• act quickly on feedback
• turn guidance into momentum
• don’t need to be dragged—just aimed

When a driven 16-year-old meets a serious adult who actually shows up, something powerful happens:
→ confidence compounds
→ standards rise
→ effort accelerates

This is how future builders are made.

Not through endless motivation talks.
But through proximity to adults who expect a lot—and give a lot.

Here’s the thing:

We’ve built systems that spend most of their energy on disengagement...
...and almost none on acceleration.

Imagine if we flipped that.

If we treated ambitious teens the way elite athletes are treated:
• coaching instead of babysitting
• stretch goals instead of sympathy
• real-world exposure instead of busywork

The ROI would be absurd.

The future doesn’t need more engagement frameworks.
It needs more adults willing to say:

“You’re capable of more. Let’s move.”

That’s not pressure.
That’s respect.

And ambitious teens feel the difference immediately.

If you’re a leader, founder, or educator:
Who are you actively investing in right now?

Most school systems say they’re “student-centered.”

The Department of Defense Education Activity (DoDEA) actually builds around student outcomes.

And the difference shows.

DoDEA schools consistently outperform U.S. averages on NAEP.
Not because they spend wildly more.
Not because they cherry-pick students.
But because the system is designed around a very clear idea:

👉 Learning is the product. Everything else is support.

A few things DoDEA gets right (that most systems quietly avoid):

• Outcomes are explicit. Mastery matters more than seat time.
• Curriculum is coherent. Fewer random initiatives, more alignment.
• Accountability is real. Results aren’t “contextualized away.”
• Mobility is assumed. When families move, learning doesn’t reset.
• Execution beats ideology. Less debate, more delivery.

Here’s the uncomfortable comparison:

Most districts optimize for inputs
– staffing ratios
– programs
– compliance
– optics

DoDEA optimizes for outputs
– what students actually know
– what they can do
– how consistently they grow

Same kids.
Same humans.
Very different system incentives.

This isn’t about military culture (well, maybe a little).
It’s about clarity.

When a system agrees on:
• what success looks like
• how it’s measured
• who owns it

Students win.

The real question isn’t:
“Could this work elsewhere?”

It’s:
“Why aren’t we even trying?”

If we’re serious about student outcomes, the playbook already exists.
We’re just pretending it doesn’t.

--------------

educationdaly.us

The Best American School System

HierLearning isn’t here to disrupt schools.
We’re here to unlock them.

We don’t position ourselves as the hero.

We’re the guide that helps:
- Students rebuild confidence through mastery
- Educators shift from coverage to outcomes
- Founders design tools that prove impact
- Systems move from time-based to growth-based

Our bias is simple:
- Measure what matters
- Skip the hype cycle
- Build for human potential in an AI world

We don’t sell hope.

We help build systems where hope becomes measurable.

Every parent wants their kid to be educated the way they were.

The logic is simple:
“I turned out fine.”
So my kid will too.

But... is fine really the goal?

Fine means:
• average outcomes
• unrealized potential
• learning that works for school, not for life

And “fine” made sense when:
• information was scarce
• careers were linear
• conformity was rewarded

That world no longer exists.

Kids today aren’t limited by access to knowledge.
They’re limited by expectations.

Every child is more capable than our systems assume.
More curious.
More adaptable.
More ambitious.

School shouldn’t recreate our past.
It should be designed to unlock their future.

Not to produce kids who are “fine.”
But kids who:
• master fundamentals
• move at the pace of understanding
• build confidence through real competence
• discover what’s possible when standards are high and support is real

Children are not fragile.
They’re limitless.

The real problem isn’t that school fails kids.
It’s that we’ve normalized aiming too low.

“Fine” is survival.
Education should be about thriving.

If we truly believe in our kids, we have to stop asking:
“Did this work for me?”

And start asking:
“Is this worthy of them?”

When most people watch Eileen Gu land a double cork, they see talent.

District leaders should see policy.

In that clip, she isn’t talking about being “gifted.”
She’s talking about expectation.

She trains her mind to believe the trick is possible before her body ever lands it.

That’s not confidence.
That’s a system reinforcing high standards.

Here's the parallel for K-12:

Students rarely rise above the expectations embedded in the system around them.

Not the mission statement.
The actual system.

How we group students.

How quickly we intervene.

How often we communicate growth.

How much productive struggle we tolerate before we lower the bar.

When a student internalizes:
“I’m not good at math.”
“I’m Tier 2.”
“I’m not a reader.”

That label becomes a ceiling.

And once ceilings are operationalized, they’re hard to undo.

The truth district leaders already know:

Children are far more elastic than our structures.

Neuroplasticity does not expire in Grade 3.
Motivation doesn't disappear in middle school.
Potential is not capped by last year’s assessment data.

But expectation signals matter.

If your district systems:

--> Make mastery visible and attainable
--> Pair high standards with high support
--> Use intervention as acceleration, not containment
--> Treat early struggle as temporary, not predictive

You are institutionalizing belief.

If your systems:

- Track early and rigidly
- Emphasize deficits over growth
- Define students by status labels
- Lower expectations in the name of equity

You may be scaling limitation.

The districts that will outperform over the next decade won’t be the ones with the most tools.

They’ll be the ones whose systems assume capability.

The question isn’t whether children are limitless.

The question is whether your operating model reflects that belief.

And whether your EdTech vendors, data systems, and instructional design reinforce ceilings — or expand them.

__________

https://lnkd.in/eRA8xQKj

Benjamin Bloom proved it in 1984.

One-on-one tutoring produces results two standard deviations better than traditional classroom instruction.

He called it the 2-sigma problem.

The challenge: how do you deliver that level of personalized learning to every child... at scale?
For 40 years, nobody had a real answer.
Now we do.

A Fortune article published this month highlights what's already happening. Efekta Education deployed an AI teaching assistant to 4 million students in Brazil. The result: a 32.5% improvement in English test scores across 750,000 students on a state standardized assessment.

Let that number land.

Not a pilot. Not a lab study. 750,000 students. 32.5%.

The article's thesis: AI can transform education through personalized learning — but only if governments, tech firms, and educators work together.

That last part matters. And it's exactly where most EdTech gets it wrong.
You cannot build in isolation and drop a product into a school system and expect transformation. Co-design is the unlock. Teachers are not obstacles. They're the bridge between what AI can do and what students actually need.

This is the work HierLearning is doing.

We're not building AI to replace teachers. We're building AI to give every child what only the wealthiest families have always been able to buy: a personalized, bespoke learning experience that adapts to them.

Bloom's 2-sigma. At scale. In the existing system.

For too long, the quality of a child's education has been determined by the accident of birth — the neighborhood they live in, the school they attend, the resources their family can access.

AI is the great equalizer.

Not because technology fixes everything.

But because, for the first time, the tools exist to move the needle on student outcomes for every child... not just some of them.

If you're a school district leader that wants to co-design the future of learning, DM me.

It's time we built systems that prove it.

_________________

Open article: AI could spark a new age of learning, but only if governments, tech firms and educators work together | Fortune by fortune.com

Jose Manuel Barroso, former president of the European Commission.

AI could spark a new age of learning, but only if governments, tech firms and educators work together | Fortune

Find me on https://lovable.dev/@lazarjovanovic and learn Lovable on https://february.lovable.app/

Lazar Jovanovic

Professional Vibe Coder at Lovable | L5: Diamond Certified

Next stop - Lovabletown! ❤️ 

Dream it -> Ship it

Am I still crazy for saying no one will need to code 6 months from now? 
Am I still crazy for saying that PMs and designers do not need to learn how to code to build production grade software? 

Am I crazy? Or am I just trying to shake you from your roots? Make you do something about it? 

Not freak out by any means - but by all means take action and start doing something. 

It's entirely your choice and within your reach, please please please listen to Lenny Rachitsky and Boris Cherny dive deeper into this topic. 

Don't listen to me. Watch me as an example it is possible, and do something! 

https://lnkd.in/eK5jAdwq

Open video: Head of Claude Code: What happens after coding is solved | Boris Cherny on youtube.com

Head of Claude Code: What happens after coding is solved | Boris Cherny

Trying to come up with a good caption for this one.

This lesson is probably going to be very polarizing so I need your opinions on this in the comments. 

My POV:

The real leverage isn't in building more apps. 
It's in building fewer apps that can become many.

I used to think every project had to be unique. 
A new idea, a new market, a new everything. 
That is backwards.

Most beginners build apps. 
Builders build templates.

I don't mean a generic boilerplate. 

I mean a repeatable solution to a repeatable problem. 
Because most people in the same niche need the same things.

Take fitness creators. 
They all need workout delivery, progress tracking, and community features. When you build it, the pitch isn't "I have an idea for an app." 
The pitch is "I already built this. It just needs to look like you."

Or look at podcasters. 
They have audience and trust, but they lack products. 
You build a companion app once with searchable content and AI summaries. You use the same structure and simply swap the identity for the next creator.

The math changes everything:

Build one solid template in two weeks. 
Customize it for a client in two days. 
At $2,000 per branded app, five clients is $10,000 from that same initial week of work.

To find your own template, look for these four things:
1. A niche where people share the same needs.
2. A stable structure where only branding and content change.
3. A market where people are already spending money.
4. A clear way to reach that audience.

Your best work isn't just for one client. 
It is proof that you can deliver something premium, and that proof can be replicated.

Find a repeatable need, build once, and customize many times.

Catch Day 26 and the full lesson at https://lnkd.in/eWZShRpu and tell me if you agree about this being the easiest way to start monetizing your Lovable builds?

I think most people are still using AI at the surface level.

They use it to generate something faster. 
A document. 
Some code. 
A summary.
A deck. 

And that’s fine. 
It already feels magical.

But the real shift for me wasn’t speed. It was structure. I stopped thinking of AI as a tool that produces output and started treating it like a thinking partner.

Now I use it to pressure-test ideas before they become expensive.
1. To argue with me.
2. To ask me the uncomfortable questions.
3. To simulate edge cases I wouldn’t have thought about on my own.

The biggest unlock isn’t “write code for me.”
It’s shortening the feedback loop between idea and clarity.
That’s the part that changes how you work.

Vibe coding is just problem-solving under new constraints.

People hear the term and think shortcuts or laziness. 
In reality, it is the natural next step in the history of software development.

In Day 27 of 28 Days of Lovable, Marija Milosevic Lovable Ambassador and a former software engineer with 10 years of experience writing Java joins us to reframe how we look at AI-powered building.

If you zoom out, the pattern is logical:
- We moved from binary to functions.
- We moved from machine commands to readable languages like Python.
- We moved from manual coding to visual low-code builders.
- Now, we describe functionality in natural language and let the system generate the structure.

Every time we build on top of a new layer, we give up a bit of control in exchange for leverage. 

That has always been the deal. 
But faster execution does not mean less thinking. 
If anything, it means your thinking matters more. 

Thinking, judgment, and taste are what keep you calibrated when the tools move fast.

Over the last 27 days, the goal hasn't been to master a tool, but to master a loop:
1. Identify a problem.
2. Understand the constraints.
3. Design a system to solve it.
4. Execute as cheaply as possible.
5. Review honestly.
6. Decide deliberately.

When you look at an app like Uber, it feels like magic. 
But when you break it down into driver location, your location, distance, and a recalculation loop, it stops being mysterious. 

It becomes a system. 
And once you see the system, it is buildable.

Good builders don't wait for perfect tools. 
They see limitations early and design around them. 
That is what transfers. 
That skill doesn't expire when the tools change.

Catch Day 27 and the full lesson at https://lnkd.in/eWZShRpu

Community spotlight time! 

I asked -> you shared -> now it's my turn :) 

I cannot be more grateful for all of you that kept sending me Lovable app links for the past week. 

I hate singling anything out - but these are the 3 that popped for me. 

Keep sending stuff that you build and I'll do my best to feature you. 

https://meucv.online/ by Diego Ruzzinenti - simple (love that) application, the reason why I really loved it is because he took advantage of everything that AI development can offer. Check out the animation of how the app works on the page. That is a game changer. You no longer need to record videos of your demos or get people onto the waitlist. Just show them. 

https://lnkd.in/e8disuhJ by Erik Willemse - very cool for getting a bit of perspective in life, in case you ever asked yourself the question I've been asking myself a pretty decent chunk of my time on earth, which is, "Would my life be any different if I was born elsewhere?" 

https://lnkd.in/ezm3xJ88 Michael Tippett - Most people come to me, and when I ask them why they haven't used Lovable, they tell me they don't know what to build. I think this is one of the best apps to solve for the "cold start problem" that I've seen recently. 

Keep shipping, keep sharing, and I'll keep giving you the spotlight. 

Happy Friday!

Tomorrow, to end the lesson portion of 28 Days of Lovable - I have another surprise guest to announce! 

She's a Lovable Ambassador, a wearer of all hats one could put on their head and the best person I could think of explaining what I believe vibe coding is really about - problem/constraint solving! 

Stay tuned for an amazing 15 minute session from Marija Milosevic! I was on the edge of my seat for this one, and am convinced you'll be as well 🙂 

(and you'll hear a few amazing few quotes too)

Everyone talks about how AI makes you faster.
That’s true.
But something else happened that I didn’t expect.

It made me more exposed.

When you can ship in days instead of months, there’s nowhere to hide.

If the idea is weak, it shows immediately.
If your taste is average, it shows immediately.
If you don’t understand the user, it shows immediately.

Before, you could blame timelines.
Or dependencies.
Or engineering bandwidth.
Now the bottleneck is you.

AI removes friction.
And friction used to hide mediocrity.

That part is uncomfortable.
But it’s also the opportunity.
Just depends on where you stand. 

We're all producing faster. The question is what - magic, or garbage.

Most projects don't die because the idea is bad. 
They die because the structure collapses.

On Day 22 of 28 Days of Lovable, we are discussing the uncomfortable truth: sometimes a project isn't worth fixing. 

When fixes start breaking other fixes, you are no longer progressing. 
You are fighting entropy. 
And entropy always wins.

Starting over is not quitting. 
It is optimizing for leverage.

If you find yourself re-explaining the entire system to the AI just to make one change, you are past the point of efficient repair. 

The professional move is to extract what worked, identify what caused the breakdown, and move the good components into a fresh build.

You do not owe a project completion.
You owe yourself systems that can evolve.

Watch the full lesson on structural failure and how to restart intentionally in this video

For a long time, building something felt like training for a marathon.

You would prepare for weeks.
Write specs.
Align stakeholders.
Wait for engineering bandwidth.

By the time something shipped, so much time had passed that it almost felt detached from the original idea.
Now it feels more like going to the gym.
You have an idea in the morning.
By the evening, there’s a working prototype.
And that changes something fundamental.

When building is slow, you can hide inside planning.
You can say, “We’re still refining the strategy.”
You can live in Notion and feel productive.

When building is fast, that shield disappears.
If the idea is weak, you find out quickly.
If users don’t care, you know within days.
If the execution is sloppy, it’s visible immediately.

AI didn’t just make me faster.
It removed the space where I used to overthink instead of finish.

And finishing and shipping something real, however imperfect - is becoming the actual edge.
Not intelligence.
 Not credentials.
Just the discipline to turn thoughts into things.

Don't watch this video at all! 

Day 21 is about building, and this post is for my own consistency purposes - your only purpose for the day should be to create! 

And then visit https://lnkd.in/esnAfSXh to submit what you created as I plan to share it tomorrow. Stop reading! Go ship!

Finally on Android!! 

Shane Spencer let's get to 1M faaaast 😎 Bobby Siegfried can't be the only one!

I was literally thinking this morning - if we're all solving for software, how will the hardware keep up? 

Perhaps this is the answer!?

This result is just mind-numbing. When you can generate 1M toks/min (which corresponds to say 3-4k pages of a book, or a pretty large codebase) - what new AI applications become possible? :)

Ljubisa Bajic a fellow Serbian and former co-founder of Tenstorrent, is building a new AI ASIC at Talaas.

When we spoke last February, he told me this was exactly the direction he was heading in - and now a year later, he’s shipped it.

The ultimate chip specialization: burn the weights of the transformer directly into the chip. Why even deal with software (at least at that level of the abstraction)?

When you're providing the intelligence infrastracture at planetary scale (and given how much the LLM architecture has converged)  this can be a very viable economic model. You tape out a chip that can support 3-6 months of inference - and then you ditch it after that.

Keep in mind that these numbers are for an 8B heavily quantized model (so the quality is somewhat lower) - but then again this is just an "MVP". :) We'll soon be able to do this at a much larger scale.

Check out their blog post here: https://lnkd.in/gEXdXBKs

You can apply to try it out.

Most challenges reward outcomes. This one rewards process.

Today is Day 28 of 28 Days of Lovable, and we are closing the program by opening the 7 Day Buildathon.

Starting now, you have one full week to build and ship a project using Lovable. 

But I am not looking for the prettiest UI or the biggest scope. 
I am looking for clarity of thinking and constraint awareness.

I am judging five specific pillars of execution:

1. Deliberate Starting Point
Show why you chose your entry point. 
Did it come from a real problem, a remix, or a template? 
Day 1 through Day 5 were all about this.

2. Intentional Documentation
You must demonstrate context preservation. 
I want to see your Forward docs (what you planned) and your Backward docs (what you actually built and the decisions you made along the way).

3. Agent-Oriented Execution
Show how you designed for execution, not just prompting. 
This means structured task breakdowns and phased builds with verification steps.

4. Systems Over Memory
Demonstrate how you avoided relying on one-off prompts. 
Show the system you used to keep the project aligned as it grew in complexity.

5. Reflection
This is critical for builder maturity. 
What broke? What limitation did you hit? How did you work around it? 

A month ago, you might have hesitated to start or feared breaking things. 
If you have done the work, you are not that person anymore. 
You have practiced the loop: identify a problem, design a system, execute cheaply, review honestly, and decide deliberately.

That loop is yours now. 
It does not depend on any single tool. 
The thinking transfers.

Submissions close next Friday. Winners will be announced next Saturday.

Catch Day 28 and get the full Buildathon briefing at february.lovable.app

P.S. I am proud of you. And proud of myself for showing up every morning in February. It's now the best month of the year for me ❤️

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