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The AI gold rush has officially entered its messy phase.

For the past couple of years, Silicon Valley has been showered with headlines about all these trillion-dollar potentials, miracle software, and “game-changing” systems that were supposed to transform everything overnight. Investors piled in like gangbusters, and the media cheered it all on. And anyone who raised an eyebrow was told they just didn’t “get it.”

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But this is always how bubbles work, right? First comes all the hype. Then comes all the money. And eventually, the insiders start talking… and that’s where this latest scam story begins.

Now, one of these really hyped-up AI startups has found itself at the center of a growing storm after a former employee dropped what he claims is the beginning of a massive internal document dump. According to the post, there’s a group of former employees, contractors, and personal connections who say they’ve come forward with about 70 GB of recordings and documents tied to the Indian-owned GigaAI and claiming it’s a massive scam.

The post claims internal revenue numbers were inflated, fake customers were listed in sales decks, cap tables were misrepresented, employees were cheated out of equity, and customers were pressured or blackmailed over pricing. This former employee says the company looked very different behind the scenes than it did on pitch decks and press releases.

Jared:

giga files are here.

a small army of people came forward;
-former employees
-contractors
-personal connections

they shared ~70GB of recordings & docs.
> false revenue numbers
> hiring *female workers* in dubai
> bribing F500 co’s
> listing fake customers
> multiple false cap table claims (ex. @sama)
> not paying + cheating employees from equity
> blackmailing customers for price increases

tea incoming.

Here’s a closeup of the image:

 

We have no idea if these extremely damaging allegations are true, but this could be indicative of the massive AI bubble that’s been inflated over the past few years.

Jared, that same former employee wrote a post back in November, saying he didn’t even need weeks or months to see red flags. He says he quit after his very first day.

Jared:

Alright, time to spill the beans on giga.

Got hired back in April to lead demand gen for them.

Quit after the first day.

Red flags everywhere.
>”when we hit $10m arr, we’re going to spend $100k on ____”(illegal stuff)

>”we’re doing $____ in mrr”
(Dashboards in the hq show 6x less)

>bait n switch on title, start date, comp, etc.

>had 2 international weddings I need them to pre-approve to take time off. They said yes.
After I signed contract, they said “well you need to pick who you’re better friends with bc you can’t do both weddings now”

>”I chopped off a goats head in India bc it brings good luck”

>in office, 7 days/week, 12 hr days. “Pto policy is subject to change at our discretion… you are expected to always be working”

>gave offer letter on Wednesday, said I need to sign by Thursday, and start job Monday morning.
I had 3 days to move from atx -> sf.

>first day of work, I got in early. Founder walks in my direction, I stand up, extend my hand for a handshake. He snubs me – not even an acknowledgement.

I just moved my entire life & drove 26 hours across the country & not even a “welcome to the team” or a hello.

Easiest decision of my life to quit after first day.

I rarely root against founders, but this is the epitome of what’s wrong with tech/ai now.

Offer letter for proof.

Jared paints a picture of bait-and-switch job offers, questionable internal culture, wildly inconsistent revenue claims, and pressure tactics that would make any serious investor pause. To back up his involvement, Jared later posted a short sizzle reel he says he created during a YC work trial, pushing back on claims that his story was fabricated.

Meanwhile, GigaAI’s public image tells a very different story.

In that PR video, the company boasts about a $61 million Series A, major enterprise clients, and AI agents handling massive volumes of customer interactions across multiple languages. It’s sleek, confident, and exactly what investors want to hear in the middle of an AI gold rush.

And this is exactly where the bigger picture matters.

We’ve been asking the uncomfortable questions about hype, valuation, and whether any of this actually works the way it’s being sold.

We’ve been tracking how AI went from promising tool to speculative frenzy almost overnight, with investors throwing billions at companies that couldn’t even explain what they do, let alone prove these outrageous real-world returns. The warning signs have been there for a while. Most people just don’t want to hear them.

Revolver:

AI is the new dot-com, and just like last time, the hype is outpacing the reality at warp speed. Billions are being poured into systems nobody fully understands, run by companies that can’t even explain how their own tech works. And just like before, the herd thinks this time is different.

Spoiler alert: It’s not.

The only question now is who survives when the bubble bursts and how much of the real economy it takes down with it.

Everyone from Big Tech to Wall Street is gambling on AI like it’s a sure thing, but the cracks are already showing. According to recent research, nearly every major company pouring billions into generative AI still hasn’t seen a real return. Even the insiders—from Sam Altman to Jeff Bezos—are starting to admit what’s obvious: this gold rush feels a lot more like a bubble than a breakthrough.

The experts say that this time it’s different. But is it? Sure, the crash might not happen overnight. Maybe instead of one big nuclear pop, the AI balloon could deflate slowly, choking out the weaker players while the giants tighten their grip. But most agree that the warning signs are all there: massive investments backed by a whole lotta hype, self, and tech valuations that don’t come close to reality.

The thing about today’s AI bubble that makes it a lot worse than the ’90s dot-com mania is that these days, everything is global.

The Business Standard:

A recent MIT study found that 95% of companies investing in generative AI have yet to see measurable returns. Sam Altman, the chief executive of OpenAI, admitted that “many parts of AI are kind of bubble-y right now.” Amazon founder Jeff Bezos has voiced similar concerns, saying that when excitement peaks, “every experiment gets funded,” even when it should not.

But if AI is a bubble, it may not be one that bursts in a single dramatic pop. Economists suggest it could deflate slowly, squeezing weaker players while leaving giants standing taller. Pierre-Olivier Gourinchas, chief economist at the IMF, told Reuters that, unlike the dotcom bust, the AI boom is “not financed by debt,” which makes a systemic crash less likely. Investors may lose, but the economy will not necessarily collapse.

Still, the scale of investment is hard to ignore. OpenAI is reported to be seeking $1.5 trillion for computing capacity, far exceeding its current revenue streams. Nvidia is not only supplying chips but also investing in AI companies that depend on its hardware.

Analysts have likened this web of “circular deals” to the 1990s internet bubble, where hype fed upon itself until it could no longer sustain the weight.

The World Economic Forum’s president, Børge Brende, recently warned that AI could be one of three major bubbles threatening the global economy, alongside crypto and debt. The Bank of England issued a similar caution, saying that “the risk of a sharp market correction has increased.”

But warnings be damned, the investment money is still coming in hot, hot, hot.

You can read the full article here:

The AI bubble is about to burst and nuke a lotta people…

Even if every single allegation doesn’t hold up, it’s stories like this that are why people keep saying the AI bubble is starting to get shaky. When the hype runs ahead of the reality, and when money pours in faster than results, something’s got to give.

S

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Could this be just another Indian scam, and it’s not a “crack” in the AI system? Sure. But we can’t ignore that this system has been running on buzzwords, smoke, and investor FOMO. So, it’s understandable that questions are getting louder, and patience is wearing thin.

If this AI bubble pops, it won’t start with some massive bang. It’ll begin with stories just like this.

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