Liberate Labs

In my role as CEO at Liberate Labs, I lead a team of expert product engineers to use a Product-Led Growth (PLG) strategy at Liberate Labs, addressing the unique challenges and opportunities of startups. 

We prioritize metrics that reflect the real health and future trajectory of these businesses. Our approach aims to reduce Customer Acquisition Costs (CAC) and enhance engagement and retention.

By tracking natural growth rate, activated sign-ups, and the balance between new ARR and cash burned, we offer startups a clear, data-driven view of their product's market impact and reach.

Our commitment goes beyond just delivering software; we aim to produce quantifiable results for startups through top-tier product development and strategy.

Specialties: Strategic and Tactical Leadership, Stakeholder Management and Communications, Program Management, Customer UX Design, SCRUM, Agile, SDLC, DevOps, System Design, Data Analysis.

Chief Executive Officer

Superessence

Fractional Chief Technology and Product Officer

StudyBuds

Acreage

Bullseye for Schools

As the fractional Chief Technology and Product Officer at Bullseye Education Solutions, I'm a key contributor to the evolution of our instructional support system that's currently transforming teacher coaching and student outcomes in over 500 schools, engaging more than 2,000 daily active users.

Our collective endeavors have led to a significant upswing in student standardized test scores by up to 51%.

My role is highly collaborative, working across business, engineering, and design teams to rapidly iterate on our product development. My focus is on delivering a world-class user experience that is both intuitive and effective.

Currently, I'm steering the platform towards its next generation. This includes leveraging AI capabilities and reshaping the platform for a product-led growth strategy. These initiatives aim to solidify Bullseye's standing in the ed-tech industry.

Amazon

•	Coordinated rollout of 100+ software deliverables across 500 stores driving improvements in food safety and compliance across multiple departments, teams, and business functions

•	Managed 5+ cross-functional teams to improve recipe data consistency across multiple data catalogs by 30%

•	Spearheaded green-field Traceability program to enable WFM supply chain tracking to achieve newly formed U.S. FSMA 204 compliance standards: justified headcount, defined program charter, and established high-level technical vision

•	Lead deprecation of legacy systems costing 10M+/year and hundreds of labor hours in inefficiencies across 5 WFM domains and 10+ engineering and business teams

Senior Technical Program Manager

•	Investigated and coordinated optimization exercise to reduce scan orchestration duration by 48%

•	Automated vulnerability remediation to reduce time-to-remediate critical OS vulnerabilities by 42% 

•	Managed platform stabilization project which reduced database load by 70%

•	Launching service redesign planned to increase automated vulnerability remediation throughput by 350%

•	Launching tool to extend vulnerability scan coverage for 20 subsidiaries containing >100K hosts

•	Launching Amazon-wide platform to standardize and increase accuracy of remediation priority across the company

•	Conducted architecture reviews into technical systems, proposed solutions, and managed/launched optimizations 

•	Managed stakeholder communications via monthly reporting, quarterly reports, and weekly syncs up to VP of InfoSec

•	Streamlined feature delivery pipeline to meetings by 66% while increasing burndown of tasks by ~30%

Technical Program Manager II

•	Collaborated to implement internal Amazon vulnerability ticketing script to notify 12K+ teams of critical vulnerabilities

•	Implemented feature to auto-assign appropriate ticket severity for emergent third-party vulnerabilities

•	Root-caused platform issues and proposed solutions to address throttling, database deadlocks, and platform instability

Software Engineer II

•	Designed and implemented feature to auto-classify 300k+ customer accounts improving automated process accuracy by 3%

•	Conducted customer research to implement work distribution tool enhancement reducing manual work by 455 hours/month

•	Expanded service alarms and metrics collection to improve diagnosis, resolution, and prioritization of service issues

•	Mentored and coached multiple interns to successfully receive return offers and new hires through knowledge transfers

•	Led strategic initiatives to improve team code quality standards, testing, and culture through documentation and event planning

Software Engineer

Georgia-Pacific LLC

•	Created new help page using JavaScript, HTML, and CSS for GP Packing Order Account Management Website

•	Worked closely with customers and product owners to plan and deliver solution to reduce frequency of support tickets from corrugated plants

Software Development Engineer

•	Planned and implemented 12-week project to improve the efficiency of internal Amazon business process

•	Creating API for Remote Procedure Call framework to pull data from relational database 

•	Utilizing React and worked with internal users to create front-end component to be utilized by internal agents

Graph House LLC.

•	Founded creative agency to deliver affordable marketing solutions to startups in the Atlanta area

•	Negotiated multiple partnerships between Georgia Tech Academic departments and organizations, and assisted with the acquisition of clients

•	Acquired and coordinated all business communications with all clients to deliver quality and efficient services

Co-Founder, CEO

Acuity Brands

•	Writing scripts in SQL to update Acuity Brands product information within the Product Data Management portal

•	Developing webpage using Kendo UI framework to update and view Acuity Brands product log

Product Management

Fractional CTO for B2B SaaS | 2× Feature Velocity in 90 Days—Guaranteed | Ex-Amazon | CEO, Liberate Labs

Most SaaS founders hit a wall between $1M-$5M ARR. 
Growth stalls. Churn climbs. The next funding round feels impossible.

I've been there. As a former Amazon engineer, 
I've seen what separates companies that scale from those that struggle.

Here's what I've learned: 
It's not about hiring more people. 
It's about building better systems.

Today, I serve as Fractional CTO for 12+ SaaS companies and run Liberate Labs, 
where we've helped founders achieve:

→ 25-50% revenue growth in 6 months
→ 30% churn reduction through funnel optimization
→ $2M+ in unlocked expansion revenue
→ 3x revenue growth in 24 months (Series A client)

My approach is different: 
I don't just give advice, I build and implement the systems myself. 

1. Customer Journey Funnels. 
2. Product roadmaps. 
3. Engineering execution. 
4. Marketing automation. 

All designed to turn your growth plateau into predictable, scalable revenue.

What makes this work:
✓ Engineering-led methodology (not marketing fluff)
✓ Focus on measurable outcomes, not vanity metrics
✓ 60-day implementation sprints (no endless consulting)
✓ Money-back guarantee if you don't see results

I've packaged everything that works into proven systems. If you're a B2B SaaS founder ready to break through your growth ceiling without burning cash on expensive hires, let's talk.

Dm me on LinkedIn (I stay super active) or email me at: jihad@liberate-labs.com

I’ve watched dozens of founders build AI features that no one uses. Here’s what they’re missing:

It’s not about the model.
It’s about the moment.

Most teams obsess over AI capabilities.

But forget to nail the trigger point that makes users actually need the feature.

One client spent months on an AI content generator that could do everything.

But usage was abysmal.

Turns out, users didn’t need more content.
They were drowning in revision requests.

So we pivoted.

- The AI now kicked in exactly when a revision request arrived.
- Usage jumped 400% in two weeks.

The difference wasn’t smarter AI.
It was smarter product thinking.

If you’re building AI features, stop asking:

“What cool AI thing can we build?”

Start asking:
1. What specific pain occurs regularly in our product?
2. When does the user feel it most acutely?
3. How can AI remove that friction in that exact moment?

The best AI features aren’t the most impressive ones.

They’re the ones that show up at the perfect time with the perfect solution.

Your users don’t care about your AI. They care about getting unstuck and moving forward.

If you’re a SaaS founder building AI into your product, what moment are you targeting? Drop in comments.

Jihad Iqbal

I Build and Grow B2B SaaS | Technology and Product Advisor for 20+ B2B SaaS Startups | Ex-Amazon

Skimmed the Y Combinator S25 batch list this morning. Over 160 startups. 60% are heavily focused on AI. That’s what grabbed me.

But let’s be honest:

We’re still early.

Not “buy now or miss the boat” early.
More like “everything’s still breaking” early.

I’ve spent the last 2 years shipping real AI products.
Across K-12, real estate, and SaaS.

Here’s what I’ve learned:

There’s a wide gap between hype and utility.

The best founders? They don’t lead with AI.

They lead with:

✅ A real problem
✅ Proprietary data
✅ A wedge into existing workflows

And then they ask:

“How does AI make this 10x better?”

What they don’t do?

❌ Build demos for problems that don’t exist
❌ Depend on APIs they don’t control
❌ Launch features before they earn distribution

The YC AI startups that survive?

They’ll be the ones that hit the trifecta:

- Painkiller problem
- Sustainable GTM
- AI that’s the multiplier, not the story

The rest?

Just very expensive prototypes.

I've been tracking a chilling data point that's keeping me up at night:

LLM capabilities are doubling every 7 months.

Not years. Months.

This isn't about theory anymore. It's about survival.

A workflow that takes your customer 8 hours today will soon be handled entirely by an AI agent. Then 40-hour workflows. Then 80-hour projects.

I'm seeing two types of SaaS founders right now:

Those who see this as "AI optimization" - adding features around the edges to stay competitive.

And those who understand they're in a race to completely reinvent their value proposition before AI makes their current one obsolete.

The harsh reality? If your product solves a problem that can be reduced to information processing, decision workflows, or pattern matching, the clock is ticking.

The winners won't be those with the best AI features.

The winners will be founders who fundamentally reimagine their entire product category through the lens of exponential intelligence.

Don't add AI. Rebuild around it.

This isn't incremental change. It's exponential disruption that's coming for every workflow your customers pay you to solve.

I Build and Grow B2B SaaS | Fractional CTO/CPO for B2B SaaS | Ex-Amazon

Eight founders called me in a panic last week. None asked about AWS. All asked: What do I tell my users?

Not surprising.

When outages hit, 
it’s not your cloud infrastructure that breaks first.

It’s trust.

After building cloud systems for 15 years, 
here’s what I’ve learned the hard way:

3 patterns separate companies that keep trust from those that lose it fast:

1. Transparency > Vagueness

“Investigating” kills trust.
“AWS is down. We're affected. Here's our plan.” builds it.

2. Proactive > Reactive

Founders who messaged before complaints kept users.
The ones who hid behind support queues didn’t.

3. Clarity > Complexit

“S3 bucket latency” means nothing to users.
“File uploads are delayed” does.

Resilience isn’t just architectural.
It’s communicative.

Your customers don’t expect perfection.
They expect honesty and a plan.

Build your outage playbook now.

Because when the system goes down…
…the right words bring it back up.

I Build and Grow B2B SaaS | Technology and Product Advisor for 47+ B2B SaaS Startups | Ex-Amazon

After 50+ founder conversations this quarter, one pattern’s clear: Most “AI products” aren’t really AI products.

Top layer:
Everyone slapping AI on landing pages and pitch decks.

Middle layer:
Startups adding a prompt box and calling it an “AI product.”

Bottom layer:
A handful of founders rebuilding their core workflows to be AI-native.

And that’s where the real opportunity lives.

Because the best AI products don’t look like AI products.
They just work better.

Here’s what top-performing SaaS founders are doing differently:

They’re not asking “Where do we add AI?”
They’re asking “What steps can we eliminate altogether?”

They’re not adding flashy AI overlays.
They’re embedding AI under the hood to make UX seamless.

They’re not building “chatbots.”
They’re rearchitecting entire flows to cut time-to-value by 80%+.

Last week, we helped a SaaS client replace a bloated onboarding flow with a natural language intake powered by our own custom RAG + LLM layer.

→ Time-to-value dropped from 35 mins to just 6.
→ Activation rate spiked 27% in a week.

This is what most people miss:

The biggest ROI isn’t in adding an AI toggle.
It’s in rethinking your entire product architecture from first principles.

Your competitors are still trying to bolt AI onto their existing UX.
We help you build something they can’t just copy.

If you’re ready to stop chasing AI trends and start engineering defensible advantages, that’s where we Liberate Labs come in.

Let's talk.

Founders spent $200K on growth tactics
Their broken mindset made every dollar worthless
 
Want to see the real burn rate in SaaS?
 
It’s not salaries.
It’s not ad spend.
It’s misalignment.
 
When the founder’s mindset is:
❌ Tactical > Strategic
❌ Fast growth > Smart growth
❌ Do more > Do better
 
That’s when money disappears and nothing compounds.
 
Here’s the fix:
• Strategic segmentation
• Clear GTM and messaging
• Growth feedback loops that actually loop
 
If your ARR is stuck, this might be why.

Last night I talked to a founder who had burned through $72,000 on a development team that built exactly what he asked for.

The problem? It wasn't what his customers needed.

This happens all the time.

Founders ship features that sound smart in a pitch deck, 
but solve nothing for real users.

Here’s what actually works:

1. Talk to your best customers weekly. 

Don’t ask what they want. 
Ask what’s not working then map your roadmap to outcomes.

2. Audit conversion, not backlog.

If it doesn’t move revenue, retention, or expansion... 
it’s just future tech debt.

3. Shrink scope until it hurts.

The “minimum” in MVP should sting.
If you're proud of what you shipped, you waited too long.

4. Add one, kill one. 

Every new feature should replace one -
that doesn’t pull its weight in your funnel.

5. Never ship on 6-week sprints.

In SaaS, assumptions age like milk. 
If you’re not shipping bi-weekly, you’re flying blind.

I’ve seen founders 3x their MRR in 90 days,
not by building more, but by building with precision.

The best products don’t do everything.
They do one thing so well, customers can’t imagine life without them.

If your team is building but not growing, we should talk.

At Liberate Labs, we help SaaS companies achieve $300k ARR with a done-for-you growth system that aligns product, marketing, and analytics and delivers results in 90 days. 

Drop a comment or DM me.

3 years ago, I helped launch a SaaS product that flopped. Hard. We had a solid dev team. A roadmap. A “big vision.” What we didn’t have? 

Proof anyone wanted it.
We spent 5 months building, branding, and refining the UX.

On launch day, we got 6 users.
4 of them churned within 10 days.

That punch in the gut taught me something I’ve never forgotten:

“Great tech doesn’t guarantee growth. Great validation does.”

This is the rule we follow and help every founder apply
Before you build, validate one of these 3 signals:

1. People are actively searching for a solution
2. They’re hacking together clunky workarounds
3. They’re paying someone else to solve it poorly

If you don’t see one of these, 
You’re not looking at product-market fit.

You’re looking at founder fantasy.

We at Liberate Labs builds Customer Journey Funnels -
that only start after signal confirmation.

→ We’ve cut engineering cycles by 60%
→ Helped clients unlock $2M+ in expansion revenue
→ Reduced churn by 30% in under 6 months

Why? 

Because we validate before we build.

If you’re a founder sitting on an “idea that feels right,” pause.

Find the signal. Then go full throttle.

I spent 2 weeks helping a founder "fix their data warehouse"...only to realize they didn’t need one at all. If you're a SaaS founder < $5M ARR, read this: 

I see it constantly:

Founders building enterprise-grade data stacks…
…before they’ve nailed product-market fit.

❌ DBT models
❌ Snowflake
❌ Full-time data engineer

All built to track metrics no one looks at.

Here’s what your board (and your growth) actually needs:

✅ Clear attribution for revenue drivers
✅ Simple dashboards to show user behavior
✅ Answers to basic questions in hours, not days

That’s it.

What you need instead:

1. Basic instrumentation (Segment, PostHog, Rudderstack)
2. Lightweight product analytics (Mixpanel, Amplitude)
3. Scrappy SQL + Sheets for reporting

One founder I worked with spent $200K,
building a data system they barely touched.

Another scaled to $4M ARR using nothing but GA, Sheets, and Mixpanel.

The difference?

Founder #2 knew what signals actually mattered.

Here’s the rule:

Data maturity should FOLLOW revenue maturity , not precede it.

Build what you need today. 
Not what Stripe uses.

$280K burned on features that didn’t move revenue.
Here’s the filter that would’ve saved it.

In 12 months, 
I led shipping 47 product features across 8 B2B SaaS teams.

Only 11 actually moved the needle.

The rest? Vanity.

What changed?

I stopped listening to feature requests.
And started listening for buying signals.

Here’s the framework that turned busywork into profit:

Before we ship any feature, I ask 4 brutal questions:

1. Will it get users to upgrade or expand usage?
2. Will it reduce churn in the next 60 days?
3. Will it trigger referrals or stronger engagement?
4. Can we tie it to revenue within 30 days?

If the answer isn’t hell yes to at least two, we kill it.

Hard truth: Most founders build what users say they want.
But users don’t pay for “wants.”
They pay to solve pain.

One client wanted an advanced analytics dashboard.
We shipped a simple usage alert system instead.

Churn dropped 23% in 6 weeks.
Dashboard? Still on the backlog.

Lesson: Your roadmap isn’t a wishlist.
It’s your revenue strategy.

Don’t build for applause.
Build for ARR.

Every demo ends with "let me get back to you"
Nobody ever gets back to you

Here’s why your product feels invisible:

You’re stuck in the tar pit -
That deceptive middle zone where you try to serve everyone…
…and end up resonating with no one.

It feels safe.
The market looks wide.
Competitors aren’t crowding it.

So you think: “Let’s sit here.”

But the fact is,
Decision-makers don’t buy average.

They buy urgency.
They buy differentiation.
They buy what solves their #1 problem faster than anything else.

You want traction?

- Pick an edge.
- Go deep.
- Say something no one else is willing to say.

The tar pit is where startups go to quietly die.
Don’t build there.

Everyone builds onboarding. We build reboarding. Here’s the SaaS blind spot almost no founder talks about:

- It’s not failed signups.
- It’s users who already paid you… and disappeared.

We analyzed 47 SaaS products over 18 months. 

The pattern was brutal:

• 60% of users went dormant within 90 days
• Only 12% came back on their own
• 73% re-engaged with the right trigger

Most teams obsess over acquisition.
Meanwhile, silent churn is bleeding ARR.

That’s backwards.

The best reactivation playbooks don’t ask:
“Why did you leave?”

They ask:
“What changed since you signed up?”

Because context changes.
Teams evolve.
Priorities shift.

The problem you solved 6 months ago?
Might be their #1 pain again, right now.

Example:
One client had 2,400 dormant accounts.

We built a simple reactivation sequence.
- 340 accounts reactivated.
- $180K ARR recovered.
- Zero new acquisition spend.

That’s not a campaign.
That’s a revenue unlock.

Your warmest leads already paid you.
Stop chasing cold traffic while money slips out the back door.

Want help reactivating dormant users? DM me.

The fastest way to sabotage your SaaS?
Build for the narrative instead of the metrics.
 
I've seen founders:
– Hire too fast because “scaling” sounds sexy
– Raise money they don’t need to avoid the “bootstrapped” label
– Ship features customers never asked for to chase trends
 
Then the narrative shifts... and they’re stuck with burn, bloat, and regret.
 
I’ve watched profitable companies take VC money just to feel included,
only to spend 2 years chasing growth targets that erode their margins.
 
All for the story.
 
If you're a founder:
→ Build your own scoreboard
→ Measure what actually matters
→ Ignore the noise
 
Because long-term winners?
 
They’re not chasing the narrative.
They’re writing their own.

Most founders think retention is about fixing churn.
They're wrong.
 
I've analyzed product data for 40+ SaaS startups over the past 3 years. The pattern is always the same: companies obsessing over exit surveys and churn emails while their best customers quietly slip away.
 
Here's what actually drives retention:
 
Your power users aren't using your core feature more. They're using adjacent features that create stickiness. 

The CRM that wins isn't the one with the best contact management rather it's the one whose users can't live without the reporting dashboard.
 
Your onboarding teaches features, not outcomes. Users don't care about your 47 integrations. They care about the specific result they hired your product to deliver. Show them that result in week one, or lose them in week two.
 
Your product roadmap is built backward. You're adding features existing users request instead of features that would make leaving impossible. There's a difference between satisfaction and dependency.
 
The companies with 95%+ net retention don't have better customer success teams. They have better product loops. Every action a user takes makes the product more valuable for them personally.
 
Stop measuring engagement. Start measuring entrenchment. The best retention strategy is making your product essential to how they work.

Some founders move 10x faster than others
Same market, same resources, different mindset
 
Most people think it's all about:
→ Funding
→ Hiring
→ GTM velocity
 
But the biggest unlock?
The mindset of repeat SaaS founders.
 
These are folks who get funded before they finish pitch decks.
Why? Because they've internalized a replicable approach to growth.
 
They don’t guess.
They don’t chase vanity metrics.
They don’t build aimlessly.
 
They build with precision -
around what's proven to work:
 
→ Focused experiments
→ Fast iteration
→ Ruthless prioritization
→ Obsession with activation & retention
 
Want to grow faster?
 
Stop looking at tools.
Start modeling mindsets.

Most SaaS founders I talk to have their data strategy completely backwards. They obsess over the wrong things...

Perfect dashboards, 
Complex stacks, and pixel-perfect visualizations.

But after working with dozens of B2B startups to ship revenue-driving features fast, here’s what actually works:

Instrument first. 
Analyze later.

The playbook we now use at Liberate Labs:

From day one, build event tracking into your product.

Not dashboards. 
Not analytics tooling. 
Just track the right events.

1. User clicked X
2. User completed Y
3. User abandoned Z

That’s raw behavioral data,
the gold you'll mine later.

Most founders wait until they “need analytics.”
By then, they’ve already lost months of untracked user behavior.

And when they finally ask:

- What features actually drive retention?
- Where do users drop off in the funnel?
- What actions predict expansion vs. churn?

There’s no data to answer those questions.

Big mistake. Easy fix.

The cheapest time to add event tracking is while building the feature.

That’s why we mandate it across every SaaS product we build.

No exceptions. No excuses.

You don’t need a fancy stack. You need:

1. A clear event schema
2. A reliable tracking library
3. A consistent naming convention

That’s it.

Build dashboards later.
But start capturing now, 
so future-you has something to work with.

Because the best insights don’t come from Day 1 data.

They come six months later…
When you're finally asking the right questions.

80% of product roadmaps are built backwards, 
Because teams start with features instead of... 

....the problem users are willing to pay to solve .

I see this mistake everywhere.

Here's what most roadmaps look like:

- Build AI feature
- Add mobile app
- Integrate with Slack
- Ship collaboration tools

But users don't buy features.
They buy solutions to painful problems.
The kind that cost them time, money, or sanity every single day.

So here's what I do instead:

Before adding ANY feature to our roadmap,
I ask 5 questions:

1. What problem does this solve?
2. How much does this problem cost the user RIGHT NOW?
3. What are they currently using to solve it?
4. Why would they rip that out for us?
5. What behavior has to change?

If I can't answer all 5?
We don't build it.

Because here's the thing:
Your users already have a solution.

Maybe it's a spreadsheet.
Maybe it's a competitor.
Maybe it's doing nothing.

Your feature needs to be 10x better than what they're doing now.

Not 10% better.
Not "nice to have."

10x better.

The best roadmaps don't start with features.
They start with expensive problems.
Then work backward.

What's the most expensive problem you're solving?

We spent 7 weeks revamping a product. Never touched a line of code. Trial signups jumped 34%. Here’s what worked:

I’ve been working with a B2B SaaS founder,
who wanted to “revamp the entire product.”

But we didn’t ship a single new feature.

Instead, we fixed his pricing page:

- Cut 5 plans down to 3
- Removed 60% of feature clutter
- Rewrote copy to match how customers actually speak
- Added outcome-driven social proof

The result?

34% more trial signups,
Zero product changes.

Here’s the hard truth:

Your product doesn’t need more features.
It needs a clearer promise.

Most founders build in response to objections.
They add features to “overcome” friction.

But the smartest founders?
They simplify.

They create clarity.
And clarity converts better than complexity, every single time.

So before you rebuild your product…
Try rewriting your promise.

When a buyer lands on your pricing page, 
they should instantly know:

• Who it’s for (and who it’s not)
• The problem it solves
• The outcome they’ll get
• Why it’s worth the price

Your pricing page is more than a list of features.
It’s your strategy, exposed.

Next time you’re thinking of a product revamp, start here instead.
You might be surprised what clarity alone can unlock.

Most founders think they need more features to grow. They don't.
They need better distribution loops....
 
I've watched 50+ SaaS teams build incredible products that nobody discovers. Beautiful interfaces. Powerful functionality. Zero organic growth.
 
The pattern is always the same: They optimize for product perfection while ignoring how users actually find and share software.
 
Here's what actually drives SaaS growth:
 
Your product becomes the distribution channel. Every user action should create value for someone else. Every workflow should have a built-in reason to invite teammates, share results, or publish insights.
 
We rebuilt a client's reporting feature to automatically generate shareable insights. Users started posting their metrics on LinkedIn. 

Organic signups jumped 340% in 6 weeks.
 
Another client added collaborative workspaces to their solo tool. 
Teams started inviting colleagues to review projects. 

Viral coefficient went from 0.1 to 0.8.
 
The best SaaS products don't just solve problems, they create natural moments where users become distributors.
 
Your next feature shouldn't just add value. It should spread value.
 
Stop building in isolation. Start building for virality.

I’ve spent the last 6 weeks working with 4 different AI startups. Every single one made the same mistake:

They built AI features, not AI products.

Let me explain:

An AI feature is a bolt-on that demos well but doesn’t shift user behavior.

An AI product redefines how users get their job done — 
faster, easier, and with less friction.

Here’s a real example:

One client had 11 shiny AI capabilities:

→ Sentiment analysis
→ Summarization
→ Entity extraction

(All technically impressive. None actually used.)

Why?

Because they didn’t remove friction.
They just layered on complexity.

So we scrapped the noise.

We rebuilt the product around the 3 highest-friction tasks -
where users spent 80% of their time on.

The result?

Usage jumped 340% in 3 weeks.
Customer NPS spiked.
Expansion revenue unlocked.

So, the lesson here is:

AI isn’t valuable because it’s cutting-edge.
It’s valuable when it makes painful work vanish.

Stop building for the demo.
Start building for the workflow.

That’s how you win in AI SaaS.

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