Helping SMEs boost profits 10x faster with my AI & Automation-as-a-Service agency—turn your business processes into saved time, empowered teams, & increased profits, all without the extra overhead. Link in Bio ↓

There are two ways to be a business leader in 2025:

1. Struggle with inefficient processes. Stagnate.
2. Leverage AI Agents (aiGENTS). Scale 10x faster. 

Most are stuck in the first.

As a leader, you have ambitious goals. But they're out of reach, aren't they? 

The bigger problem?

You're missing out on game-changing opportunities. 

Opportunities to streamline operations, outpace competitors, and attract top talent to fuel your growth.

Yet, when it comes to:

↗ Automating repetitive tasks
↗ Breaking down departmental silos
↗ Achieving rapid, sustainable growth
↗ Reducing reliance on costly vendors

You find:

↗ Your workflows are still painfully manual
↗ Your teams are disconnected and inefficient
↗ Your operational costs are spiraling out of control

The solution? 

Transform your business with AI Agents and workflow optimization.

That's our expertise. 

Our services encompass:

↗ Crafting tailored AI strategies aligned with your business goals
↗ Implementing AI Agents for immediate impact
↗ Streamlining cross-departmental collaboration
↗ Providing ongoing optimization and support

Are you serious about revolutionizing how your business operates? 

Are you ready to scale 10x faster with AI Agents? 

Reach out now to start your journey towards operational excellence and exponential growth. 

→ GO HERE: www.hiteshmahajan.com 

Email: hello@aidapt.co
X: @hitesh_ai​

Hitesh Mahajan

most companies in MEA aren’t behind on AI because of budget.

they’re behind because they’re waiting for certainty that will never come.

the playbook is the same everywhere: “let’s wait until it’s proven, then we’ll move fast.”

but by the time it’s proven, the window is gone.

the businesses I see winning right now didn’t wait for a perfect business case.

they ran a small deployment, learned something real, and compounded from there.

3 months of cautious observation costs more than 3 weeks of messy experimentation.

the risk isn’t moving too fast. the risk is confusing “careful” with “safe.”

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.​​​​​​​​​​​​​​​​

Hitesh Mahajan 🚀

CEO @ Aidapt | I design your AI strategy and orchestrate the data foundations, platforms and intelligent systems you need, then build and run them for you in a single AI-first operating model with clear, measurable value

I stole this idea and now use it with every hire.

Best illustration of high agency I've ever seen.

There are 5 levels of work:

1.	"There is a problem."
2.	"There is a problem. Here are some causes."
3.	"Here's the problem. Here are possible solutions."
4.	"Here's the problem, the cause, the options, and the one I'd pick."
5.	"I found it. I fixed it. Just keeping you in the loop."

Here's what I tell every new hire on Day 1:

You start at Level 4. You earn Level 5. Anything below is a conversation we need to have.

High agency isn't just how you tackle problems. It's your entire orientation to work.

(AI is a multiplier for Level 4+ people. An expensive babysitter for everyone else.)

P.S. What level are you operating at right now?

A founder’s appetite for;

eating shit, 
embracing unsexy work, 
using their ears more than their mouth, 
cutting losses quickly, 
and maintaining a tight emotional range…

Will always be the algorithm for success.

AI changes the tools.

It doesn’t change this.

What I’ve learned after putting Snowflake at the center of 10+ enterprise data projects:

1.	The warehouse is never the problem. The data culture is.

2.	Clean data in Snowflake still means nothing if nobody trusts it.

3.	Most companies are paying for Snowflake and querying Excel sheets for board decks.

4.	The real ROI unlocks when AI agents can query your data warehouse without a human in the loop.

5.	Governance isn’t a Snowflake feature. It’s a people decision that has to happen before you touch the platform.

6.	The teams who move fastest treat Snowflake as infrastructure, not a project.

7.	If your data team and your business team are in separate meetings, you already have a problem.

The tool is the easy part.

The hard part is deciding what you actually want to know.

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.​​​​​​​​​​​​​​​​

If your answer to "how do you use AI?"
 is drafting emails, writing reports, and smarter googling...


You are at the tip of a profoundly large iceberg.


Work your way down by:

Questioning everything about how you've worked.

↳ Not some things. Everything.
Assuming AI can handle far more than you think.
↳ Give it credit before you take it away.
Giving the technology time and feedback to earn
your trust.
↳ No different than a new employee.

Most people quit at the surface.

The people building real leverage?

They're at the bottom of the iceberg.

P.S. What's the most surprising thing AI has done
for you that you didn't expect?

two years ago I genuinely didn’t know if the work we were doing would land.

AI transformation is a hard sell when most people think it’s still a tech department problem.

There were client conversations where I could see the skepticism in the room.

“Sounds good in theory. We’ll see.”

What changed wasn’t the technology.

It was the moment businesses stopped asking “should we do this” and started asking “why haven’t we done this yet.”

I think about the early clients who took the bet on us before it was obvious.

They’re not asking those questions anymore.

They’re the ones other businesses are benchmarking against.

The window isn’t closed. But it is narrowing.

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.​​​​​​​​​​​​​​​​

12-year-old Hitesh would not believe the rooms
I sit in now.

Not because of status.

Because of access.

Access to how the best operators actually think.
Access to decisions that never make the press.
Access to the real story behind every
"overnight success."

Most of what I know about business?

Not from books.
From sitting across the table and shutting up.

(Listening is a superpower.
Almost nobody practices it.)

The privilege of proximity is real.

Don't take it for granted when you get it.

P.S. Who's someone you've learned from recently
that you haven't thanked? 

Go do that today.

i’ve spoken to a dozen people this month with
deep anxiety about going AI-native.

They want to get there.

They’re expected to get there.

But they feel like it’s a full-time job to do
it on top of their already full-time job.

This is the invisible cost nobody is talking about.

Leaders setting AI adoption mandates without
clearing the runway are creating a quiet crisis.

People feel overwhelmed.

They avoid.
Then leadership wonders why nobody is using it.

The technology gap is real.

It’s the second problem.

The capacity gap is the first.

If you’re one of these people, you’re not behind.

You’re not broken.

You’re just being asked to do two jobs at once
and told it should feel like one.

(That’s not a you problem.That’s a systems problem.)

P.S. Are you feeling this right now?

Drop a comment. You’re not alone.

most companies aren't losing to AI.

they're losing to companies with 5 people and an AI stack.

a 200-person team moves slower than a 4-person team with the right tools.

that's not a technology problem.

that's a structure problem.

the businesses winning right now aren't the ones with the biggest budgets.

they're the ones who stopped hiring for tasks and started hiring for judgment.

AI handles the tasks.

humans handle the calls that matter.

if your org chart looks the same as it did in 2022, that's worth asking about.

not because AI will replace your team.

because your competitor already restructured theirs.

👋🏼 I'm Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.

MEA isn’t “emerging” in AI anymore.

It’s diverging.

Some businesses here are 18 months ahead of their global peers.

Most are 18 months behind and still calling it a “pilot phase.”

Which one are you?

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.​​​​​​​​​​​​​​​​

What I’ve learned after building operations on ClickUp for teams across MEA:

1.	ClickUp won’t fix a broken process. It will just make the chaos more visible.

2.	The first 30 days are always a fight. Teams resist structure until they feel the relief of it.

3.	Most companies use 20% of what ClickUp can do and wonder why it’s “not working.”

4.	The best ops setups treat ClickUp like a single source of truth, not a task list.

5.	AI in ClickUp is genuinely useful now. Writing SOPs, summarising threads, auto-assigning tasks. It’s not a gimmick.

6.	The teams who win with it are the ones where leadership actually uses it too.

7.	Tool adoption is a leadership problem dressed up as a software problem.

If your team isn’t using it, look up before you look sideways.

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.​​​​​​​​​​​​​​​​

What I’ve learned after fixing broken data stacks for enterprises across MEA:

Most companies don’t have a data problem.

They have a “data everywhere, insight nowhere” problem.

Snowflake solves the infrastructure side in weeks.

But the real unlock is what sits on top of it.

AI agents querying your warehouse in real time.

Dashboards your CFO actually trusts.

Decisions that don’t require a 3-day data pull.

We’ve done this across 10+ enterprise deployments in the region.

The pattern is always the same: the businesses who move fastest treat data as a product, not a project.

If your data stack is costing you more in maintenance than it’s returning in insight, that’s the conversation worth having.

Check out the video, something we recently built and deployed for a world renowned airline 😉

Book a free AI Data Cloud discovery call here:  https://zurl.co/JraVH 

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.

I’ve been asking $100M+ company execs one question:
“What is the #1 thing slowing your company’s
AI transformation?”

A non-exhaustive list of what they said:

	1.	Data quality and connectivity of systems
	2.	Lack of leadership buy-in
	3.	Data governance restrictions
	4.	Willingness of staff to adopt AI
	5.	Incurious culture
	6.	Tooling doesn’t have API access
	7.	Industry regulation and privacy
	8.	Unclear ownership across teams
	9.	Mixed AI literacy levels
	10.	No clear strategy — starting from scratch
	11.	Time to actually build solutions
	12.	Silos
	13.	Lack of training
	14.	Quality of output
	15.	Time

Notice what’s missing from that list?

Nobody said the technology wasn’t good enough.

What would your answer be?

we’ve entered the enlightenment era for high agency humans.

As the cost of intelligence craters…

The #1 difference between the haves and have-nots
in a post-AI society is simple.

The extent to which you make things happen.

Or let things happen.

That’s it.

That’s the whole game.

P.S. Which one are you?

Jack Dorsey recently fired 40% of Block’s 10,000 employees because of AI.

Largest % layoff of an S&P 500 company ever.

People freaked out.

Stock jumped 20%.

People freaked out more.

Here’s my hopefully balanced take:

1. Jack has consistently been ahead of his time.
What he’s doing is the canary in the coal mine
for so many other businesses.

2. We’re going to see various flavors of AI-related layoffs.

The “using AI as a scapegoat” flavor.
The “business is failing” flavor.
The “pairing 10x employees with AI” flavor.
Only the third one is legitimate.

3. This only works for certain companies right now.

Flat structure. Meritocratic reward system.

High agency employees.

Trying it anywhere else leads to the boomerang, lay people off, AI can’t replace the culture, output drops, you reverse course.
(cough IBM)

4. The stock jumping isn’t a signal that knowledge
work is dying.

It’s a signal that markets reward cost reduction.

Full stop.

5. Does this worry me?

Yes and no.

Will AI create structural impacts in digital work?

Yes.

Will it create new employment opportunities?

Also yes.

The calm before the storm is real.

I just don’t think this is the storm.

P.S. What’s your read on the Block news?

Until you spend 100+ hours with Claude Code,
Codex, Cursor, and Cowork…

Do not tell me “the technology isn’t there.”

The technology is basically there.

For 99% of knowledge work.

What isn’t there is the patience to learn it.

The willingness to rebuild workflows from scratch.

The leadership courage to tell your team that

the way you’ve worked for 10 years is changing.

That’s not a technology problem.

I’ve watched companies spend months evaluating
AI tools and zero hours actually using them.

Evaluation is procrastination with a budget.

Pick a tool.

Spend 100 hours.

Then form an opinion.

P.S. What tool have you put the most hours into?

Building AI is the easy part.

Driving real change is the hard part.

9 steps to make any process AI-native:

1. Identify the Problem
↳ Find the manual process worth automating.

2. Understand the Workflow
↳ Map how people actually work today.

3. Collect the Data
↳ Gather sample inputs, edge cases, documents.

4. Build the Prototype
↳ The AI. The model. The demo.

5. Test and Iterate
↳ Validate with real users and edge cases.

6. Integrate with Systems
↳ Connect to your existing tools and data.

7. Roll Out and Train
↳ Get it into your team’s hands at scale.

8. Drive Adoption
↳ Make sure people use it every day.

9. Measure and Capture Value
↳ Redirect freed time. Prove the ROI.

Steps 1 to 4?

Most companies can do those in weeks.

Steps 5 to 9?

That’s where 80% of AI projects die.

Building the AI took days.

Deploying it to 500 people is the real work.

P.S. Which step is your company stuck on?

Most companies don't have an AI problem.

They have a courage problem.

The technology is there. The ROI cases are there. The tools are basically free.

What's missing is a leader willing to redesign the org around what AI actually makes possible.

That's not a technology decision. That's a leadership one.

P.S. The companies that figure this out in 2026? Untouchable by 2027.

The gap between theoretical AI capability and actual usage isn’t a technology problem.

It’s a knowledge and process problem.

Most people play with a tool for 30 minutes, don’t get the output they expect, and decide the technology is dumb and broken.

The person is broken, not the technology.

The companies closing this gap fastest aren’t
the ones with the biggest AI budgets.

They’re the ones who built internal conditions for curiosity to compound.

Dedicated time to experiment. 

Psychological safety to fail.

One internal champion who makes it their mission.

If you don’t have that person yet, you need to find them.
Or grow them.

P.S. Who is the internal AI champion in your company right now?

Ryan Staley

I help Chief Revenue Officers & Sales Professionals Leverage AI to work 10 hours less weekly and 2x performance. Follow for cutting-edge cheat codes, prompts, and workflows🎙Scale Up Show Host🔥$0→$30M ARR in 5.5 yrs

Over the last decade, I’ve grown a division from 0-$30M ARR with 4 Sales People and have upskilled over 2,500 GTM executives on AI, Enterprise Sales and GTM Strategy  .

My mission is to inspire 1 million Go To Market Executives to work less and sell more through becoming Superhuman with Artificial Intelligence.

I help revenue leaders transform their teams by acquiring AI skills to escape the operational grind, and accelerate topline revenue.

I’m the founder of Whale Boss and The Scale Up Show.

My portfolio:

→ I’m the Founder of Whale Boss, an AI Sales & Marketing consulting and skill transformation company
→ I’m the Founder of the Scale Up Show, Top 1% Global Podcast
→ I teach Executives, Sales & Marketing teams to implement tools like ChatGPT, Copilot, Claude, etc.   
→ I provide Chief AI Officer Advisory services for human capital.  


My results:

→0-$30M without funding, marketing or SDRs with only 4 Sales people
→Identified and implemented over 500 AI use cases (internally and externally)
→Taught over 800 CROs proprietary selling strategy and tactical execution
→Consulted over 40 Technology companies on custom revenue growth strategies.  
→Voted as a TOP global AI thought leader, Gartner Ambassador & Sales Assembly thought leader. 


If you want to learn more on how to become Superhuman, you can join my newsletter.
⇒ https://superhumanrevenue.beehiiv.com/


If you want to explore AI skill transformation for your organization or Team, apply for an AI Consult.  
=> https://calendly.com/ryanstaleywss/introductory-call-with-ryan-staley-from-whale-boss


Youtube- https://www.youtube.com/channel/UCFGndSHN4KkE89kUP74U7Qg

Podcast-https://ryanstaley.io/podcast/

X-https://x.com/Ryan_Staley1

Podcast Host

I deconstruct how the top SAAS CEOs in the world grow their companies repeatedly and predictably.  

This show has featured Startup and Billion Dollar Founders, Best Selling Authors, and the World’s Top Sales and Marketing Experts like Terry Jones (Founder of Travelocity and Chairman of Kayak),  Andrew Gazdecki (Founder of Microacquire), Harpaul Sambhi (Founder of Magical with a previous exit to Linkedin) and many more.

Hot take: The most underrated AI tool right now isn't a model.

It's a browser extension.

Claude Chrome extension works really well and I expect this to continue to increase in value.

I know that sounds ridiculous.
Browser extensions have been slow, buggy, and frustrating. Most people have written them off.


But here's what happened when I stopped ignoring Claude's Chrome extension:


I built a complete inventory of every AI assistant and agent I've created across ALL platforms in 15 minutes.


This would have taken me 2 hours of manual copying, pasting, and formatting.


And here's why this matters more than you think:


If you've been building AI systems for the past year, you probably have agents scattered across 3 to 5 platforms with no central view of what exists.


That's not an AI strategy. That's digital hoarding.

The extension handled the tedious part. Pulled the data, organized it, formatted it cleanly.


Will these tools get better? Absolutely.


But RIGHT NOW, they already work for the unglamorous work that actually matters. Data transfer. Organization. Structuring information across platforms.


The flashy stuff gets the attention.
The operational stuff gets the results.


What hidden tool has surprised you lately?

Founder & CEO, Whale Boss | Demystifying AI Agents | Helping revenue leaders 2x team results through AI Led GTM | Trusted by $50M-$20B PE-backed and Publicly Traded Companies | AI ROI for your team in 60 days

I just watched a 2.5 hour interview that changed how I see the next 3 years. And what he said should make every business leader stop and pay attention.

Dario Amodei, CEO of Anthropic, on the Dwarkesh Podcast. 

Here's the part that hit me hardest:

There are TWO exponentials happening right now. Not one. 

The first is the capability curve. Models getting smarter at research speed. 

The second is economic diffusion. How fast businesses actually ADOPT and deploy AI. Both are fast. Neither is instant. And there's a GAP between them. 

That gap is where careers are being made or destroyed RIGHT NOW. Dario put a number on AGI. 1-3 years for most knowledge work. 90% confidence within a decade. 


He said software engineering gets fully automated FIRST because code is verifiable. It works or it doesn't. But every function is next. Sales. Marketing. Operations. Finance. Strategy. 

The question isn't whether AI will transform your organization. That's settled. 

The question is whether YOU close the gap between what's possible and what your teams are actually doing. 

Anthropic went from $0 to $9-10 BILLION in revenue in 3 years. 

10x growth per year. 
That's not hype. 
That's the market screaming that AI delivers real value. 

I've been implementing AI across leadership teams for 3 years now with 3,100+ executives. 

The pattern is clear. 

The leaders who move during the gap between capability and adoption don't just win. 

They make it nearly impossible for competitors to catch up. 

Whether you're a CEO setting direction, a VP running a division, or a Director leading a team of 15, the window is the same. 


NOTE: I pulled the key visuals and takeaways from the full 2.5 hours so you don't have to watch it all. Link in comments. Where do you think your organization sits on the adoption curve right now?

AGI Transition Strategy

What if the "ruthless" ElevenLabs quota model is actually the most HUMANE way to run a sales team?


Hear me out.


Right now, most sales orgs carry 50+ reps. Half of them miss quota. 

They grind through manual research, data entry, and admin work that has nothing to do with selling.


They burn out. They churn. They blame enablement. Leadership blames them.


Everyone loses.


ElevenLabs flipped the script. 

Micro-teams of 5-10. AI handles the grunt work. 
Reps focus on what they were actually hired to do.

The result? 80% quota attainment.


And if you hit your number? 
You get paid MORE because there are fewer people splitting the pie.


This is the part nobody talks about with AI transformation.


It's not about replacing people.
It's about FREEING the right people to do their best work and paying them what they're actually worth.


The old model punishes A-players by surrounding them with B and C-players who drag down performance, culture, and comp pools.


The new model? Only A-players. Only selling. Only winning.


NOTE: After working with 3,100+ executives on AI transformation, the biggest resistance isn't from reps. It's from leaders who built their identity around managing large teams.


Smaller team = less perceived power.


But the CROs who get over that ego hurdle?


They're the ones building the future.


Would you rather manage 50 reps at 40% attainment or 10 reps at 80%?

Controversial take: The CROs and CMOs who work the MOST hours are often the worst performers.

I know. That's uncomfortable.

But after 23 years in GTM and 3 years of working with 3000+ revenue leaders across Public Traded and PE-backed SaaS, I can't unsee the pattern.

The leaders grinding 80-hour weeks aren't outperforming anyone. They're too exhausted to realize their strategy stopped working 6 weeks ago.
I've been there myself.

I used to wear exhaustion like proof I was committed. 70-hour weeks. Always on. Always grinding. I thought that's what it took to build Whale Boss while delivering for clients.

Then I hit a wall where I couldn't see what was obvious. I was making slower decisions. Recycling old ideas. Running on fumes and calling it discipline.

The moment I started treating rest as a STRATEGIC INPUT instead of a reward, everything changed.

My content got sharper. My client sessions got better. I started seeing patterns in AI implementation I'd been too fried to notice.

Think about Tom Brady.

He didn't become the GOAT by outworking everyone in the weight room. He became the GOAT by obsessing over recovery, nutrition, rest, and how he treated his body. While other quarterbacks were breaking down at 35, Brady played 4-5 years LONGER and at a HIGHER level than his peers.

That wasn't luck. That was a strategic decision to optimize for longevity and peak performance instead of brute force.

Revenue leadership is the same game.

The executives I train who ruthlessly protect recovery time?


They see market shifts faster.
They make pricing decisions with conviction instead of desperation.
They retain their best people because burned-out leaders create burned-out teams.


One CRO told me something I'll never forget:
"I made more strategic progress in 10 days off than I did in the 6 months before. Because I finally had the space to THINK instead of just REACT."

Your brain isn't a machine that performs better with more runtime.
It's a system that performs better with RECOVERY CYCLES.

The same way PE firms don't expect compound returns without reinvestment, you can't expect compound performance without rest.

NOTE: The executives who survive and thrive across multiple PE cycles aren't superhuman. They're the Tom Brady's of leadership. They figured out that strategic rest isn't soft. It's the hardest competitive edge to copy.

What's your actual recovery strategy right now? Or are you still telling yourself you'll rest after this quarter?

Canary in the coal mine, here’s why this happened…


This is going to be common moving forward if you don’t take this seriously.

I repeat, if you don’t adapt and AI upskill, companies you work for will adapt for you.

If you don’t adapt your workforce to be AI unskilled you will be disrupted by companies like this that will put you out of business.



This is an exact quote from the CEO.

“we're not making this decision because we're in trouble. our business is strong. gross profit continues to grow, we continue to serve more and more customers, and profitability is improving. but something has changed. we're already seeing that the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. and that's accelerating rapidly.”

I took inventory of every AI agent and assistant I've built for my business.

Here's a some of what my "Agent/Assistant org chart" looks like:

Operating Systems:
• CEO OS (strategy, planning, reviews)
• Sales OS (pipeline, deal coaching, forecasting)
• Product OS (curriculum, delivery, design)

C-Suite Agents:
• Chief Counsel (legal review, contracts)
• CHRO (hiring, candidate scoring, team design)
• CMO (Content, Creative, Strategy, team design)

Sales:
• Deal Coach with Next Best Action
• Research assistant

Productivity:
• Email management
• Proposal design

Marketing:
• LinkedIn content teammate

Product:
• Program design
• Agent designer
• Customer artifact designer

That's 15 agents across 6 functions. Built in 3 months. No engineering team. No dev budget.

Here's what I've learned:

The mistake most people make with AI agents is building them one at a time, like isolated tools.

The unlock is designing them like an organization.

Just like a company has:
→ Leadership (Operating Systems)
→ Departments (Sales, Marketing, Product)
→ Communication layers (how agents share context)
→ Reporting structure (which agent leads which workflow)

When you architect assistants or agents as a system instead of individual tools, every new agent you add makes the whole thing more powerful.

Not additive. Multiplicative.

The question for every leader right now:

What does YOUR agent org chart look like?

If the answer is "we don't have one" — that's your biggest AI blind spot.

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