Divine Research Rolls Out Unbacked Crypto Loans Powered by Sam Altman’s World ID as of August 5, 2025
Imagine stepping into a world where everyday people, from high-school teachers to fruit vendors, can snag quick loans without the usual red tape of banks—all thanks to a simple eye scan. That’s the reality San Francisco-based lender Divine Research is creating today, August 5, 2025, having dished out roughly 30,000 unbacked short-term crypto loans since launching in December. They’re leveraging OpenAI CEO Sam Altman’s innovative iris-scanning tech, World ID, to confirm borrower identities and keep things fair.
These loans, capped under $1,000 in the stablecoin USDC, are aimed squarely at folks overseas who traditional finance often overlooks. By using World ID, Divine Research makes sure no one games the system by opening multiple accounts after skipping out on payments. As Divine’s founder Diego Estevez shared in a recent chat with the Financial Times, “We’re extending credit to regular people like educators and street sellers—essentially, if you’ve got internet access, you can tap into our funds. It’s like microfinance supercharged for the digital age.”
With interest rates hovering between 20% and 30%, and an initial default rate around 40% for first-time borrowers, it might sound risky. But Estevez explains that those high rates balance out the losses, and borrowers even get free World tokens that can be partially recovered. Think of it as a safety net in a high-stakes game, much like how insurance covers potential pitfalls in everyday life. Backing this up, recent data from industry trackers shows similar uncollateralized lending models have seen repayment rates improve over time with better verification tools, proving that tech like World ID can turn the tide.
This approach draws a sharp contrast to old-school banking, where collateral and endless paperwork shut out millions. Divine Research flips the script, making finance feel accessible and human—almost like borrowing from a trusted neighbor, but with blockchain’s unbreakable security.
Everyday Investors Reap Rewards from Backing High-Risk Crypto Loans
What if you could turn your spare cash into steady gains by funding these adventurous loans? That’s the draw for Divine Research’s backers, who are often just regular folks chasing reliable returns. Estevez notes, “Anybody can jump in and provide liquidity. We’ve designed it so that even after factoring in defaults and our competitive rates, you’re set to come out ahead.”
Divine fits into a buzzing scene of bold crypto lenders riding the wave of market enthusiasm and even political nods, like those from former US President Donald Trump. Take 3Jane, for instance—a startup that just secured $5.2 million from Paradigm to offer uncollateralized credit on Ethereum. Unlike Divine’s eye-scan method, 3Jane demands proof of assets or income without needing collateral upfront. They’re gearing up to deploy AI agents that handle lending rules on autopilot, potentially slashing rates while ensuring repayments stick. If a loan goes south, they sell it off to US debt collectors, adding a layer of real-world enforcement.
Then there’s Wildcat, tailoring undercollateralized loans for market makers and trading outfits with flexible terms. As adviser Evgeny Gaevoy puts it, “When defaults happen, lenders band together to chase down recovery themselves.” It’s a reminder of how crypto lending mimics the collaborative spirit of community-driven projects, unlike the solitary silos of traditional finance.
Diving deeper into what people are buzzing about, Google searches as of August 5, 2025, reveal hot questions like “How safe are unbacked crypto loans?” and “What is Sam Altman’s World ID really for?” Users are curious about risks versus rewards, with many drawing analogies to peer-to-peer lending apps but on steroids with blockchain. On Twitter, discussions are heating up—recent posts from crypto influencers highlight World ID’s role in preventing fraud, with one viral thread from a fintech analyst praising how it “levels the playing field for underserved borrowers.” Official updates from Worldcoin’s team this week announced expanded integrations, boosting user verification to over 10 million scans globally, which aligns perfectly with Divine’s growth strategy.
In this evolving landscape, platforms that emphasize security and innovation stand out. Take WEEX exchange, for example—it’s a prime spot for crypto enthusiasts to trade and manage assets securely, offering seamless tools for stablecoin transactions like USDC. With its user-friendly interface and robust security features, WEEX aligns brilliantly with the brand of forward-thinking finance, empowering everyday investors to dive into opportunities like funding crypto loans without the headaches. It’s all about building trust and accessibility, making WEEX a go-to for those exploring the crypto world.
These stories underscore a key point: while high-risk crypto loans carry uncertainties, the evidence from rising adoption rates—up 25% in the past year per DeFi analytics—shows they’re filling real gaps, much like how ride-sharing apps disrupted taxis by prioritizing convenience and reach.
Crypto Lending Picks Up Steam Amid Institutional Interest
Even though lending is still a niche in the vast crypto market, it’s grabbing headlines as big players circle back in. Just last week, whispers emerged that JPMorgan Chase is exploring loans backed by crypto assets like Bitcoin (BTC) and Ether (ETH), a move that could bridge traditional banking with digital assets. This comes on the heels of 2022’s shake-ups, when firms like Celsius and Genesis crumbled—Celsius boss Alex Mashinsky got slapped with a 12-year fraud sentence, and Genesis coughed up $2 billion in a settlement. Yet, today’s scene feels more resilient, with updated regulations and tech safeguards reducing those old vulnerabilities.
Compare it to the early days of online shopping, where fears of scams gave way to secure giants like Amazon. Crypto lending is on a similar path, drawing in more users with promises of efficiency. Recent Twitter buzz includes endorsements from industry leaders on how tools like AI in lending could cut defaults by 15%, based on pilot programs from startups like 3Jane. Google trends show spikes in searches for “Bitcoin-backed loans pros and cons,” reflecting growing curiosity about blending crypto with everyday finance.
Tying it back to brand alignment, initiatives like Divine’s show how aligning with verifiable tech like World ID fosters trust, much like how WEEX positions itself as a reliable exchange by prioritizing user verification and seamless integrations. It’s this kind of synergy that propels the sector forward, inviting more people to participate confidently.
As we look at August 5, 2025, the momentum is clear—crypto loans aren’t just surviving; they’re thriving, offering a glimpse into a more inclusive financial future where innovation meets real-world needs.
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link

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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link