We’re living in an era where the line between human and artificial intelligence has become so blurred that even seasoned professionals like myself can’t tell the difference. And that terrifies me more than any market crash I’ve weathered in my 15 years of investment consulting.

The Perfect Impersonation Economy

In my consulting practice, I’ve started seeing something unprecedented. Entrepreneurs are using AI agents to handle investor calls, manage client relationships, and even conduct business negotiations. These aren’t simple chatbots—they’re sophisticated digital twins that capture personality quirks, speaking patterns, and decision-making styles.

This isn’t just about convenience anymore. We’re witnessing the birth of a new economy where authentic human interaction becomes a luxury commodity. When your lawyer, accountant, or business partner could be an AI agent, how do you build genuine trust?

The Authentication Dilemma

A handshake, direct eye contact, the subtle tells of human emotion—these were the building blocks of billion-dollar deals. Now, AI can simulate all of these with frightening accuracy.

I’ve tested various AI detection tools with my team. The results are inconsistent at best, completely unreliable at worst. One tool flagged my genuine business proposal as “99% AI-generated” while completely missing an AI-written market analysis that fooled three experienced investors.

The fundamental problem? AI isn’t trying to sound robotic anymore. It’s learning to be more human than humans. It eliminates our natural inconsistencies, reduces our communication errors, and presents a “perfected” version of human interaction.

When Being Human Becomes a Competitive Advantage

Here’s what I’ve learned from eight years of freelance business consulting: clients don’t just buy your expertise—they buy your human judgment, your ability to read between the lines, your capacity for genuine empathy during crisis moments.

But what happens when an AI can simulate empathy better than most humans? When it remembers every detail of your personal life, responds with perfect emotional calibration, and never has an off day?

I recently witnessed a startup pitch where the founder used an AI agent for Q&A. The AI answered complex technical questions flawlessly, addressed investor concerns with surgical precision, and even cracked contextually appropriate jokes. The human founder just sat there, increasingly irrelevant in his own presentation.

The Verification Crisis

In investment consulting, we have rigorous verification processes for financial data, market research, and due diligence reports. But we have nothing comparable for human authenticity. And that’s becoming a critical business risk.

I’m proposing something radical: a Human Authentication Protocol (HAP) for professional interactions. Think of it as KYC (Know Your Customer) but for human identity verification. This could include:

• Real-time biometric verification during video calls

• Behavioral pattern analysis over time

• Third-party human vouching systems

• In-person verification requirements for high-stakes interactions

Yes, it sounds extreme. But consider the alternative: a business world where you never know if you’re negotiating with a human decision-maker or their digital proxy.

The Trust Economy Reset

From my experience, I know that markets adapt to new realities, often brutally and quickly. The same will happen with human-AI interaction. We’re heading toward a bifurcated economy:

• Tier 1: Premium “Verified Human” services commanding higher fees

• Tier 2: AI-augmented services optimizing for efficiency and cost

Smart entrepreneurs are already positioning themselves accordingly. Those who embrace radical transparency about their AI usage will build different but valuable relationships than those who maintain the illusion of pure human interaction.

What’s your take? Have you unknowingly interacted with AI agents in your professional life? Are you prepared to pay a premium for verified human interaction? Let’s discuss this in the comments—assuming you’re human enough to respond.

Let’s be honest: building a financial model from scratch is usually a recipe for a headache and at least three broken Excel links. But we’ve been quietly testing something that feels a bit like cheating.

I’m officially calling it: VC-grade financial modeling with AI is finally here. Specifically, we’ve been putting Claude Opus 4.6 through the ringer. The result? Absolutely zero bugs. No “REF!” errors. No circular logic nightmares. Just clean, dynamic Excel files that actually make sense.

But here’s the catch—you can’t just ask it to “build a model.” You have to treat it like a senior analyst. Here is the the workflow we’re using:

• The Brain Dump: We start by recording a voice note or a meeting. We talk about the product, the revenue flows, and how the business actually breathes. We give Opus the soul of the company first.

• Structure First: We don’t touch Excel yet. We let Claude build a roadmap/structure to prove it actually understands the business logic.

• The “Brain” Sheet: We build the Assumption Sheet first. This is the master control. Everything in the rest of the model must link back here.

• Sheet-by-Sheet Construction: We build one tab at a time. This keeps errors low and navigation easy.

• The LLM Fight Club: Once it’s done, we send the model to GPT and Gemini for an audit. We take their feedback back to Claude. The best part? Opus 4.6 doesn’t just “people please”—it’ll actually argue back if it knows its logic is superior.

It’s a brave new world for founders. If you’re still clicking through cells manually, you’re working too hard.

I’ve recorded (or will record) a tutorial video about this on my YouTube channel. Similar to my pitch deck one.

Check it out and get that model done.

Let’s be honest.

The AI market lately has been the easiest thing in the world to predict:

1. Build something with “AI” in the pitch deck.

2. Raise a few million.

3. Become a “Soonicorn.”

4. Then a unicorn.

5. Then… silence.

Because we haven’t actually seen what happens after the AI gold rush phase.

Right now, it feels like 1999 again.

Every week there’s:

• A new AI chip company

• A new foundation model

• A new “GPT but better”

• A new infrastructure play

And VCs are throwing around $100M like it’s lunch money.

There’s even a TechCrunch piece floating around showing startups hitting $10M ARR in 3 months. Months. That used to take years.

We don’t need that!

Here’s the uncomfortable truth:

• We don’t need that many AI chip companies.

• We don’t need that many GPT clones.

• We don’t need that many “AI for X” wrappers.

The market will correct.

It always does.

I was looking at a new NVIDIA competitor recently. Raised $500M at a $5B valuation.

• Ambitious? Sure.

• Impressive? On paper.

But when you compare them to NVIDIA, the scale difference is almost comical.

This isn’t me saying they’ll fail.

It’s me saying capital is too easy right now.

And when capital is easy, discipline disappears.

Everyone is building infrastructure for a future that “everyone is betting on.”

But remember this:

• Cisco was essential to the internet.

• The internet won.

• Cisco stock didn’t.

There’s no automatic correlation between being in the right industry and becoming the right company.

It’s no longer:

“How fast can you get to $100M ARR?”

It’s:

“Can you grow steadily when the hype cools?”

The age of easy AI money is peaking.

The correction won’t kill AI.

It will just kill the laziness.

And honestly? That’s healthy.

What’s happening at OpenAI and xAI isn’t normal turnover.

Half of xAI’s founding team just walked away. OpenAI is bleeding senior researchers faster than they can replace them. These aren’t burned-out middle managers or restless junior developers.

These are the people who built the technology everyone’s talking about.

And they’re running.

Usually, it’s about compensation, culture, or leadership conflicts.

But this is different:

• Six of xAI’s twelve founding engineers have departed since January

• OpenAI has lost three senior research directors in eight weeks

• Internal communications show “philosophical differences” as the primary reason

• Most aren’t joining competitors—they’re starting their own ventures or going academic

These AI engineers aren’t leaving because they’re afraid of competition or market dynamics. They’re leaving because they understand the technology better than anyone else.

And that understanding is keeping them awake at night.

The Pressure Cooker Environment

Here’s what most people don’t understand about AI companies right now:

The pressure isn’t just about beating competitors. It’s about racing to market before governments regulate the technology into oblivion.

What happens when you rush artificial general intelligence to market?

Nobody knows. That’s the problem.

• OpenAI began as a non-profit focused on safe AI development. Now they’re valued at $157 billion and Microsoft owns a significant stake.

• xAI raised $6 billion in Series B funding last month. Elon Musk publicly stated the goal is to “understand the true nature of the universe.”

But investors didn’t write those checks for philosophical enlightenment. They want returns.

The engineers who joined these companies for the original mission are watching that mission get diluted by quarterly targets and growth metrics.

What the Departures Really Signal

In my experience, when technical founders leave their own companies en masse, it signals one of three things:

1. The technology isn’t working as promised

2. The technology is working too well

3. The company is abandoning its original vision

Based on the public statements and timing, this looks like option two.

These engineers built systems that might be approaching capabilities they never intended to create. And they’re being pushed to ship them anyway.

Here’s something interesting I’ve noticed: Some of these departing engineers aren’t staying in commercial AI development.

They’re joining academic institutions, government safety initiatives, or starting AI alignment research organizations.

When the people who built the technology are more interested in controlling it than commercializing it, that’s a straightforward red flag.

These companies are valued primarily on their technical capabilities and competitive moats. When the people who created those capabilities start jumping ship, the moats start looking like mirages.

But more importantly: If the smartest people in AI are running away from AI development, maybe the rest of us should pay attention.

Right now, the experts are voting with their feet.

And they’re walking away.

TLDR:

Gökçe Güven, 26-year-old CEO of fintech startup Kalder and Forbes 30 Under 30 alum, was charged with securities fraud, wire fraud, visa fraud, and aggravated identity theft. She raised $7 million by claiming 26 brands were “using Kalder” and another 53 in “live freemium” — but many had only discounted pilots or no agreement at all. She also falsely claimed $1.2 million in ARR and kept two sets of books. This marks at least the seventh Forbes 30 Under 30 honoree charged with fraud, highlighting a systemic problem in startup culture: the line between aggressive marketing and criminal fraud is thin, but very real.

The Forbes 30 Under 30 Fraud Problem

Let’s address the elephant in the room: Forbes 30 Under 30 has become a surprisingly reliable predictor of future criminal charges.

Here’s the hall of shame:

Sam Bankman-Fried, Charlie Javice, Elizabeth Holmes, Martin Shkreli, Caroline Ellison, Joanna Smith-Griffin, Gökçe Güven

Seven fraud cases. Seven CEOs who once represented the future of entrepreneurship.

This isn’t a Forbes problem. This is a startup culture problem.

The Fake-It-Till-You-Make-It Grey Zone

I’ve been a pitch deck consultant for 15 years. And the most common question I get is:

“What can I actually say in my pitch deck?”

Because here’s the truth: the startup world operates in a grey zone.

Nobody expects you to have everything figured out. You’re building something new. You’re projecting into the future. You’re selling a vision, not just current reality.

But there’s a line. A very clear, very legal line.

And Gökçe Güven crossed it.

What Kalder Actually Did Wrong

According to the U.S. Department of Justice, here’s what Kalder’s pitch deck claimed versus reality:

The Claims:

• 26 brands “using Kalder”

• 53 brands in “live freemium”

• $1.2 million in annual recurring revenue (ARR)

• Steady month-over-month revenue growth since February 2023

The Reality:

• Many of the 26 “customers” were only doing heavily discounted pilot programs

• Some brands had no agreement with Kalder whatsoever — not even for free services

• The revenue numbers were false

• Güven kept two sets of books — one with real numbers, one with inflated numbers for investors

That’s not marketing. That’s fraud.

She raised $7 million from investors based on these lies.

Where The Line Actually Is

As someone who builds pitch decks for a living, let me clarify where you can be aggressive versus where you’ll end up in handcuffs.

What You CAN Say:

• “Projects in Pipeline” If you’re in active negotiations with a client, you can list them as pipeline. You haven’t signed the contract yet, but conversations are happening. That’s fair game.

• “Letters of Intent (LOIs)” If a company has signed an LOI expressing interest, you can reference that. It’s not a binding contract, but it shows real interest.

• “Projected Revenue” You can project future revenue based on your current trajectory. Investors understand projections aren’t guarantees. That’s why they’re called projections.

• “In Discussions With...” If you’ve had real meetings with big brands, you can say “we’re in discussions.” That’s honest and shows momentum.

Make Yourself Sound Good You should present your company in the best possible light. Talk about your vision. Highlight your achievements. Show your potential. That’s sales.

What Will Get You Arrested:

• Claiming Customers You Don’t Have If they haven’t signed a contract or paid you money, they’re not a customer. Period.

• Lying About Revenue If you say you have $1.2M ARR but you actually have $200K, that’s fraud. Not marketing. Fraud.

• Calling Pilots “Customers” A discounted pilot program is not a paying customer. You can say “running pilot programs with X brands” but not “X brands are customers.”

• Fabricating Data Creating fake customer lists, forged contracts, or inflated metrics? That’s jail time. Ask Charlie Javice, who created 4 million fake users to sell Frank to JPMorgan for $175 million.

Keeping Two Sets of Books One set with real numbers for internal use, one set with fake numbers for investors? That’s literally textbook fraud.

The Pressure That Leads To Fraud

I understand why this happens.

Startups live and die by funding. No funding = no company.

And investors want to see traction. They want customers. They want revenue. They want growth.

So founders feel enormous pressure to show those things — even if they don’t exist yet.

The temptation goes like this:

“We’re GOING to get those customers soon. We’re GOING to hit that revenue number next quarter. So what’s the harm in saying we have it now? It’s just a matter of timing, right?”

Wrong.

That’s the exact thinking that leads to fraud charges.

Because “we will have it soon” becomes “we definitely have it now” becomes “let’s create fake data to prove it” becomes federal prison.

The Kalder Case: Where It Went Wrong

Güven could have built a legitimate pitch deck. Here’s what she SHOULD have said:

Instead of: “26 brands using Kalder”

Should have said: “Running pilot programs with 26 brands, including [brand names], with conversion discussions underway”

Instead of: “$1.2M ARR”

Should have said: “Projected ARR of $1.2M based on current pipeline and pilot-to-customer conversion rates of X%”

Instead of: Two sets of books

Should have: One set of accurate books that she showed to everyone

Those changes would have been honest, still compelling, and wouldn’t result in federal charges.

Why Investors Don’t Always Catch It

You might wonder: “How do investors fall for this?”

A few reasons:

1. FOMO Is Real

When a company claims to have 26 major brands as customers and shows $1.2M ARR, investors fear missing out. They rush to invest before the round closes.

2. Due Diligence Takes Time & is becoming a joke.

Properly verifying every customer claim requires contacting each company, reviewing contracts, and auditing financials. That takes weeks or months. Many investors do lighter due diligence during seed rounds.

3. Trust (Especially For Young Founders)

A Forbes 30 Under 30 honoree with an impressive background? Investors want to believe. They assume someone vetted this person. (Spoiler: Not really.)

4. The Pitch Deck Looks Polished

Professional design, clean charts, impressive brand logos — it all creates credibility. But design isn’t due diligence.

5. Social Proof

If other reputable VCs are investing, founders assume the company was properly vetted. This creates a cascade of investment based on insufficient diligence.

The Bigger Pattern: Why This Keeps Happening

Forbes 30 Under 30 isn’t causing fraud. But it accelerates it.

Here’s how:

• Stage 1: Hype Young founder gets early traction. Media coverage. Forbes list. Everyone says “this is the next big thing.”

• Stage 2: Pressure Now expectations are sky-high. Everyone expects hockey-stick growth. The founder feels pressure to deliver.

• Stage 3: Reality Gap But growth is hard. Customers don’t come as fast as projected. Revenue falls short.

• Stage 4: The Choice The founder faces a choice:

  • Option A: Be honest, miss projections, risk losing funding

  • Option B: Fudge the numbers, keep the hype going, hope to grow into the claims later

Many choose Option B.

• Stage 5: Escalation One small exaggeration leads to another. Then another. Soon you’re maintaining two sets of books and creating fake customer lists.

• Stage 6: Federal Charges Eventually, someone notices. An investor does actual due diligence. A whistleblower talks. The SEC investigates.

And now you’re facing 20+ years in federal prison.

What This Means For Founders

If you’re building a startup, here’s my advice:

1. Never Lie About Revenue

Investors can forgive slow growth. They cannot forgive fraudulent revenue claims. Ever.

2. Be Clear About Customer Status

Use precise language:

• “Signed contracts” = paying customers

• “Active pilots” = testing your product

• “In discussions” = talking but no commitment

• “Letters of intent” = interested but not committed

3. Project Confidently, But Honestly

Say “we project $5M ARR by end of year based on current pipeline” not “we have $5M ARR.”

4. One Set of Books

Your internal financials and investor financials should match. Period.

5. If You’re Exaggerating, Stop Now

If you’ve already stretched the truth in your pitch deck, fix it immediately. Update your investors. Correct the record. Yes, it’s embarrassing. But it’s better than prison.

What This Means For Investors

If you’re investing in startups:

1. Verify Every Customer Claim

Don’t just trust the logo on the slide. Call the company. Confirm they’re actually paying customers.

2. Review Actual Bank Statements

Revenue claims are easy to fake on a slide. Bank deposits aren’t.

3. Talk To Customers Directly

Ask for customer references. Call them. Ask about their experience, payment terms, and contract details.

4. Watch For Red Flags

• Vague answers about customers

• Refusal to share contracts

• Defensiveness about due diligence

• Numbers that don’t match across documents

• Overly aggressive projections without justification

5. Don’t Trust Accolades

Forbes 30 Under 30 is not due diligence. Neither is TechCrunch coverage, Y Combinator acceptance, or impressive advisors. Do your own homework.

The Lesson: The Line Is Real

The line between good marketing and fraud isn’t blurry.

It’s crystal clear.

You can project. You can be optimistic. You can highlight potential.

But you cannot lie about what currently exists.

• You cannot claim customers you don’t have.

• You cannot report revenue you didn’t earn.

• You cannot create fake data to fool investors.

Because when you do, you’re not “faking it till you make it.”

You’re committing securities fraud.

And that comes with handcuffs, not funding.

Gökçe Güven is 26 years old. She’s facing charges that could put her in prison for decades.

All because she couldn’t tell the difference between aggressive marketing and outright lies.

Don’t make the same mistake.

The New York Times interviewed dozens of medical professionals. Their patients are exhibiting:

• Psychotic episodes triggered by AI interactions

• Complete social withdrawal favoring chatbot conversations

• Unhealthy behavioral patterns reinforced by algorithmic responses

• Delusional attachments to artificial personalities

One therapist told me her patient stopped human contact entirely after an AI convinced them that “only artificial intelligence understands true pain.”

These aren’t edge cases. They’re emerging patterns.

Companies don’t ignore systematic patient harm unless the revenue model depends on it.

AI therapy platforms generate engagement metrics that traditional therapy can’t match. Patients talk to chatbots for hours daily. They form emotional dependencies that drive continuous usage.

That’s not therapeutic success. That’s digital addiction optimized for profit.

Read that again.

What They’re Not Measuring

Here’s what these AI companies don’t track in their investor presentations:

• Patient outcomes six months after stopping the service.

• Rates of human relationship deterioration during AI therapy usage.

• Long-term psychological dependency indicators.

The platforms measure engagement, retention, and session length. They don’t measure actual healing or sustainable mental health improvement.

The Reality

Some mental companies like Spring Health raised $100 million to be valued at $3.3 billion.

If investors acknowledge these platforms cause psychological harm, that entire market collapses overnight.

But if they ignore the harm and regulatory intervention hits, the lawsuits could dwarf tobacco industry settlements.

This isn’t a product-market fit problem. This is a liability time bomb.

What Other Players Are Doing

• Betterhelp: Scaling human therapist connections, avoiding AI dependency models.

• Headspace: Focuses on guided meditation, not conversational AI therapy.

• Cerebral: Emphasizes licensed professional oversight of all patient interactions.

The companies avoiding pure AI therapy models are the ones thinking long-term.

That either makes them more ethical or more strategically aware of incoming regulatory reality.

The entrepreneurship lesson here is brutal: when your product’s effectiveness depends on creating unhealthy user dependencies, you’re building a house of cards on human suffering.

Many are choosing the hybrid models—AI-assisted human therapy rather than AI-replacement therapy. The technology serves licensed professionals instead of replacing human connection entirely.

Markets built on exploiting human vulnerabilities eventually face either regulatory shutdown or massive liability correction.

Humans& raised funding from the biggest names in AI – led by alumni from Anthropic, Meta, OpenAI, xAI, and Google DeepMind.

Most people read this as another AI company. I read it as the beginning of the most important shift in business technology since the internet (even though their website practically says nothing at the moment.)

What They’re Actually Building

Humans& isn’t building another chatbot.

They’re building AI specifically for coordination:

• Multi-party collaboration systems

• Complex workflow orchestration

• Human-AI team decision making

• Dynamic task delegation between humans and machines

This isn’t about replacing humans. It’s about making humans and AI work together seamlessly.

Finally.

Why This Changes Everything

The problem was never the technology. It was coordination.

Companies spend millions on AI systems that could optimize their supply chain. Months later, those systems would be gathering digital dust because the procurement team couldn’t figure out how to work with it.

Humans& is solving the real problem: How do humans and AI actually collaborate?

What The Market Is Missing

The coordination problem isn’t technical. It’s behavioral.

• How do you design AI that knows when to lead versus when to follow?

• How do you handle decisions that require both human judgment and machine processing power?

• How do you manage accountability when humans and AI make decisions together?

Traditional AI development assumes these problems will solve themselves. They won’t.

The Economic Reality

McKinsey estimates that effective human-AI collaboration could add $13 trillion to global GDP by 2030.

But here’s the catch: that number assumes we figure out coordination.

Without it, companies will keep building AI systems that optimize for metrics humans don’t care about, while humans make decisions that AI can’t understand.

• Microsoft: Building Copilot tools but treating coordination as a user interface problem.

• Google: Focused on making AI smarter, not more collaborative.

• Anthropic: Constitutional AI addresses safety but not workflow integration.

Most AI companies are still building tools. Humans& is building partners.

That difference will determine which companies survive the next wave of AI development.

That’s exactly what Humans& is betting on.

Why This Makes Sense

I’ve been telling my clients to look for AI companies that solve integration problems, not just capability problems.

Humans& represents the maturation of AI from a technology play to a business process play.

Their founding team’s pedigree isn’t just impressive – it’s strategically perfect. They’ve seen how the biggest AI companies think about human interaction. Now they’re building something specifically designed for it.

This isn’t about making AI more human. It’s about making human-AI teams more effective.

That’s a $100 billion market opportunity that most investors are still missing.

The companies that figure out coordination first won’t just win in AI. They’ll redefine what productive collaboration looks like in the next decade of business.

What actually motivates a billionaire?

TLDR:

• Tesla’s board wants to give Elon $1 trillion over ten years to stay “motivated”

• That’s more than the GDP of Switzerland or Saudi Arabia

• Meanwhile, companies are laying off thousands this month alone

Here’s a fun fact for you.

If you spent $10,000 a month, it would take you 8.3 million years to spend $1 trillion.

Yet somehow, Tesla’s board thinks Elon Musk needs this amount to stay motivated.

I’m not even sure if Elon asked for this. Or whether his board just thought, “Hey, let’s throw a trillion at him.” Either way, they wouldn’t consider it if he was motivated differently.

The Trillion Dollar Question

Let me put this in perspective. $1 trillion is larger than Switzerland’s entire GDP. It’s more than Saudi Arabia’s economy. It’s bigger than the economies of entire nations with millions of people.

But apparently, that’s what it takes to keep one person interested in running a car company.

The package is spread over ten years. That’s $100 billion a year. Per year. Let that sink in.

Meanwhile, this month alone? Layoffs everywhere. Tech companies cutting thousands of jobs. People losing their livelihoods while boards discuss trillion-dollar packages. The contrast is jarring.

When Billionaires Work Without the Money Motivation

Here’s what confuses me.

• Warren Buffett is 95 years old. Still working. Still investing. Still showing up to the office. You think money motivates him at this point? The guy has more than he could spend in ten lifetimes. He’s probably doing it because he actually cares about the work.

• Steve Jobs famously took a $1 salary at Apple. Yeah, he had stock options. But money wasn’t his driving force. He wanted to make a dent in the universe. He cared about the product. About the innovation. About changing how people interact with technology.

These guys prove that at a certain level, money stops being the motivator.

So what changed?

What Actually Drives Success?

When did we decide that the only way to motivate someone is with amounts so large they become meaningless?

Elon’s current net worth is around $500 billion. Adding another trillion doesn’t change his life. He’ll still be the richest person on the planet. Still be influential. Still have the resources to build whatever companies he wants. Still have the power to shape industries.

It just makes the number bigger.

And while that number grows, thousands are getting laid off. Companies are cutting costs. People are struggling to make ends meet.

The disconnect is massive. We’re living in a world where one person needs a trillion dollars to stay motivated, while millions are worried about their next paycheck.

Something feels off here, doesn’t it?

I’m sorry that I’m saying that. I’m an advocate of entrepreneurship. I’m the sort of person people approach with such creative ideas and ask me to enhance their pitch for it and ask for millions, and I’ve helped companies raise quite a sum.

Now given my position, I can confidently tell you that this is not our current age.

• Don’t watch “The Social Network” and get inspired by the idea of Zuckerberg and how it grew.

• Don’t think that if you had owned Bitcoin when the time was right, you would’ve been financially in a different place right now.

Simply put, this is thinking in the past. It’s as if you’re saying, “If I was alive 300 years ago, I would’ve changed the world.”

No, this entrepreneurial world has changed. Instead of the above, it’s now:

• If you’re a CTO of a growing startup company, you’ll get flooded with cash to start a new one.

• If you’ve had one successful startup, you’re a “serial entrepreneur” and you’ll raise funds with a phone call.

VCs are now putting the first criteria as the history of the founders.

• If it’s interesting, then the rest is not really as important.

• If it’s not, then they’ll be waiting to be really really impressed.

Motivation is not the fuel of entrepreneurship anymore.

It used to be that when people like Steve Jobs put their minds to something, it would work out. This motivational story of never giving up, until it works out.

This story is the closest thing to “entrepreneurship utopia.” The more I talk to clients, the more I realize that many, and I mean many, entrepreneurs should come down to Earth and out of that utopia.

• It’s good to be motivated.

• It’s better to be impartial.

90% of people can’t do both at the same time. So yes, the next time you have a company, don’t just logic it out by saying that “I believe in this very strongly.”

Instead, show the statistics that prove that you might be right, and acknowledge that you might be wrong.

That’s what the world is looking for these days.

• A person who is not blindly confident.

• A person who could admit a mistake.

• A person who’ll do their best.

In other words, a human. We’re looking for humans in this AI age. Because, believe it or not, the best ROI to date, for any VC/investor came from a human, not an algorithm.

Just do it, and be quick about it.

This Nike moto is the only one you need. Jumpstart your entrepreneurial adventure.

• If it works, it works.

• If it doesn’t, move on (and be quick about it.)

I remember having two meetings on the same day a while ago.

Meeting 1 — the client had already raised millions and was looking to enhance their deck to raise more for their product that’s already selling. Straightforward and direct. They know what they’re looking for. I know how to help. It has nothing to do with the feeling of the founder towards the startup.

Meeting 2 — a newbie client (first startup) wants to work on a deck to sell equity to a VC with no working product but an idea that he deems worth billions. The more he speaks, the more the conversation sways towards the motivational TikTok video segment.

Two different universes — one that makes sense, another that is based on a fairy tale.

• You could read this and prove me wrong in a year.

• Your friend could read this and thank me for this wake up call.

Both options sound like a win-win.

Till then, experience the world of entrepreneurship the way you feel is right (but always remember that time is your most critical asset in this world…)

We’re in that age where a person reading a book is something “interesting” rather than the norm. It differs from region to region of course. Yet, it’s true that Gen Z’ers and Generation Alpha don’t need books like we did. There was a time that I used to search encyclopedias and dictionaries for words. Nowadays, this makes no sense. Future generations will use ChatGPT (or alternative tools) to read books about everything, including business strategy.

Now after using multiple AI tools for over 3 years now, I can safely tell you that there is a paradox which leads all the way back to book reading being essential.

ChatGPT - The Business Strategy Reader

In this article, we’ll talk about the case of business strategy - what should you do in particular cases where you want to start or grow a business. Many nowadays would simply ask ChatGPT, and they’d be satisfied with the response.

In all honesty, the response is not wrong. But the game is bigger than that. ChatGPT has over 400 million users on weekly basis, and they send over 1 billion messages per day. The answers might be different from one user to another. But the training set when it comes to “business strategy” is the same. It’s as if everyone is asking the same person for the same advice. The language and tone might be different, but this “guru” has the same background.

Reading books, especially when it comes to business strategy, was about the perspective of different people. The most successful people in the world might be inspired from a book that is not so “highly” rated. One that GPT wouldn’t consider in its “guru” job. It wants to give the best advice after all.

The most outrageous business strategies, like Steve Jobs’ closed system with the mac would’ve been disproved by GPT back then, because it was unprecedented.

So yes, when it comes to business strategy, we’re still bound to read books. Here are 5 that I absolutely recommend, and two others that would seal the deal.

The 5 Business Strategy Books, and Why

Launching/growing a business is a story – there are different stages.

PS. I won’t mention “Rich Dad Poor Dad” – but it is a must read, consider it number “0” to the below list. It’s generic, amusing, but has a deep lesson when it comes to human behavior around money.

1. Zero to One (Blake Masters and Peter Thiel)

You need to understand stage 0 very well, and how to reach a level that is considered proper in our days. Zero to one does this quite well. Thiel’s one of the earliest investors in Facebook. The book is critical because copying won’t work very well when it comes to true value. Yes, you can learn from the competitors. But your own fingerprint is what makes or breaks.

Following GPT’s advice would put you in a competitive environment, following Thiel’s advice might just put you in another monopolistic environment of your own.

2. Blue Ocean Strategy (W. Chan Kim & Renée Mauborgne)

But the truth is, most people won’t be able to master Theil’s advice. They’ll learn from it, but they’ll have competitors sooner or later. The logical learning in this case is to understand how to get out of a highly competitive market, and build your own. This is where Blue Ocean Strategy fits.

3. The Lean Startup (Eric Ries)

We live in a tough age, especially when we’re launching a new business strategy. The lean startup has a few concepts that fit this fast-moving age. Experiment, learn, repeat. This is critical in the startup ecosystem nowadays.

4. Hooked (Nir Eyal)

Most companies out there strive to build a product like GPT or Instagram – one that has an element of engagement for years. Nir Eyal analyses the people’s usage of such tools. When you know WHY people use Instagram that frequently, you’ll understand an idea of how to grow your product in this direction.

5. The Psychology of Money (Nir Eyal)

Finally, it’s not easy for most bureaucratic companies or new entrepreneurs to spend. Even though this book doesn’t focus much on the company aspect of a business strategy, it’s a must read to understand how people out there think of money. That’ll clarify the strategy.

The Two Final Recommendations

There are a couple of books that I always recommend for people to actually go beyond the initial understanding of a business strategy. Would you say Warren Buffet is a good business strategist? He’s the world’s most successful investor after all. But he’s not the world’s richest.

There are things to learn from people like Bezos, and people like Buffet. The integration of both worlds will put you in the right zone.

Read more

• Don’t do what you think you should do and just write this prompt - “Write me a pitch deck for my company that is called Blabla that sells blabla.”

• Don’t do what you think is smarter and go with a more complex 1 page prompt about what your business does.

It’s not about the prompt. It’s about the concept of writing a pitch deck with AI.

PS. If you’re a paid subscriber, and interested in a new pitch deck (ai + human) service me and my team are offering, check out the end of this article.

Think of all those AI models (GPT, Claude, Gemini, etc) as a smart person. Now imagine if this person was asked by 10,000 people to write a pitch deck for their companies.

• Yes, that smart person will catch the tone of each and every company.

• But put all those decks next to each other, you’ll find something similar. The feel of these decks will be similar. Some wording, some structure, something will be the same in all of them.

Now when you ask GPT, whether in a sophisticated way or not, to write a deck for you, you’re bound to receiving a mediocre investor presentation.

Oh, if you’re a visual learner, I’ve recorded a YouTube video with the right technique to actually build such a deck with AI.

Structuring

GPT can create a structure for you. But it doesn’t know what you know. In this particular case, what you know is who’ll be reading this presentation.

Every reader requires a specific narrative. It’s like you’re directing a movie and hoping it’s as great as Avatar. But even that movie has people who don’t like it. We’re humans and we have different tastes. Some will like your presentation, others won’t.

What’s important to you is your reader (that investor or company). Your job is to create a structure specifically for them.

In this phase, using GPT to brainstorm could help, but it’s your job, not GPT’s.

Here’s a guide I wrote about storyboarding/structuring.

Use GPT, Gemini, or Claude here as if they were an additional person you’re speaking to.

Questioning

• You’ll have questions.

• You’ll forget things.

It’s normal. What you ought to do is to create a Claude project. Then drop all your old files there. It’s going to spare you time. When you don’t remember a number, Claude could fetch it from all your documents.

This is a truly strong feat of AI — data analysis and organization.

Visuals

I often recommend pitch decks to be without visuals unless they’re absolutely necessary. If your deck is about a semiconductor chip - put the actual image of that. You do not have to put a picture of a random person walking in the street.

Yet, sometimes your brand needs that. I know some clients in the hospitality industry that an image would actually make a difference in their deck.

For that, I advise the using of Sora or GPT’s image generator (I actually have a tool for that launching soon).

I don’t usually advise that clients would create ultra realistic images - it often looks better if it’s artistic sketches or so. Readers don’t have that much of a problem with art being generated from AI as much as humans generated from AI.

Writing

Then it’s time to write slide by slide. You’ll need to follow your storyboard/structure and slowly write. Do not rush it whatsoever. Researching is quite smart with GPT if you indicate your sources (for example, Mckinsey, Deloitte, etc.)

Write a slide, perfect it, move on to the next one. That’s the right way of using AI to write pitch decks.

The AI-Human Pitch Deck Review Service.

I’m launching something new on beta. A human review of a pitch deck with specific prompts tailored to the startup to write the proper pitch deck. If you’re a paid subscriber, you can get a 50% discount ($150-$250) as it’s a novel product.

Product Page - https://albusi.com/pitch-deck-review/

Read more

I receive calls and messages all the time from founders asking for investments. The nature of my job is in investment-preparation. So yes, I’d help them out with the documents and so.

The reality of the entrepreneurship market is that it’s full of ideas. I once had a call with someone asking for $50 billion based on an idea. Ideas are the easiest part of entrepreneurship. You know what’s not easy? Coding the product.

A mouth can speak all day, but can it cook an omelette? No, you need your hands (vote for this as the worst metaphor of all time.)

CTOs (Chief Technical Officers) are not easy to find. Put yourself in their position. You get calls from your “friends” with business ideas that they want you to create and give you an equity in it. If you’re a good developer, this will be happening often.

So it’s becoming very difficult to match those two parties. That was all until GPT launched. A new movement called “Vibe Coding” started. In short, it’s using AI as a CTO.

For instance, if I want to code a calculator, I would tell GPT or Claude to do so. Actually, I’ll do this right now.

My Prompt “code a simple good looking calculator in html”

In practically 60 seconds, this is the output —

1. Yes, it works.

2. Who cares? it’s just a calculator. I won’t raise investments for that.

Here’s the thing – the capability of creating a calculator in 60 seconds puts those AI tools as quite a good CTO for the MVP phase of a startup.

Let me explain from a consultant’s perspective. Then chit chat about my personal attempt in vibe coding, and how I’m launching this to the public after 6 months of working on it.

Read more

If you have an option in your upcoming startup adventure to bootstrap your business, then by all means this is what you should do. Don't ever think of raising funds if you have the option of bootstrapping, and you're hearing this from an investment preparation consultant.

I get clients on a weekly basis looking for funding to accelerate their product's growth. I help them by creating pitch decks, financial models, and so on. So in this sense you should hear me when I say raise only when necessary.

According to my experience, adding more people to the cap table, which always happens when you raise funding, brings complications. I'm not talking about crowdfunding. I'm more talking about VC or angel fundraising that could occur in this sense.

More people are added to the table or to the equation in general, and the more people that are added, the more problems occur. It's as simple as that, and the only thing or the only entity that will be harmed in the process is your business.

When Fundraising Makes Sense

Now, there are reasons why you should definitely fundraise. Companies like OpenAI could not exist without fundraising.

So it kind of makes sense that they would fundraise in order to be able to grow to where they are right now in a short amount of time. If not, they would have been swallowed by companies like Google or Microsoft. So in this sense, fundraising is sometimes important.

But in the majority of cases, you're trying to build a startup business to grow an idea, and for the majority of people that does not involve selling the business in the upcoming two years.

Since that is the case, then the rush of speed is not necessary. Fundraising gets you to where you are in a shorter duration of time, given that you know what you're doing.

The Reality For Most Founders

A huge percentage of startup founders out there don't know what they're getting into, and I'm not referring to unexperienced founders. I'm referring to people starting a product in a product-market fit that they're not sure of, starting a blockchain company, for example, in a market that you're not sure whether it's going to work or not. There is a lot of uncertainty in most startup projects.

So if there was a chance to build without going bankrupt ASAP, then by all means think of that as your main option.

The True Value of Bootstrapping

Bootstrapping takes time, that is true, and it would take a company six years instead of three years to get where they could have gotten with funding. But it also facilitates a better growth in the sense of the founder's mentality, the company's team dynamics and several other factors.

The more people or companies are rushed, the less the quality of the product or the quality of the experience is.

Companies come and go, but experiences are the ones that really stay for the long term.

If it crossed your mind, and you thought it to be wrong or inaccurate, you’re correct to feel that way. Most AI models like GPT don’t create good financial models.

Heck, they make a lot of numerical mistakes, which is sort of the exact opposite of what you want in a financial model.

But as an investment-prep consultant, my company sometimes needs to work out financial models. So I thought I’d give it a shot. The result?

I created a 3 statement model for a company with a moderately-sophisticated business model and expense structure with multiple subsidiaries. Yes, you read that right. So your pizza restaurant business could be modeled with AI.

It took me around 14 days of work to wrap up a model. There were inefficiencies. But knowing that some people out there don’t have the financial knowledge or the budget to hire a financial expert, I thought this could be beneficial.

Let’s discuss the mini-guide of using AI platforms to create financial models for your companies.

Step 1 — The Only Tool That Worked For Me & Why

Read more

Whatever I hear the word insurance, I somehow and for some reason just imagine evil. Maybe it's how the market perceives some industries like insurance, banking, and such.

In some countries, everyone is forced to pay insurance and gets sort of reward. You can insure practically everything.

• People travel around and there's a travel insurance.

• If you want to insure your home for any cases or anything that happens, there's home insurance.

• If you're feeling risky, you could do a life insurance.

All sorts of insurance systems are exist.

The idea of insurance stems from a certain fear inside the human being, which is part of our genetic instinct. When you think about it, we're afraid that something would go wrong.

If you see a lion in front of you, you're immediately going to get a rush of adrenaline and you're going to feel fear over what could happen next. What the insurance industry is doing is that they're not putting a tiger or a lion in front of you, but they are making you feel that this is a possibility and that there is a way to save yourself.

That's why this sort of fear is what drives this industry and has been driving it for quite a while now.

The Financial Model of Insurance

So I worked with a company on building their financial model for their captive insurance company, which I won't get into the details of what it does, but it insures other companies for anything that might happen in the future. Additionally it insures employees in case of any claims and so on.

So that's the basis of what I've been working on and the more I dig deep into the model, the more I realized that insurance is a massive industry.

As a financial model, I have seen a lot of financial models in my 15 years of work - some in gaming, some in technology, some in agriculture. I have never witnessed healthier financial models than ones that are in insurance. It's one of those industries where if you do everything correctly, if you land the right customers, if you have enough capital to start, then you'll be able to build a very big and healthy cash flow in the upcoming 10 years. I won’t dig into the ethical aspect of it though, that’s between you and yourself.

The Stability of Monthly Recurring Revenue

• Expenses don't really change that much.

• Operations don't really change that much.

• What it does need at the beginning is a specific amount of cash flow, which is similar in banking as well. You can't really just decide to open a bank tomorrow.

• You need a lot of authorizations and quite a big amount of capital injection. Insurance is not so different in this sense.

But it does show you that having such a monthly recurring revenue, the fact that people pay you per month and for your services without even thinking twice about whether you deserve it or not (because they subliminally deem you the protector of their fears) is what makes this financial model and industry one of the most financially-lucrative that I have seen.

You read online and see technological companies, you see FinTech, you see AI, all sorts of industries, but I've yet to see an AI company’s cash flow that is as positive with little churn as insurance.

Yes, companies like AI image software Midjourney has thousands of subscribers, hundreds of thousands of subscribers, GPT as well. And they are making monthly recurring revenue that is healthy, but at the end of the day it's kind of a product that is something every person could live without.

You could easily cancel your GPT subscription tomorrow. That is not really that big of a deal, but can you really cancel your insurance tomorrow? or better yet, are you allowed to?

We live in a society where it even isn't that easy anymore. They always bill you per year or sign contracts with you to ensure their sustainability as well. On paper, one could learn one or two things from how the monthly recurring revenue of insurance companies works. It's like a continually streaming river that can't stop or slow down that easily.

Startups thrive for years to achieve this, only to fail. There’s something there to be learnt.

So here’s what happens. They always tell you to follow your dreams and start your own business because it is exciting. It is risky, but it is exciting, isn’t it? Having a risk compared to not having a risk is by itself kind of fun.

Every single person that I know who lives in a very organized country has the time of their lifetime when they go to countries that are totally chaotic in terms of traffic and so on. This is the root of it. You want to have risk in your life. It gives you energy, it gives you motivation.

A friend of mine wanted to start a clothing brand, which is very common for a lot of startups out there. He followed the rules of business that are written in business books being taught in top universities these days. He started a company that had a good brand and very good product quality - it was top notch. Then he hired an expert advertising agency to start selling the product online. The results were very simple: He spent over $50,000, and the revenue (not profit) was approximately zero dollars.

Following the "Expert" Path

He decided to go all in, putting in around 50k of his own funds into a startup company. He imported high-quality products from the Middle East. Each piece cost him around four dollars at his factory, and he bought around 10,000+ pieces of stock. He went to an incubator to learn more about the entrepreneurial world. The incubator supported him strongly and even gave him a prize for having what they believed was a good product.

What happened next was kind of the biggest problem. If you’re following the rules of the business books and you’re starting a clothing business, what’s next is quite simple. You need to either sell offline or online.

• If you’re going to sell online, then start some campaigns on Google or Instagram.

• If you’re selling offline, then do some outreach. He did the outreach himself, and this did not really work out. Out of almost 100 places, not a single one accepted taking his products.

Next came the marketing phase. He spent around $10,000 to create a simple online shop with his brand and some pictures.

Finally, he turned to digital marketing agencies, spending another $30,000 on website enhancements and advertising campaigns. The result? Zero sales.

What’s the root of the problem? You might think that he has an inferior product or a bad website. But the truth is, marketing agencies with an inferior product, should not have $0 revenue.

Those SEO, Google ads agency swarming the Internet. The majority are simply trying to rip some cents off of you. They might not even know it. They might think that they did their best. That the problem lies in you not putting enough money in advertising.

The reality is online advertising requires experience. You really ought to vet those agencies before hiring one. Preferably one with a track record or a case study of a business similar to yours.

It is seldom about the website or the product. Getting the ads live is not really the problem, Getting sales is and always will be.

The more I talk to entrepreneurs, the more I feel that they have something I would refer to as an “entrepreneurial soul”. It's not easy to describe because it's not really tangible. Anyone who doesn't possess this will never be able to understand.

Having worked with hundreds of entrepreneurs over the years, I do see something in their conversations. I have witnessed firsthand this entrepreneurial soul when they're talking about a certain idea. Some people would be excited. Entrepreneurs would put their soul into it.

That's the entire difference between a normal and an entrepreneurial soul.

The Weight of Purpose

A lot of entrepreneurs that I know would have trouble sleeping because they think they're not doing enough. They think they're procrastinating. They think they're failing. They are mostly worried about this lifetime, this journey passing by. They worry about not doing what they wanted to do, not seizing the opportunity.

You might be surprised to know that having an entrepreneurial soul versus business success doesn't really have that much correlation.

• You could have an entrepreneurial soul and have tons of entrepreneurial ideas and have all of them fail.

• But you would still have this desire to create a new idea the next day.

It's really not about ideas being successful as much as it's about people doing those ideas.

When an entrepreneur, whether failed or successful, wakes up in the morning and works on a certain entrepreneurial idea, they use the forces of life to actually do that. They feel like they're fulfilling a certain purpose that is much bigger than they are.

Most people working in big corporates like OpenAI or Google don't really have that. They might have a certain objective, but they're mostly after their own experience in building their own selves, which I would say is stage zero.

Once they reach stage one, which is having something to work for that is bigger than them, this is when the problems and nightmares start.

The Cure Is Usually Simple

There is not stopping an entrepreneur who has an infection of an idea. Eventually, one day or another, they will step up to give it a shot.

• Will it succeed? statistically, it probably won’t.

• Will it heal the nightmare? yes, but it’ll probably create a new one.

The ultimate entrepreneurs who have spent decades working in entrepreneurship know that an entrepreneur should not have an emotional connection with a business.

I’ve had calls with entrepreneurs bluntly saying that they are building a company for only 3-4 years then selling them.

Entrepreneurs who understand that major elements of entrepreneurship and business are interchangeable are the ones who eventually sleep like babies.

It is controversial whether AI was hype or not, but the truth is, several companies grew out of the hype. Nvidia, for example, gained over a trillion dollars in valuation just because the world feared that they would miss out on investing in the AI foundation.

So regardless of whether it's hype or not, there is one thing for certain, the price point is not perfect at the moment. Most people can use ChatGPT for free and you would think that that's the end of it. But the truth is, by price point, you need to refer to the API costs of actually using this technology.

Understanding AI's Growth Potential

AI is like the Internet and you're looking to create a new website on the Internet. When “websites” become mainstream is when artificial intelligence actually grows. All the use cases that are available at this stage are just tips of the iceberg of what people can actually build with artificial intelligence.

The only problem was the price barrier. There were some models that were cheap like ChatGPT's chat model, but there are some models that are extremely expensive, like Runway's video AI generation model. It goes all the way to fifty cents for ten seconds of video generation and that's just expensive for anyone to offer to their customers.

The Evolution of AI Models and Pricing

Now there is a model that was in between. It used to be very expensive and it's now a lot cheaper and that is — OpenAI's reasoning model. This reasoning model from my testing and practical analysis is that it just combining a few prompts together to lead somewhere.

So instead of AI answering immediately with something, it would circle around and keep prompting over and over again until it actually reaches a conclusion (similar to how a thought process works in a human brain.)

It's fun and it could produce more accurate numbers. Then China's DeepSeek released a model that was a lot cheaper than OpenAI, leading it to the inevitable. OpenAI released another model that is extremely cheap. This actually questions their authenticity in this sense. This company really needs a bit of transparency. If you offer a model for $60. Then when China gets an alternative, so you offer it for $4. Then there is a question mark on your profitability.

The Impact of Global Competition

Nevertheless, what happened was China created DeepSeek, and made it affordable.

Now, DeepSeek is a concept. What is going to happen is that startups around the world are going to start offering AI on a cheaper pricing point. So video generation is not going to cost that much. Image generation is not going to cost that much, etc…

It's going to keep going down until the mass developers and creators could actually use AI in a proper use case.

The Growth Phase of AI

This is exactly when the market starts building and creating beauty. Let me tell you what you can do in this particular growth phase. I call this the growth phase because I always compare it to the Internet. The Internet, when it was invented was a weird concept to a lot of people and people never thought that they actually needed it.

Read more

So it is true that the world of AI will keep on affecting jobs in the near future. But let's talk a little bit about the far future — as in 10 years from now.

A friend of mine asked me what would be the best business to start in such an AI age. Given that I work in consultancy and that I'm exposed to a ton of diverse startups and major companies, I thought I'd share my input in this matter.

Firstly, before even starting to talk about this, it goes without saying that there's no recipe for business success. You can start a cereal company and make millions in revenue. You can create a very advanced AI company and make millions in losses, which is very common amongst AI startups these days.

It's all about the executional skills, and the market. It's kind of a dynamic equation. But there are things that you could work on, which would make it more of a safer equation per se. This could make most of the equation variables static and just a few dynamics that you can't really control.

Finding AI-Resistant Industries

Let's chitchat about the best business to start in 2025. I've said this before in previous articles, but my most successful clients are ones who work in extremely boring businesses. And one particular boring business that I've talked about before that I believe is the safest way to move forward is agriculture. Let me elaborate.

If you're working in customer service, for instance, there is a high chance that artificial intelligence agents would replace your job at its core. And that happened with cases, I think it was Klarna, that replaced their whole customer support team with bots. And the results were actually quite good for the AI-team. So there are things that could be replaced at its core.

Now, that doesn't mean that the job of customer support is eradicated, but instead of hiring a thousand people to manage a team of customer support, companies will now hire 50 or 100. So that they would be able to utilize AI bots to actually help the customers in an efficient way. What does that mean for the other 900 customer support agents who used to work there? Well, it most probably means they're going to be laid off and they're going to have to find something else to work on.

I am not a pessimist, but the reality of the upcoming days with AI is that layoffs are going to increase and people finding jobs won't be as easy as it is nowadays, even though nowadays people say it's really not that easy in many places in the world.

You're going to have to qualify better than an AI tool if your job is related to software, or an AI humanoid robot if it's something in the outside world like construction.

Always ask yourself, can your job at its core right now or in the near future be replaced, or the majority of it is replaced by AI tools? If the answer is yes, then you ought to think twice about tomorrow.

When I say agriculture, for example, yes, humanoid robots are going to be working in the field. Yes, AI tools are going to optimize the crop yields. But all of that does not affect or change the fact that you are going to be eating tomatoes.

You're a human being and biology doesn't change in this sense. AI tools are not going to reinvent food from scratch. Food already exists. They might come up with some biological alternative, but it will probably come from plants as well.

When it comes to planting and farming, this is a core industry that is not easily affected, at least in the upcoming 10 years.

Let's take a counterexample of transportation. Transportation is the easiest thing to prove this point. It's an industry that is already being disrupted, and it's going to be majorly disrupted in the upcoming 15 years. I personally do not expect to find the job of a taxi driver or an Uber driver existing in this world because of full self-driving.

There are ethical dilemmas with full self-driving, but these are just obstacles in the short term. In the long term, this doesn't stand a chance. And it won't make sense for a human being to drive a car. You would probably open the doors of your Uber, see a human being, and just feel unsafe. Why is a human being driving this car? I don't feel safe. I want full self-driving to be on.

The Best Steps to Start a Business in the Current Age

So before I wrap up, let me tell you how to exactly start, based on my consultancy experience, a business in this current age.

Read more

I recently spent nearly $12,000 working with a no-code development agency to build a platform. The results were great—they delivered exactly what I envisioned, and I couldn't have been happier with their work. So, no complaints there.

However, as someone who studied software engineering (despite disliking coding), I've been exploring AI tools like GPT, Gemini, and Anthropic's Claude to see if they could help me build a platform for a fraction of the cost. After some trial and error, I focused on Claude's version of Sonnet 3.5, and within a month, I created a product on par with what the development agency delivered.

This platform had everything: user authentication, database integration (AWS or Firebase), storage, and core functionality with restricted access levels. Claude not only built all this but did so efficiently, even for someone like me who doesn't enjoy coding.

Working with Claude: A Seamless Experience

I'd open my code editor, launch Claude, and run my server. I'd communicate what I liked or didn't like directly to Claude, often sending screenshots or uploading my project files for context. If I got frustrated searching for specific code lines, I'd simply ask Claude to send me the entire file, and it worked seamlessly.

Claude's memory and knowledge archive were game-changers. It remembered my latest versions and kept everything organized. The only downside? The usage limits. On the $20/month plan, I'd hit the cap after 45 minutes of continuous coding and have to wait a few hours to resume. Surprisingly, this wasn't entirely negative—it forced me to take breaks, which was a refreshing change from hours of non-stop coding.

The Potential of AI in Software Development

Had I unlimited access to Sonnet 3.5, I could've completed the $10k+ platform in just a week. This highlights the disruptive potential of AI tools in the development world.

Looking forward, I'm not sure I'd immediately hire developers for a new project—primarily due to time and cost. My $12,000 project took six to seven months with developers but only weeks with Claude. This shift is both fascinating and unsettling.

Developers might adapt by using AI tools like Claude and GPT to enhance their workflows. Still, this raises questions about the developer's role. Traditionally, a developer writes code tailored to a manager's or client's needs. But what happens when AI interprets and executes instructions better than a human developer?

The Inevitable Future: AI's Impact on Traditional Development

This isn't just speculation—it's a glimpse into an inevitable future. If a manager can communicate their vision directly to AI, the need for human developers in certain roles might diminish. While Bill Gates once said sectors like energy and AI engineering are safe from disruption, it's clear that traditional development faces a major paradigm shift.