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?

Aram Mughalyan

Helping web3 B2B businesses turn LinkedIn into a lead-gen and growth engine | Building personal brands for crypto leaders | Startup & GTM Advisor | Pioneering ‘Crypto LinkedIn’ | Shirtless Ultramarathoner

Are you a web3 B2B company trying to scale beyond the crypto-native bubble of X (Twitter)?That’s the problem I solve. Most web3 companies build early traction on X. It works well with crypto-native audiences. But when it’s time to scale beyond the crypto-native bubble of X and sell to institutions, TradFi, enterprises, other B2B buyers, or decision-makers outside crypto, growth stalls. Those buyers don’t live on X. They’re on LinkedIn. And they respond to clear positioning, credibility, and business-first messaging. I help web3 Founders, leaders, and B2B teams grow their revenue by 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐥𝐞𝐚𝐝𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧. Depending on where you’re at on LinkedIn, my work typically falls into 3 areas. → 1. 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 𝐏𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐢𝐧𝐠 &amp; 𝐏𝐫𝐨𝐟𝐢𝐥𝐞 𝐑𝐞𝐛𝐮𝐢𝐥𝐝 I start by auditing and rebuilding your LinkedIn profile to fix positioning and credibility gaps that are currently limiting visibility, trust, and inbound conversations. → 2. 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 𝐀𝐮𝐭𝐡𝐨𝐫𝐢𝐭𝐲 𝐚𝐧𝐝 𝐋𝐞𝐚𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 For Web3 founders and leaders who want authority and consistent pipeline, I help shape content and execution so LinkedIn becomes a reliable source of qualified leads. This includes defining what you should talk about and how your content supports real business conversations. → 3. 𝐒𝐩𝐨𝐧𝐬𝐨𝐫𝐞𝐝 𝐏𝐨𝐬𝐭𝐬 𝐚𝐧𝐝 𝐂𝐫𝐞𝐚𝐭𝐨𝐫 𝐂𝐚𝐦𝐩𝐚𝐢𝐠𝐧𝐬I distribute your message to my audience through sponsored posts. Need wider reach? I also work with a curated network of web3 LinkedIn creators to amplify beyond my own following. Why me? I'm a LinkedIn Top Voice with an audience of 64,000+ followers in the web3 space.I've done this by solving the same problem most web3 companies face: translating crypto-native credibility into positioning that resonates with institutional buyers, enterprise partners, and B2B decision-makers.Ready to build visibility that drives growth? Book a 1:1 Profile Audit Call or DM me “GROWTH". My DMs are open for everyone.

Co-Founder

A user-owned web3 DAO. Working with the best web3 companies to help them hire top crypto talent.

This idea is pretty uncomfortable to admit.

Crypto was NOT built for humans.

It was built for machines.

And once you see it, you can’t unsee it.

For 17 years we tried to force humans into crypto.

Gas fees.
Hex addresses.
12-word seed phrases.
Signing unreadable transactions.

And then we wondered why crypto didn’t go mainstream.

Because humans prefer:

• Customer support
• Reversible payments
• Simple user experience
• Someone to blame when things break

Sure, banks are hugely inefficient.

But they were designed around human needs first.

Crypto wasn’t.

Crypto is deterministic.

Rigid.
Rule based.
Unforgiving.

Now flip the lens.

Who thrives in deterministic systems?

Machines.

AI agents don’t care about simple user experience.

They don’t panic when they see a 0x address.

They don’t fall for phishing attacks.

They can:

→ Verify contracts in seconds
→ Simulate complex outcomes
→ Execute transactions automatically

Now, try plugging an AI agent into the traditional banking system.

It can’t open a bank account.

It can’t pass KYC as a human, business, or government.

It can’t legally hold funds.

The legacy system literally has no category for it.

But onchain?

A wallet is just code.

So an AI agent can hold funds, move value, and execute agreements without paperwork, approvals, or waiting on banking hours.

This is the part most people miss.

Crypto won't go mainstream as a frontend product.

But it will go mainstream as a backend infrastructure.

(Stablecoins and Real-World Assets are big facilitators in this transition.)

Humans won’t be comparing bridges or signing 7 popups.

They’ll tell their AI agent what they want:

“Pay this invoice.”
“Rebalance my treasury.”
“Find me yield with these constraints.”

The AI agent will route through stablecoins, DeFi, RWAs, whatever stack exists, and you’ll only see the outcome.

That’s when crypto finally feels normal.

Not because everyone became crypto native.

But because crypto became the default rail for machines, and humans benefited from it in the background.

The uncomfortable truth?

Crypto was never built for humans.

It was waiting for machines.

---
👋 I’m Aram, helping web3 leaders & B2B businesses grow on 𝗖𝗿𝘆𝗽𝘁𝗼 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻.

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manusiatech

solidatehq

Helping web3 B2B companies get inbound + outbound leads on LinkedIn | Building personal brands for crypto leaders | Shirtless Ultramarathoner

RWAs on Ethereum just crossed $15B.

That’s more than 3x growth in a year.

What’s driving almost all of this growth?

Tokenized funds.

Mostly short duration U.S. Treasury and money market style products.

Here are the top categories:

1. 𝗧𝗼𝗸𝗲𝗻𝗶𝘇𝗲𝗱 𝗴𝗼𝗹𝗱 𝘀𝗰𝗮𝗹𝗲𝗱 𝗵𝗮𝗿𝗱.

Tether Gold jumped from ~$515M to ~$2.71B, up ~426% YoY.

Paxos Gold climbed from ~$527M to ~$2.34B, up ~344% YoY.

Gold alone added over $4B in new onchain value.

2. 𝗧𝗼𝗸𝗲𝗻𝗶𝘇𝗲𝗱 𝗧𝗿𝗲𝗮𝘀𝘂𝗿𝘆 𝗮𝗻𝗱 𝗺𝗼𝗻𝗲𝘆 𝗺𝗮𝗿𝗸𝗲𝘁 𝗳𝘂𝗻𝗱𝘀 𝗲𝘅𝗽𝗹𝗼𝗱𝗲𝗱.

→ Ondo USDY: +190%
→ BlackRock BUIDL: +44%
→ Janus Henderson treasury: +1,700%
→ Ondo short term gov bonds: +224%
→ Superstate short duration gov fund: +670%
→ WisdomTree digital money market: +6,000%+

This is real cash management infrastructure moving onchain.

3. 𝗡𝗲𝘄 𝘆𝗶𝗲𝗹𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 𝗿𝗲𝗮𝗰𝗵𝗲𝗱 𝘀𝗰𝗮𝗹𝗲 𝗮𝗹𝗺𝗼𝘀𝘁 𝗶𝗻𝘀𝘁𝗮𝗻𝘁𝗹𝘆.
 
Syrup USDC scaled to ~$1.72B, while Syrup USDT reached ~$605M.
 
Both effectively started from a negligible base, implying hypergrowth within a single year.
 
Together, they now represent over ~$2.3B in onchain RWA value.
 
Why these assets drove the growth?
 
Because they turn idle stablecoins into yield.
 
And integrate directly into DeFi as collateral.
 
While large issuers are deploying real capital, not pilots.
  
Ethereum still dominates the RWA landscape with close to 60% market share.
 
Zooming out, stablecoins on Ethereum alone exceed $160B in market cap.
 
RWAs at $15B are still only a fraction of that base layer of onchain dollars.
 
If one of the fastest growing asset classes in crypto is still this small relative to the stablecoins, the growth ceiling is nowhere near being hit.
 
So you are still not bullish on RWAs?

P.S.
All figures above refer to the natively issued, distributed RWAs on Ethereum.
________________________________________________________
👋 I’m Aram, helping web3 leaders & B2B businesses grow on 𝗖𝗿𝘆𝗽𝘁𝗼 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻.

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Many web3 Founders wonder why enterprises won’t buy from them.

It’s NOT their tech holding them back.

It’s the way they communicate it.

Most founders speak in crypto-native language.

Hype. Jargon. Protocol talk.

Perfect for the X (Twitter) crowd.

Useless for enterprise buyers on LinkedIn.

Because these buyers don’t care about decentralisation, block space or validator sets.

They care about:

→ Reducing risk
→ Improving margins
→ Staying compliant in regulated environments
→ Getting clear outcomes they can defend internally

And when your messaging doesn’t map to those outcomes, two things happen:

• They don’t understand what you do
• They don’t trust you enough to buy

This is the silent killer of Web3 B2B growth.

Your team world-class.
Your traction impressive.
Your product can be brilliant.

But if your narrative doesn’t translate into their language, your deals die before the first call.

The teams that win outside crypto do something different:

→ They stop selling tech and start selling outcomes
→ They rebuild the founder’s LinkedIn for credibility
→ They reposition their story around business impact
→ They publish content that speaks to decision-makers, not degens

Because enterprises don’t buy innovation.

They buy clarity.

Fix the story and the sales motion finally starts moving.

P.S. 
Want to see how a web3 Founder’s narrative sounds when it’s rewritten for enterprise buyers instead of crypto natives?

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Most of of web3 Founders fail at building a personal brand. 

They keep making the same mistake all the time. 

They spread themselves too thin. 

They try to be everywhere at once.

• X
• LinkedIn
• YouTube
• Farcaster
• Newsletter
• Telegram Channel

And then wonder why nothing compounds.

Here’s the boring truth nobody wants to hear:

Pick one problem to solve
Pick one platform
Pick one niche

And double down on it until you get to 6 or 7 figure ARR. 

Only then start expanding. 

Don't dilute your attention too much. 

Most web3 Founders expand too early.
 
That’s why they stay invisible.

This is why I am only on LinkedIn and not X.

P.S.
If you had to start all over again, which platform would you pick?

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Most crypto users are forced to make the same compromise.

Either use software wallets like MetaMask that feel fast and familiar, but leave them exposed.

Or rely on hardware wallets that are secure, but clunky and awkward to use.

Neither option really fits how people actually operate anymore.

And for a long time, that was also my setup.

A mix of different wallets:

• Some software wallets for speed.
• Some hardware wallets for “safety”.

Every time I wanted to move crypto, connect to an app, or do something slightly more involved, it became a hassle.

Switching wallets.
Switching hardware devices.
Breaking my flow into unnecessary steps.

A simple portfolio rebalancing could easily take 1 hour. 

Not ideal.

Eventually it clicked that this could be much simpler.

These days, Ledger Wallet is where I manage things.

It’s the app interface I use to manage my crypto portfolio, connect to dApps and protocols, and move through web3 in a secure way.

And then there's Ledger Nano Gen5 that sits behind it as the signer.

It’s the hardware device that verifies what’s happening and signs transactions with full visibility before anything goes through.

Sleek.
Touchscreen.
Clear context.

No guessing what you’re approving.

The result is that things just feel smoother.

I cut down the portfolio rebalancing time more than 4x to under 15 mins. 

And no longer worry about choosing between convenience and security.

If you’ve been in my shoes and need a simpler setup, check out Ledger Nano Gen5.

Link is in the comments.
________________________________________________________
👋 I’m Aram, helping web3 leaders & B2B businesses grow on 𝗖𝗿𝘆𝗽𝘁𝗼 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻.

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Web3 B2B sales is broken.

Because we’re still using the old 2021 playbook.

And that playbook was built for hype.

Not for institutional or enterprise buyers.

Here’s the old way most web3 B2B teams still operate:

→ Blast automated DMs on X and call it “B2B sales”
→ Inflate follower counts with bots and vanity metrics
→ Spam prospects on Telegram from random accounts
→ Hire Twitter KOLs to pump narratives and dump attention
→ Run airdrops and InfoFi campaigns that attract the wrong crowd

This worked in 2021.

When everyone was early.
When credibility didn’t matter.
When buyers were crypto native.

Today?

Institutional and enterprise buyers see right through this.

• Telegram spam kills credibility.
• X (Twitter) outreach has low trust.
• Automation without context signals amateurism.

None of these converts into large ticket web3 B2B deals.

We need to change how we think about it.

Positioning beats noise.
Credibility beats automation.
High trust beats high volume.

Most importantly, Founders and web3 sales leaders need to be where the real buyers are.

And that's not X or Telegram.

That platform is LinkedIn.

This is where the institutional and enterprise decision makers live.

The new playbook for web3 B2B BD should be:

→ Founders build a visible personal brand on LinkedIn
→ Storytelling that builds familiarity with right stakeholders
→ Clear positioning around real business value, not token hype
→ Consistent content that explains what you do in buyer language
→ Highly customized LinkedIn approach instead of cold random DMs

When done right, something flips.

You stop chasing buyers.

Institutional and enterprise leads come to you.

Conversations start warm.

Trust is already established.

Closing large ticket web3 B2B deals becomes easier, not harder.

This is how modern web3 B2B sales actually works.

P.S.
If you’re a web3 B2B business and want to scale without spam or hype, DM me “Growth”.

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The Battle

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