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GeekWire’s Todd Bishop tries Amazon’s new smart delivery glasses in a simulated demo.
SAN FRANCISCO — Putting on Amazon’s new smart delivery glasses felt surprisingly natural from the start. Despite their high-tech components and slightly bulky design, they were immediately comfortable and barely heavier than my normal glasses.
Then a few lines of monochrome green text and a square target popped up in the right-hand lens — reminding me that these were not my regular frames.
Occupying just a portion of my total field of view, the text showed an address and a sorting code: “YLO 339.” As I learned, “YLO” represented the yellow tote bag where the package would normally be found, and “339” was a special code on the package label.
My task: find the package with that code. Or more precisely, let the glasses find them.
Amazon image from a separate demo, showing the process of scanning packages with the new glasses.
As soon as I looked at the correct package label, the glasses recognized the code and scanned the label automatically. A checkmark appeared on a list of packages in the glasses.
Then an audio alert played from the glasses: “Dog on property.”
When all the packages were scanned, the tiny green display immediately switched to wayfinding mode. A simple map appeared, showing my location as a dot, and the delivery destination marked with pins. In this simulation, there were two pins, indicating two stops.
After putting the package on the doorstep, it was time for proof of delivery. Instead of reaching for a phone, I looked at the package on the doorstep and pressed a button once on the small controller unit —the “compute puck” — on my harness. The glasses captured a photo.
With that, my simulated delivery was done, without ever touching a handheld device.
In my very limited experience, the biggest concern I had was the potential to be distracted — focusing my attention on the text in front of my eyes rather than the world around me. I understand now why the display automatically turns off when a van is in motion.
But when I mentioned that concern to the Amazon leaders guiding me through the demo, they pointed out that the alternative is looking down at a device. With the glasses, your gaze is up and largely unobstructed, theoretically making it much easier to notice possible hazards.
Beyond the fact that they’re not intended for public release, that simplicity is a key difference between Amazon’s utilitarian design and other augmented reality devices — such as Meta Ray-Bans, Apple Vision Pro, and Magic Leap — which aim to more fully enhance or overlay the user’s environment.
One driver’s experience
KC Pangan, who delivers Amazon packages in San Francisco and was featured in Amazon’s demo video, said wearing the glasses has become so natural that he barely notices them.
Pangan has been part of an Amazon study for the past two months. On the rare occasions when he switches back to the old handheld device, he finds himself thinking, “Oh, this thing again.”
“The best thing about them is being hands-free,” Pangan said in a conversation on the sidelines of the Amazon Delivering the Future event, where the glasses were unveiled last week.
Without needing to look down at a handheld device, he can keep his eyes up and stay alert for potential hazards. With another hand free, he can maintain the all-important three points of contact when climbing in or out of a vehicle, and more easily carry packages and open gates.
The glasses, he said, “do practically everything for me” — taking photos, helping him know where to walk, and showing his location relative to his van.
While Amazon emphasizes safety and driver experience as the primary goals, early tests hint at efficiency gains, as well. In initial tests, Amazon has seen up to 30 minutes of time savings per shift, although execs cautioned that the results are preliminary and could change with wider testing.
KC Pangan, an Amazon delivery driver in San Francisco who has been part of a pilot program for the new glasses. (GeekWire Photo / Todd Bishop)
Regulators, legislators and employees have raised red flags over new technology pushing Amazon fulfillment and delivery workers to the limits of human capacity and safety. Amazon disputes this premise, and calls the new glasses part of a larger effort to use technology to improve safety.
Using the glasses will be fully optional for both its Delivery Service Partners (DSPs) and their drivers, even when they’re fully rolled out, according to the company. The system also includes privacy features, such as a hardware button that allows drivers to turn off all sensors.
For those who use them, the company says it plans to provide the devices at no cost.
Despite the way it may look to the public, Amazon doesn’t directly employ the drivers who deliver its packages in Amazon-branded vans and uniforms. Instead, it contracts with DSPs, ostensibly independent companies that hire drivers and manage package deliveries from inside Amazon facilities.
With the introduction of smart glasses and other tech initiatives, including a soon-to-be-expanded training program, Amazon is deepening its involvement with DSPs and their drivers — potentially raising more questions about who truly controls the delivery workforce.
From ‘moonshot’ to reality
The smart glasses, still in their prototype phase, trace their origins to a brainstorming session about five years ago, said Beryl Tomay, Amazon’s vice president of transportation.
Each year, the team brainstorms big ideas for the company’s delivery system. During one of those sessions, a question emerged: What if drivers didn’t have to interact with any technology at all?
“The moonshot idea we came up with was, what if there was no technology that the driver had to interact with — and they could just follow the physical process of delivering a package from the van to the doorstep?” Tomay said in an interview. “How do we make that happen so they don’t have to use a phone or any kind of tech that they have to fiddle with?”
Beryl Tomay, Amazon’s vice president of transportation, introduces the smart glasses at Amazon’s Delivering the Future event. (GeekWire Photo / Todd Bishop)
That question led the team to experiment with different approaches before settling on glasses. It seemed kind of crazy at first, Tomay said, but they soon realized the potential to improve safety and the driver experience. Early trials with delivery drivers confirmed the theory.
“The hands-free aspect of it was just kind of magical,” she said, summing up the reaction from early users.
The project has already been tested with hundreds of delivery drivers across more than a dozen DSPs. Amazon plans to expand those trials in the coming months, with a larger test scheduled for November. The goal is to collect more feedback before deciding when the technology will be ready for wider deployment.
Typically, Amazon would have kept a new hardware project secret until later in its development. But Reuters reported on the existence of the project nearly a year ago. (The glasses were reportedly code-named “Amelia,” but they were announced without a name.) And this way, Amazon can get more delivery partners involved, get input, and make improvements.
Future versions may also expand the system’s capabilities, using sensors and data to automatically recognize potential hazards such as uneven walkways.
How the technology works
Amazon’s smart glasses are part of a system that also includes a small wearable computer and a battery, integrated with Amazon’s delivery software and vehicle systems.
The lenses are photochromatic, darkening automatically in bright sunlight, and can be fitted with prescription inserts. Two cameras — one centered, one on the left — support functions such as package scanning and photo capture for proof of delivery.
A built-in flashlight switches on automatically in dim conditions, while onboard sensors help the system orient to the driver’s movement and surroundings.
Amazon executive Viraj Chatterjee and driver KC Pangan demonstrate the smart glasses.
The glasses connect by a magnetic wire to a small controller unit, or “compute puck,” worn on the chest of a heat-resistant harness. The controller houses the device’s AI models, manages the visual display, and handles functions such as taking a delivery photo. It also includes a dedicated emergency button that connects drivers directly to Amazon’s emergency support systems.
On the opposite side of the chest, a swappable battery keeps the system balanced and running for a full route. Both components are designed for all-day comfort — the result, Tomay said, of extensive testing with drivers to ensure that wearing the gear feels natural when they’re moving around.
Connectivity runs through the driver’s official Amazon delivery phone via Bluetooth, and through the vehicle itself using a platform called “Fleet Edge” — a network of sensors and onboard computing modules that link the van’s status to the glasses.
This connection allows the glasses to know precisely when to activate, when to shut down, and when to sync data. When a van is put in park, the display automatically activates, showing details such as addresses, navigation cues, and package information. When the vehicle starts moving again, the display turns off — a deliberate safety measure so drivers never see visual data while driving.
Data gathered by the glasses plays a role in Amazon’s broader mapping efforts. Imagery and sensor data feed into “Project Wellspring,” a system that uses AI to better model the physical world. This helps Amazon refine maps, identify the safest parking spots, pinpoint building entrances, and optimize walking routes for future deliveries.
Amazon says the data collection is done with privacy in mind. In addition to the driver-controlled sensor shut-off button, any imagery collected is processed to “blur or remove personally identifiable information” such as faces and license plates before being stored or used.
The implications go beyond routing and navigation. Conceivably, the same data could also lay the groundwork for greater automation in Amazon’s delivery network over time.
Testing the delivery training
In addition to trying the glasses during the event at Amazon’s Delivery Station in Milpitas, Calif., I experienced firsthand just how difficult the job of delivering packages can be.
GeekWire’s Todd Bishop uses an Amazon training program that teaches drivers to walk safely on slippery surfaces.
Strapped into a harness for a slip-and-fall demo, I learned how easily a driver can lose footing on slick surfaces if not careful to walk properly.
I tried a VR training device that highlighted hidden hazards like pets sleeping under tires and taught me how to navigate complex intersections safely.
My turn in the company’s Rivian van simulator proved humbling. Despite my best efforts, I ran red lights and managed to crash onto virtual sidewalks.
GeekWire’s Todd Bishop after a highly unsuccessful attempt to use Amazon’s driving simulator.
The simulator, known as the Enhanced Vehicle Operation Learning Virtual Experience (EVOLVE), has been launched at Amazon facilities in Colorado, Maryland, and Florida, and Amazon says it will be available at 40 sites by the end of 2026.
It’s part of what’s known as the Integrated Last Mile Driver Academy (iLMDA), a program available at 65 sites currently, which Amazon says it plans to expand to more than 95 delivery stations across North America by the end of 2026.
“Drivers are autonomous on the road, and the amount of variables that they interact with on a given day are countless,” said Anthony Mason, Amazon’s director of delivery training and programs, who walked me through the training demos. One goal of the training, he said, is to give drivers a toolkit to pull from when they face challenging situations.
Suffice it to say, this is not the job for me. But if Amazon’s smart glasses live up to the company’s expectations, they might be a step forward for the drivers doing the real work.
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Spain has officially completed its most ambitious space project to date with the successful launch of the SpainSat NG II satellite, marking a significant leap forward in the country’s aerospace capabilities. The launch, conducted by SpaceX on October 25, 2025, from Cape Canaveral, Florida, saw the satellite lifted into orbit aboard the Falcon 9 rocket. This milestone is a critical achievement in Spain’s growing role in space technology and secure communications.
A Leap Toward Secure Communications
The SpainSat NG II satellite is designed to provide Spain and its allies with secure and resilient communication systems, critical for defense, governmental operations, and international collaborations. The satellite forms part of Spain’s effort to ensure greater control over its communication infrastructure, especially for high-stakes areas like defense and national security.
Weighing over six tons and standing 7.3 meters tall, SpainSat NG II is one of the largest and most advanced communications satellites launched by Spain. Its primary mission is to offer satellite communication services to the Spanish Armed Forces, NATO, the European Union, and other allied nations. This satellite is equipped with state-of-the-art technology, including advanced antennas, cyberattack-resistant systems, and protection mechanisms that can withstand nuclear events in the upper atmosphere.
Strong International Collaboration
The successful completion of the SpainSat NG II project represents the culmination of significant international collaboration. Spain’s aerospace company Hisdesat worked closely with Airbus, the lead contractor in developing the satellite, which has been designed with cutting-edge technology and robust security features. More than 45% of the satellite’s development was carried out within Spain, underscoring the country’s expanding capacity to build advanced aerospace technology.
In addition to its security features, SpainSat NG II is designed to provide broad coverage, spanning multiple regions of the world. It will facilitate secure communication services over Europe, Africa, the Middle East, and even parts of the Americas and Asia. This global reach will significantly enhance Spain’s communication capabilities in a range of international contexts.
Completion of the SPAINSAT NG Constellation
The successful launch of SpainSat NG II also completes the SPAINSAT NG constellation, following the earlier launch of SpainSat NG I in 2025. Together, these two satellites form a comprehensive network of communication infrastructure, providing reliable, secure connections across nearly two-thirds of the Earth’s surface.
This completion highlights Spain’s growing role in the global space community, with the two satellites offering advanced communications in strategic regions where Spain has critical interests. The combination of SpainSat NG I and NG II will ensure that Spain remains well-positioned to maintain a leading role in Europe’s security and communication sectors.
Overcoming Technical Hurdles
While the launch was successful, it wasn’t without challenges. Initially scheduled for October 24, the launch was delayed by 24 hours due to a technical issue with the Falcon 9 rocket’s safety system. However, SpaceX quickly resolved the problem, and the launch proceeded smoothly the next day. This quick recovery is a testament to the resilience and efficiency of both the Spanish and American teams involved in the project.
This technical delay highlights the complexity of space missions but also underscores the sophistication of modern space technology and the reliability of commercial partnerships, like that of SpaceX and Spain’s aerospace industry.
Strengthening Spain’s Technological Sovereignty
The launch of SpainSat NG II is a major step toward achieving greater technological sovereignty for Spain. As a member of the European Union and NATO, Spain’s investment in its own secure communications infrastructure is an essential component of its national security strategy. By developing and deploying its own satellite technology, Spain is reducing its reliance on foreign systems and establishing greater control over its communication networks.
This move is not only a triumph for Spain’s space industry but also strengthens Europe’s broader efforts to assert its technological independence. With increasing geopolitical tensions and the growing importance of secure communications, Spain’s new satellite capabilities will be essential for maintaining operational autonomy and enhancing collaboration with its European and international partners.
Looking Ahead: The Future of Spain’s Space Program
The launch of SpainSat NG II marks the completion of one of Spain’s most significant space projects, but it also paves the way for further developments in the country’s space program. The success of this mission is likely to spur further investment in Spain’s aerospace industry and open doors for future projects, including the development of additional satellites and even more advanced communication systems.
Spain is also moving toward the implementation of a new digital screening system by 2028 for visa-exempt travelers. This effort is part of a broader push to bolster Spain’s technological capabilities, particularly in the space sector, to ensure it remains competitive on the global stage.
Conclusion
With the successful launch of SpainSat NG II, Spain has firmly established itself as a key player in the global space sector. This achievement is not only a technological feat but also a strategic move to ensure Spain’s secure communications and technological autonomy. As the SPAINSAT NG constellation takes its place in orbit, Spain’s commitment to innovation and space technology is evident, and its future in the space race looks brighter than ever.
The global crypto market capitalization saw a modest 0.8% hours to $3.73 trillion.
As altcoins displayed mixed performance, Pump.fun’s native coin stole the show with an impressive jump.
PUMP increased from $0.003757 low on its daily chart to a $0.004179 intraday peak – an 11.23% uptick.
The digital coin’s bullish momentum coincides with an optimistic announcement from the Launchpad.
The Solana-based token generator has confirmed buying PadreApp, a flourishing multi-chain trading terminal that supports Ethereum, Solana, Base, and BNB Chain.
Pump.fun’s team expressed excitement about the acquisition, stating:
The Padre team is exceptional builders who have been building in crypto for multiple cycles and have always put users first. With our resources and unique position as the most dominant and innovative Launchpad, Padre will be able to unlock more edge for traders than any competitor.
we're excited to announce that pump fun has acquired @PadreApp
Padre is an industry leading trading terminal which provides a seamless, high-speed trading experience with next level analytics for professional traders on Solana, BNB Chain, Base, and Ethereum L1
Padre is an industry-leading trading terminal which provides a seamless, high-speed trading experience with next-level analytics for professional traders.
What’s next for PadreApp
Pump.fun declared that Padre will continue running as normal, enabling individuals to buy and sell assets on all leading DEXs and launchpads on Ethereum L1, Base, BNB Chain, and Solana.
Moreover, the application will maintain its ultra-fast shipping.
Meanwhile, users will experience various changes, including enhanced user experience for all coins launched on Pump.fun, magnified trading incentives, and improved speed and data.
Most importantly, the PADRE token will discontinue as it lacks utility on the platform.
The changes aim to advance Padre, making it a powerful tool for retail and professional traders within Pump.fun’s expanding ecosystem.
PUMP soars 11%
Pump.fun’s native token exhibited a bullish bias amidst the acquisition updates.
It is trading at $0.004016 after correcting from intraday highs.
While buyers dominate the short-term outlook, the 13% decline in 24-hour trading volume suggests weakness.
Thus, PUMP might erase the gains, especially as selling pressure overwhelms the broader market.
Technical indicators also suggest short-lived gains for PUMP.
The 1H Moving Average Convergence Divergence demonstrates buyer exhaustion as red histograms surface.
Moreover, the RSI suggests weak momentum.
Nevertheless, extended overall market recoveries will fuel continued PUMP rallies.
Tye Brady, chief technologist for Amazon Robotics, introduces “Project Eluna,” an AI model that assists operations teams, during Amazon’s Delivering the Future event in Milpitas, Calif. (GeekWire Photo / Todd Bishop)
SAN FRANCISCO — Amazon showed off its latest robotics and AI systems this week, presenting a vision of automation that it says will make warehouse and delivery work safer and smarter.
But the tech giant and some of the media at its Delivering the Future event were on different planets when it came to big questions about robots, jobs, and the future of human work.
The backdrop: On Tuesday, a day before the event, The New York Times cited internal Amazon documents and interviews to report that the company plans to automate as much as 75% of its operations by 2033. According to the report, the robotics team expects automation to “flatten Amazon’s hiring curve over the next 10 years,” allowing it to avoid hiring more than 600,000 workers even as sales continue to grow.
In a statement cited in the article, Amazon said the documents were incomplete and did not represent the company’s overall hiring strategy.
On stage at the event, Tye Brady, chief technologist for Amazon Robotics, introduced the company’s newest systems — Blue Jay, a setup that coordinates multiple robotic arms to pick, stow, and consolidate items; and Project Eluna, an agentic AI model that acts as a digital assistant for operations teams.
Later, he addressed the reporters in the room: “When you write about Blue Jay or you write about Project Eluna … I hope you remember that the real headline is not about robots. The real headline is about people, and the future of work we’re building together.”
Amazon’s new “Blue Jay” robotic system uses multiple coordinated arms to pick, stow, and consolidate packages inside a fulfillment center — part of the company’s next generation of warehouse automation. (Amazon Photo)
He said the benefits for employees are clear: Blue Jay handles repetitive lifting, while Project Eluna helps identify safety issues before they happen. By automating routine tasks, he said, AI frees employees to focus on higher-value work, supported by Amazon training programs.
Brady coupled that message with a reminder that no company has created more U.S. jobs over the past decade than Amazon, noting its plan to hire 250,000 seasonal workers this year.
His message to the company’s front-line employees: “These systems are not experiments. They’re real tools built for you, to make your job safer, smarter, and more rewarding.”
‘Menial, mundane, and repetitive’
Later, during a press conference, a reporter cited the New York Times report, asking Brady if he believes Amazon’s workforce could shrink on the scale the paper described based on the internal report.
Brady didn’t answer the question directly, but described the premise as speculation, saying it’s impossible to predict what will happen a decade from now. He pointed instead to the past 10 years of Amazon’s robotics investments, saying the company has created hundreds of thousands of new jobs — including entirely new job types — while also improving safety.
He said Amazon’s focus is on augmenting workers, not replacing them, by designing machines that make jobs easier and safer. The company, he added, will continue using collaborative robotics to help achieve its broader mission of offering customers the widest selection at the lowest cost.
In an interview with GeekWire after the press conference, Brady said he sees the role of robotics as removing the “menial, mundane, and repetitive” tasks from warehouse jobs while amplifying what humans do best — reasoning, judgment, and common sense.
“Real leaders,” he added, “will lead with hope — hope that technology will do good for people.”
When asked whether the company’s goal was a “lights-out” warehouse with no people at all, Brady dismissed the idea. “There’s no such thing as 100 percent automation,” he said. “That doesn’t exist.”
Tye Brady, chief technologist for Amazon Robotics, speaks about the company’s latest warehouse automation and AI initiatives during the Delivering the Future event. (GeekWire Photo / Todd Bishop)
Instead, he emphasized designing machines with real utility — ones that improve safety, increase efficiency, and create new types of technical jobs in the process.
When pressed on whether Amazon is replacing human hands with robotic ones, Brady pushed back: “People are much more than hands,” he said. “You perceive the environment. You understand the environment. You know when to put things together. Like, people got it going on. It’s not replacing a hand. That’s not the right way to think of it. It’s augmenting the human brain.”
Brady pointed to Amazon’s new Shreveport, La., fulfillment center as an example, saying the highly automated facility processes orders faster than previous generations while also adding about 2,500 new roles that didn’t exist before.
“That’s not a net job killer,” he said. “It’s creating more job efficiency — and more jobs in different pockets.”
The New York Times report offered a different view of Shreveport’s impact on employment. Describing it as Amazon’s “most advanced warehouse” and a “template for future robotic fulfillment centers,” the article said the facility uses about 1,000 robots.
Citing internal documents, the Times reported that automation allowed Amazon to employ about 25% fewer workers last year than it would have without the new systems. As more robots are added next year, it added, the company expects the site to need roughly half as many workers as it would for similar volumes of items under previous methods.
Wall Street sees big savings
Analysts, meanwhile, are taking the potential impact seriously. A Morgan Stanley research note published Wednesday — the same day as Amazon’s event and in direct response to the Times report — said the newspaper’s projections align with the investment bank’s baseline analysis.
Rather than dismissing the report as speculative, Morgan Stanley’s Brian Nowak treated the article’s data points as credible. The analysts wrote that Amazon’s reported plan to build around 40 next-generation robotic warehouses by 2027 was “in line with our estimated slope of robotics warehouse deployment.”
More notably, Morgan Stanley put a multi-billion-dollar price tag on the efficiency gains. Its previous models estimated the rollout could generate $2 billion to $4 billion in annual savings by 2027. But using the Times’ figure — that Amazon expects to “avoid hiring 160,000+ U.S. warehouse employees by ’27” — the analysts recalculated that the savings could reach as much as $10 billion per year.
Back at the event, the specific language used by Amazon executives aligned closely with details in the Times report about the company’s internal communications strategy.
According to the Times, internal documents advised employees to avoid terms such as “automation” and “A.I.” and instead use collaborative language like “advanced technology” and “cobots” — short for collaborative robots — as part of a broader effort to “control the narrative” around automation and hiring.
On stage, Brady’s remarks closely mirrored that approach. He consistently framed Amazon’s robotics strategy as one of augmentation, not replacement, describing new systems as tools built for people.
In the follow-up interview, Brady said he disliked the term “artificial intelligence” altogether, preferring to refer to the technology simply as “machines.”
“Intelligence is ours,” he said. “Intelligence is a very much a human thing.”
Brevis will develop a trustless rebate system for routers that integrate v4 hooked pools.
The initiative will verify rebates automatically without centralized supervision.
The program aims to supercharge Uniswap v4 adoption by rewarding aggregators.
The Uniswap Foundation has awarded blockchain infrastructure company Brevis a significant grant in efforts to fuel the adoption of its recent upgrade, Uniswap 4.
According to today’s official blog, the foundation plans to allocate up to $9 million to launch and manage an innovative Hooks Routing Rebate program.
The new initiative offers gas rebates to routers that have integrated v4’s hooked pool.
Notably, the grant aims to hasten Uniswap’s version 4 adoption.
To accelerate v4 hook adoption and make aggregator integration more rewarding, Uniswap has awarded a grant to Brevis to leverage its ZK Data Coprocessor and zkVM to deliver trustless gas rebates to any routers that route order flow through v4 hooked pools.
🚀 @UniswapFND has awarded Brevis a grant to build a trustless gas rebate program for v4 routers!
Up to $9M in rebates for DEX aggregators integrating v4 hooked pools. All calculations verified by Brevis ZK proofs.
The decentralized trading protocol released its V4 update early this year, introducing advanced features like hooks – which are modules that developers can use to personalize liquidity pools.
Moreover, V4 launched a singleton infrastructure that merges pools under a single contract.
These upgrades introduced friendly fees, on-chain automation, and enhanced experience for decentralized application (dApp) developers.
Furthermore, v4 promised traders reduced slippage, lowered fees, and more efficient trade execution.
Beyond customizability, Uniswap v4 provides gas savings for both swappers and LPs. Creating new pools with v4 is up to 99.99% cheaper than in previous versions, and swappers can expect gas savings on multi-hop swaps.
Rewarding aggregators after resource-intensive tasks
Besides introducing new advancements, the upgrade brought new challenges for decentralized aggregators like Velora, 1inch, and 0X.
Decentralized aggregators are platforms that find the top trade routes by combining liquidity across different DEXs.
Previous versions had easier integrations.
For instance, Uniswap v2 adopted a constant-product approach, whereas version 3 amplified complexity through concentrated liquidity and fee tiers.
Nonetheless, v3 still ensures a consistent model.
Meanwhile, the much-awaited Uniswap version 4 allowed each pool to function independently based on the hooks it utilizes.
With that, hooks could introduce new execution ideas, apply special trading conditions, and adjust fees.
That offers the flexibility that boosts integration.
However, it made everything demanding and complex, as aggregators should familiarize themselves with how every personalized pool functions before using it to route trades.
That’s where the new rebate program by the Uniswap Foundation comes in.
The initiative allows the interoperable protocol to incentivize routers that integrate hooked pools successfully, offering up to $9 million in gas rebates.
Users will receive the rewards automatically according to their routing activity.
Meanwhile, these rebates can lower trading fees, fund ecosystem developments, and offset gas expenses.
The team said:
These rebates provide routers new economic relief to experiment with v4 hooks. Whether routers use them to offset their own operating costs, pass rebates back to traders as lower fees, or build sustainable treasuries, the result is the same: faster integrations, deeper liquidity, and better swap execution with reduced fees for users.
Uniswap’s native token, UNI, trades at $6.24 after an over 1% increase in the past 24 hours.
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Skins have always been part of the Counter-Strike DNA, and that’s the case for lots of online games. But in CS2, they’re more than just cosmetics that you can win/purchase and use forever. Here they’re tradable assets with real value. From $2 sticker-covered rifles to $2,000 factory-new knives, CS2 skins have created a digital economy of their own. Sometimes CS2 skins bring even more profit than Bitcoin or S&P500. And while some players just collect, others are turning skins into side hustles – or even full-time income.
In this article, we’ll walk you through the world of skin trading, how much you can make, and what path to take depending on your level of experience. And since crypto is becoming the go-to method for flexible, fast, and global trading, we’ll also show you how platforms like white.market are giving players better ways to buy and sell skins in a safe, P2P environment.
What Is Skin Trading in CS2?
At its core, skin trading in CS2 is the buying, selling, and exchanging of in-game cosmetic items – primarily weapon skins, knives, gloves, and stickers. But it’s not just about looks. These virtual items hold real monetary value, and many players treat them like digital assets. Some collect for the flex, others invest long-term, and many actively flip skins to make a profit.
Here’s how it works:
Skins can be obtained by opening cases, buying from other players, or trading through a marketplace.
Once you own a skin, you can list it for sale, hold it as an investment, or trade it for another item.
Marketplaces like white.market offer advanced tools – like price tracking, float filtering, and limit orders – so users can buy low and sell high.
Because the skin market is open 24/7 and largely unregulated, there’s a ton of freedom and flexibility. You can build your collection, flip skins for profit, or scale up to pro-level trading.
How Much Can I Earn from Skin Trading?
The amount you can earn from CS2 skin trading depends heavily on your experience, strategy, and starting budget – but yes, real money can be made, and people are doing it every day. Whether you’re flipping cheap skins or dealing in high-tier knives, skin trading can be a side hustle or even a serious source of income.
Let’s break it down by some real numbers and examples:
Flipping Budget Skins
Many beginner traders start by buying and reselling lower-tier skins like AK-47 | Redline, AWP | PAW, or M4A1-S | Basilisk. These cost anywhere from $1 to $10 and often have small but consistent price movements.
Once you have a bit more capital ($100–$500+), you can start flipping mid-range items like StatTrak™ rifles, gloves, or knives with visible wear.
Flip profit: $10–$50 per item
Successful trades per month: 10–20
Monthly earnings: ~$300–$1,000+
This is where many hobbyist traders begin to treat skin trading as a legitimate side income.
High-End Traders & Collectors
Some traders go deep into the market – buying rare knives (like Karambit | Doppler or Butterfly Knife | Fade), investing in souvenir skins, or even flipping old sticker crafts from CS:GO majors.
Here are a few notable real-world examples:
ZipelCS, a well-known trader, reportedly built a six-figure inventory by flipping rare knives and investing in undervalued skins over several years.
A user known as ohnePixel once bought a Katowice 2014 sticker capsule for around $30–$50 and later sold it for over $5,000.
In 2022, a Chinese collector purchased a Factory New AK-47 | Case Hardened with 4x Titan Holo (Kato 2014) stickers for over $150,000 – yes, for one gun skin.
While these extreme profits aren’t typical, they show how deep the skin economy can go. At the high level, skilled traders routinely make $2,000–$10,000/month, or more – depending on risk, capital, and knowledge of the market.
Quick Summary of Potential Earnings:
Trader Type
Monthly Profit Range
Strategy
Beginner
$50 – $300
Flip budget skins, small volume
Intermediate
$300 – $1,000+
Trade mid-tier items regularly
Advanced
$1,000 – $5,000+
Flip rare items, larger inventory
Collector/Investor
$5,000 – $10,000+
Long-term investment in rare skins
The key takeaway? With the right tools, patience, and understanding of the market, CS2 skins aren’t just pixels – they’re profit opportunities.
Levels of Skin Traders – Where Are You, and What Should You Do?
Not every trader starts with a $5000 knife collection. Most people begin small, test the waters, and slowly level up their skills. Here’s a breakdown of the four main types of CS2 traders, along with tips tailored for each stage. Whether you’re just discovering the market or flipping skins like a pro, there’s always a way to trade smarter.
Noob – “I have no idea how skin trading works”
If you’ve never traded a skin before, or only used the Steam Market once or twice, you’re a Noob – and that’s fine. Everyone starts here. At this stage, the goal is to understand how the market works and avoid common mistakes like:
Falling for fake trade bots or scam links
Buying overpriced skins on Steam
Sending your skin to an unverified platform
What to do:
Start watching YouTube tutorials and follow legit traders on social media
Learn about float values, wear levels, and pricing trends
Use trusted marketplaces like the white.market to explore the scene safely
Try flipping a few low-tier skins (under $10) to get a feel for how trades work
Beginner – “I’ve bought or sold a few skins, but I’m still learning”
You’ve done a trade or two. You understand how listings work and may have even tried your first flip. At this level, your goal should be to build consistency – learning which skins are worth trading, tracking price changes, and managing a basic budget.
What to do:
Start using price history tools and float filters when browsing skins
Flip safe, in-demand skins like AWP | Asiimov, AK-47 | Vulcan, or M4A1-S | Decimator
Watch the market daily for discounts or underpriced listings
Stick to one or two knife types or categories you know well
This is the perfect stage to try out limit orders, a key feature that lets you set the price you’re willing to pay and wait for the deal to come to you.
Experienced – “I flip skins regularly and earn money from it”
At this point, you’ve likely developed a strategy. You know which items sell fast, and how to time your purchases, and you probably track market trends around events like cases, tournaments, and updates. You might even have a spreadsheet or Discord group for deals.
What to do:
Diversify your inventory: knives, gloves, and high-tier rifles
Use white.market’s 0% buyer fee and 0% withdrawal/deposit fee (via WhiteBIT Codes) to maximize profit
Take advantage of trending events–like sticker releases or limited drops–to buy in early
Consider re-investing profits into rare items with long-term value (e.g., high-float knives or old tournament stickers)
Pro – “I know the skin economy inside-out”
You’ve got capital, connections, and collections. You might trade with other pros, do wholesale deals, or even run your community shop. At this level, it’s all about efficiency, scalability, and knowing where to get the best terms.
What to do:
Use white.market P2P CS2 Marketplace for professional-level tools, personalized offers, and wholesale deals
Optimize your skin listings with float filtering, smart pricing, and shop branding
Stay plugged into private groups and discords where rare skins and collectibles are traded
Watch updates across other platforms.
Focus on ROI, not just flash–it’s not about having the most expensive skin, it’s about knowing when to flip it.
Conclusion: Start Simple, Grow Smart
Getting into CS2 skin trading is easier than ever. There are tens of marketplaces and thousands of traders. Today it is much safer than it used to be, and the market is much bigger (meaning more opportunities for you).
But here’s the real truth: anyone can start, but getting good takes time, research, and consistency. The players making real money from skins aren’t just lucky – they study the market, learn from every trade, and keep improving over time.
No matter where you’re starting – Noob, Beginner, or Experienced – you’ve got a path forward. Stick with it, stay smart, and trade on platforms designed for real CS2 players like you.
The transition to Counter-Strike 2 has brought about significant changes in the professional scene, but Team Vitality has emerged as one of the most formidable forces in the new era. The French organization, now featuring a multinational roster, continues to set new standards for excellence in competitive play.
The vitality CS2 roster is a testament to the organization’s commitment to assembling world-class talent. Led by the legendary in-game leader Dan “apEX” Madesclaire, and featuring superstar Mathieu “ZywOo” Herbaut, widely considered one of the most gifted players in Counter-Strike history, the team has demonstrated remarkable adaptability during the transition period. The addition of Israeli prodigy Shahar “flameZ” Shushan has injected fresh energy into their gameplay.
The team’s evolution under the guidance of coach Danny “zonic” Sørensen has been nothing short of remarkable. The Danish mastermind has successfully integrated different playstyles and cultural approaches to create a cohesive unit that can adapt to any opposition. This versatility has become one of Vitality’s greatest strengths in the new game.
Vitality’s approach to CS2 has been methodical and innovative. The organization invested heavily in understanding the new game mechanics, particularly the sub-tick system and revised movement parameters. Their practice regime, focusing on individual skill development and team coordination, has yielded impressive results in tournament play.
The synergy between team members has reached new heights in CS2. The partnership between ZywOo and William “Magisk” Møller has become particularly potent, with both players showing exceptional ability to create space for each other and capitalize on opportunities. The addition of Lotan “Spinx” Giladi has provided the team with additional firepower and tactical flexibility.
The organization’s infrastructure has played a crucial role in its successful adaptation to CS2. Vitality’s training facility in Paris provides state-of-the-art equipment and support staff, including dedicated analysts, sports psychologists, and performance coaches. This comprehensive approach to player development has helped maintain their competitive edge during the transition period.
Tournament performances since the switch to CS2 have showcased Vitality’s dominance. Their tactical depth and individual skill have translated seamlessly into the new game, resulting in several notable tournament victories. The team’s ability to perform consistently at the highest level has solidified their position among the elite.
What sets Vitality apart in CS2 is its innovative approach to the game’s new features. They have developed unique strategies around enhanced smoke mechanics and revised economy systems. Their utility usage has become particularly sophisticated, often creating unprecedented opportunities for map control and execution.
The team’s communication and decision-making have evolved to match the faster pace of CS2. Under apEX’s leadership, Vitality has developed a dynamic calling system that allows for quick adaptations mid-round. This flexibility has proven crucial in high-pressure situations against top opponents.
Looking ahead, Vitality’s future in CS2 appears bright. The organization’s commitment to maintaining a balanced roster of experienced veterans and young talent ensures long-term sustainability. Their continued investment in support staff and training facilities demonstrates a dedication to remaining at the forefront of professional Counter-Strike.
The impact of Vitality extends beyond competitive play. Their players, especially ZywOo, have become role models for aspiring professionals worldwide. The organization’s content creation and community engagement have helped build a strong fanbase that transcends national boundaries.
In conclusion, Vitality’s journey in CS2 represents a masterclass in organizational excellence and competitive adaptation. Their ability to maintain high performance while evolving their gameplay speaks to the depth of talent and professionalism within the organization. As CS2 continues to develop, Vitality’s position as a leading force in professional Counter-Strike seems secure, built on a foundation of strategic insight, individual brilliance, and unwavering dedication to improvement.
Anthropic released Claude Haiku 4.5 on Wednesday, a smaller and significantly cheaper artificial intelligence model that matches the coding capabilities of systems that were considered cutting-edge just months ago, marking the latest salvo in an intensifying competition to dominate enterprise AI.
The model costs $1 per million input tokens and $5 per million output tokens — roughly one-third the price of Anthropic's mid-sized Sonnet 4 model released in May, while operating more than twice as fast. In certain tasks, particularly operating computers autonomously, Haiku 4.5 actually surpasses its more expensive predecessor.
"Haiku 4.5 is a clear leap in performance and is now largely as smart as Sonnet 4 while being significantly faster and one-third of the cost," an Anthropic spokesperson told VentureBeat, underscoring how rapidly AI capabilities are becoming commoditized as the technology matures.
The launch comes just two weeks after Anthropic released Claude Sonnet 4.5, which the company bills as the world's best coding model, and two months after introducing Opus 4.1. The breakneck pace of releases reflects mounting pressure from OpenAI, whose $500 billion valuation dwarfs Anthropic's $183 billion, and which has inked a series of multibillion-dollar infrastructure deals while expanding its product lineup.
How free access to advanced AI could reshape the enterprise market
In an unusual move that could reshape competitive dynamics in the AI market, Anthropic is making Haiku 4.5 available for all free users of its Claude.ai platform. The decision effectively democratizes access to what the company characterizes as "near-frontier-level intelligence" — capabilities that would have been available only in expensive, premium models months ago.
"The launch of Claude Haiku 4.5 means that near-frontier-level intelligence is available for free to all users through Claude.ai," the Anthropic spokesperson told VentureBeat. "It also offers significant advantages to our enterprise customers: Sonnet 4.5 can handle frontier planning while Haiku 4.5 powers sub-agents, enabling multi-agent systems that tackle complex refactors, migrations, and large features builds with speed and quality."
This multi-agent architecture signals a significant shift in how AI systems are deployed. Rather than relying on a single, monolithic model, enterprises can now orchestrate teams of specialized AI agents: a more sophisticated Sonnet 4.5 model breaking down complex problems and delegating subtasks to multiple Haiku 4.5 agents working in parallel. For software development teams, this could mean Sonnet 4.5 plans a major code refactoring while Haiku 4.5 agents simultaneously execute changes across dozens of files.
The approach mirrors how human organizations distribute work, and could prove particularly valuable for enterprises seeking to balance performance with cost efficiency — a critical consideration as AI deployment scales.
Inside Anthropic's path to $7 billion in annual revenue
The model launch coincides with revelations that Anthropic's business is experiencing explosive growth. The company's annual revenue run rate is approaching $7 billion this month, Anthropic told Reuters, up from more than $5 billion reported in August. Internal projections obtained by Reuters suggest the company is targeting between $20 billion and $26 billion in annualized revenue for 2026, representing growth of more than 200% to nearly 300%.
The company now serves more than 300,000 business customers, with enterprise products accounting for approximately 80% of revenue. Among Anthropic's most successful offerings is Claude Code, a code-generation tool that has reached nearly $1 billion in annualized revenue since launching earlier this year.
Those numbers come as artificial intelligence enters what many in the industry characterize as a critical inflection point. After two years of what Anthropic Chief Product Officer Mike Krieger recently described as "AI FOMO" — where companies adopted AI tools without clear success metrics — enterprises are now demanding measurable returns on investment.
"The best products can be grounded in some kind of success metric or evaluation," Krieger said on the "Superhuman AI" podcast. "I've seen that a lot in talking to companies that are deploying AI."
For enterprises evaluating AI tools, the calculus increasingly centers on concrete productivity gains. Google CEO Sundar Pichai claimed in June that AI had generated a 10% boost in engineering velocity at his company — though measuring such improvements across different roles and use cases remains challenging, as Krieger acknowledged.
Why AI safety testing matters more than ever for enterprise adoption
The attack targeted remarks by Jack Clark, Anthropic's British co-founder and head of policy, who had described being "deeply afraid" of AI's trajectory. Clark told Bloomberg he found Sacks' criticism "perplexing."
Anthropic addressed such concerns head-on in its release materials, emphasizing that Haiku 4.5 underwent extensive safety testing. The company classified the model as ASL-2 — its AI Safety Level 2 standard — compared to the more restrictive ASL-3 designation for the more powerful Sonnet 4.5 and Opus 4.1 models.
"Our teams have red-teamed and tested our agentic capabilities to the limits in order to assess whether it can be used to engage in harmful activity like generating misinformation or promoting fraudulent behavior like scams," the spokesperson told VentureBeat. "In our automated alignment assessment, it showed a statistically significantly lower overall rate of misaligned behaviors than both Claude Sonnet 4.5 and Claude Opus 4.1 — making it, by this metric, our safest model yet."
The company said its safety testing showed Haiku 4.5 poses only limited risks regarding the production of chemical, biological, radiological and nuclear weapons. Anthropic has also implemented classifiers designed to detect and filter prompt injection attacks, a common method for attempting to manipulate AI systems into producing harmful content.
The emphasis on safety reflects Anthropic's founding mission. The company was established in 2021 by former OpenAI executives, including siblings Dario and Daniela Amodei, who left amid concerns about OpenAI's direction following its partnership with Microsoft. Anthropic has positioned itself as taking a more cautious, research-oriented approach to AI development.
Benchmark results show Haiku 4.5 competing with larger, more expensive models
According to Anthropic's benchmarks, Haiku 4.5 performs competitively with or exceeds several larger models across multiple evaluation criteria. On SWE-bench Verified, a widely used test measuring AI systems' ability to solve real-world software engineering problems, Haiku 4.5 scored 73.3% — slightly ahead of Sonnet 4's 72.7% and close to GPT-5 Codex's 74.5%.
The model demonstrated particular strength in computer use tasks, achieving 50.7% on the OSWorld benchmark compared to Sonnet 4's 42.2%. This capability allows the AI to interact directly with computer interfaces — clicking buttons, filling forms, navigating applications — which could prove transformative for automating routine digital tasks.
In coding-specific benchmarks like Terminal-Bench, which tests AI agents' ability to complete complex software tasks using command-line tools, Haiku 4.5 scored 41.0%, trailing only Sonnet 4.5's 50.0% among Claude models.
The model maintains a 200,000-token context window for standard users, with developers accessing the Claude Developer Platform able to use a 1-million-token context window. That expanded capacity means the model can process extremely large codebases or documents in a single request — roughly equivalent to a 1,500-page book.
What three major AI model releases in two months says about the competition
When asked about the rapid succession of model releases, the Anthropic spokesperson emphasized the company's focus on execution rather than competitive positioning.
"We're focused on shipping the best possible products for our customers — and our shipping velocity speaks for itself," the spokesperson said. "What was state-of-the-art just five months ago is now faster, cheaper, and more accessible."
That velocity stands in contrast to the company's earlier, more measured release schedule. Anthropic appeared to have paused development of its Haiku line after releasing version 3.5 at the end of last year, leading some observers to speculate the company had deprioritized smaller models.
That rapid price-performance improvement validates a core promise of artificial intelligence: that capabilities will become dramatically cheaper over time as the technology matures and companies optimize their models. For enterprises, it suggests that today's budget constraints around AI deployment may ease considerably in coming years.
From customer service to code: Real-world applications for faster, cheaper AI
The practical applications of Haiku 4.5 span a wide range of enterprise functions, from customer service to financial analysis to software development. The model's combination of speed and intelligence makes it particularly suited for real-time, low-latency tasks like chatbot conversations and customer support interactions, where delays of even a few seconds can degrade user experience.
In financial services, the multi-agent architecture enabled by pairing Sonnet 4.5 with Haiku 4.5 could transform how firms monitor markets and manage risk. Anthropic envisions Haiku 4.5 monitoring thousands of data streams simultaneously — tracking regulatory changes, market signals and portfolio risks — while Sonnet 4.5 handles complex predictive modeling and strategic analysis.
For research organizations, the division of labor could compress timelines dramatically. Sonnet 4.5 might orchestrate a comprehensive analysis while multiple Haiku 4.5 agents parallelize literature reviews, data gathering and document synthesis across dozens of sources, potentially "compressing weeks of research into hours," according to Anthropic's use case descriptions.
Several companies have already integrated Haiku 4.5 and reported positive results. Guy Gur-Ari, co-founder of coding startup Augment, said the model "hit a sweet spot we didn't think was possible: near-frontier coding quality with blazing speed and cost efficiency." In Augment's internal testing, Haiku 4.5 achieved 90% of Sonnet 4.5's performance while matching much larger models.
Jeff Wang, CEO of Windsurf, another coding-focused startup, said Haiku 4.5 "is blurring the lines" on traditional trade-offs between speed, cost and quality. "It's a fast frontier model that keeps costs efficient and signals where this class of models is headed."
Jon Noronha, co-founder of presentation software company Gamma, reported that Haiku 4.5 "outperformed our current models on instruction-following for slide text generation, achieving 65% accuracy versus 44% from our premium tier model — that's a game-changer for our unit economics."
The price of progress: What plummeting AI costs mean for enterprise strategy
For enterprises evaluating AI strategies, Haiku 4.5 presents both opportunity and challenge. The opportunity lies in accessing sophisticated AI capabilities at dramatically lower costs, potentially making viable entire categories of applications that were previously too expensive to deploy at scale.
The challenge is keeping pace with a technology landscape that is evolving faster than most organizations can absorb. As Krieger noted in his recent podcast appearance, companies are moving beyond "AI FOMO" to demand concrete metrics and demonstrated value. But establishing those metrics and evaluation frameworks takes time — time that may be in short supply as competitors race ahead.
The shift from single-model deployments to multi-agent architectures also requires new ways of thinking about AI systems. Rather than viewing AI as a monolithic assistant, enterprises must learn to orchestrate multiple specialized agents, each optimized for particular tasks — more akin to managing a team than operating a tool.
The fundamental economics of AI are shifting with remarkable speed. Five months ago, Sonnet 4's capabilities commanded premium pricing and represented the cutting edge. Today, Haiku 4.5 delivers similar performance at a third of the cost. If that trajectory continues — and both Anthropic's release schedule and competitive pressure from OpenAI and Google suggest it will — the AI capabilities that seem remarkable today may be routine and inexpensive within a year.
For Anthropic, the challenge will be translating technical achievements into sustainable business growth while maintaining the safety-focused approach that differentiates it from competitors. The company's projected revenue growth to as much as $26 billion by 2026 suggests strong market traction, but achieving those targets will require continued innovation and successful execution across an increasingly complex product portfolio.
Whether enterprises will choose Claude over increasingly capable alternatives from OpenAI, Google and a growing field of competitors remains an open question. But Anthropic is making a clear bet: that the future of AI belongs not to whoever builds the single most powerful model, but to whoever can deliver the right intelligence, at the right speed, at the right price — and make it accessible to everyone.
In an industry where the promise of artificial intelligence has long outpaced reality, Anthropic is betting that delivering on that promise, faster and cheaper than anyone expected, will be enough to win. And with pricing dropping by two-thirds in just five months while performance holds steady, that promise is starting to look like reality.
The Dfinity Foundation on Wednesday released Caffeine, an artificial intelligence platform that allows users to build and deploy web applications through natural language conversation alone, bypassing traditional coding entirely. The system, which became publicly available today, represents a fundamental departure from existing AI coding assistants by building applications on a specialized decentralized infrastructure designed specifically for autonomous AI development.
Unlike GitHub Copilot, Cursor, or other "vibe coding" tools that help human developers write code faster, Caffeine positions itself as a complete replacement for technical teams. Users describe what they want in plain language, and an ensemble of AI models writes, deploys, and continually updates production-grade applications — with no human intervention in the codebase itself.
"In the future, you as a prospective app owner or service owner… will talk to AI. AI will give you what you want on a URL," said Dominic Williams, founder and chief scientist at the Dfinity Foundation, in an exclusive interview with VentureBeat. "You will use that, completely interact productively, and you'll just keep talking to AI to evolve what that does. The AI, or an ensemble of AIs, will be your tech team."
The platform has attracted significant early interest: more than 15,000 alpha users tested Caffeine before its public release, with daily active users representing 26% of those who received access codes — "early Facebook kind of levels," according to Williams. The foundation reports some users spending entire days building applications on the platform, forcing Dfinity to consider usage limits due to underlying AI infrastructure costs.
Why Caffeine's custom programming language guarantees your data won't disappear
Caffeine's most significant technical claim addresses a problem that has plagued AI-generated code: data loss during application updates. The platform builds applications using Motoko, a programming language developed by Dfinity specifically for AI use, which provides mathematical guarantees that upgrades cannot accidentally delete user data.
"When AI is updating apps and services in production, a mistake cannot lose data. That's a guarantee," Williams said. "It's not like there are some safeguards to try and stop it losing data. This language framework gives it rails that guarantee if an upgrade, an update to its app's underlying logic, would cause data loss, the upgrade fails and the AI just tries again."
This addresses what Williams characterizes as critical failures in competing platforms. User forums for tools like Lovable and Replit, he notes, frequently report three major problems: applications that become irreparably broken as complexity increases, security vulnerabilities that allow unauthorized access, and mysterious data loss during updates.
Traditional tech stacks evolved to meet human developer needs — familiarity with SQL databases, preference for known programming languages, existing skill investments. "That's how the traditional tech stacks evolved. It's really evolved to meet human needs," Williams explained. "But in the future, it's going to be different. You're not going to care how the AI did it. Instead, for you, AI is the tech stack."
Caffeine's architecture reflects this philosophy. Applications run entirely on the Internet Computer Protocol (ICP), a blockchain-based network that Dfinity launched in May 2021 after raising over $100 million from investors including Andreessen Horowitz and Polychain Capital. The ICP uses what Dfinity calls "chain-key cryptography" to create what Williams describes as "tamper-proof" code — applications that are mathematically guaranteed to execute their written logic without interference from traditional cyberattacks.
"The code can't be affected by ransomware, so you don't have to worry about malware in the same way you do," Williams said. "Configuration errors don't result in traditional cyber attacks. That passive traditional cyber attacks isn't something you need to worry about."
How 'orthogonal persistence' lets AI build apps without managing databases
At the heart of Caffeine's technical approach is a concept called "orthogonal persistence," which fundamentally reimagines how applications store and manage data. In traditional development, programmers must write extensive code to move data between application logic and separate database systems — marshaling data in and out of SQL servers, managing connections, handling synchronization.
Motoko eliminates this entirely. Williams demonstrated with a simple example: defining a blog post data type and declaring a variable to store an array of posts requires just two lines of code. "This declaration is all that's necessary to have the blog maintain its list of posts," he explained during a presentation on the technology. "Compare that to traditional IT where in order to persist the blog posts, you'd have to marshal them in and out of a database server. This is quite literally orders of magnitude more simple."
This abstraction allows AI to work at a higher conceptual level, focusing on application logic rather than infrastructure plumbing. "Logic and data are kind of the same," Williams said. "This is one of the things that enables AI to build far more complicated functionality than it could otherwise do."
The system also employs what Dfinity calls "loss-safe data migration." When AI needs to modify an application's data structure — adding a "likes" field to blog posts, for example — it must write migration logic in two passes. The framework automatically verifies that the transformation won't result in data loss, refusing to compile or deploy code that could delete information unless explicitly instructed.
From million-dollar SaaS contracts to conversational app building in minutes
Williams positions Caffeine as particularly transformative for enterprise IT, where he claims costs could fall to "1% of what they were before" while time-to-market shrinks to similar fractions. The platform targets a spectrum from individual creators to large corporations, all of whom currently face either expensive development teams or constraining low-code templates.
"A corporation or government department might want to create a corporate portal or CRM, ERP functionality," Williams said, referring to customer relationship management and enterprise resource planning systems. "They will otherwise have to obtain this by signing up for some incredibly expensive SaaS service where they become locked in, their data gets stuck, and they still have to spend a lot of money on consultants customizing the functionality."
Applications built through Caffeine are owned entirely by their creators and cannot be shut down by centralized parties — a consequence of running on the decentralized Internet Computer network rather than traditional cloud providers like Amazon Web Services. "When someone says built on the internet computer, it actually means built on the internet computer," Williams emphasized, contrasting this with blockchain projects that merely host tokens while running actual applications on centralized infrastructure.
The platform demonstrated this versatility during a July 2025 hackathon in San Francisco, where participants created applications ranging from a "Will Maker" tool for generating legal documents, to "Blue Lens," a voice-AI water quality monitoring system, to "Road Patrol," a gamified community reporting app for infrastructure problems. Critically, many of these came from non-technical participants with no coding background.
"I'm from a non-technical background, I'm actually a quality assurance professional," said the creator of Blue Lens in a video testimonial. "Through Caffeine I can build something really intuitive and next-gen to the public." The application integrated multiple external services — Eleven Labs for voice AI, real-time government water data through retrieval-augmented generation, and Midjourney-generated visual assets — all coordinated through conversational prompts.
What separates Caffeine from GitHub Copilot, Cursor, and the 'vibe coding' wave
Caffeine enters a crowded market of AI-assisted development tools, but Williams argues the competition isn't truly comparable. GitHub Copilot, Cursor, and similar tools serve human developers working with traditional technology stacks. Platforms like Replit and Lovable occupy a middle ground, offering "vibe coding" that mixes AI generation with human editing.
"If you're a Node.js developer, you know you're working with the traditional stack, and you might want to do your coding with Copilot or using Claude or using Cursor," Williams said. "That's a very different thing to what Caffeine is offering. There'll always be cases where you probably wouldn't want to hand over the logic of the control system for a new nuclear missile silo to AI. But there's going to be these holdout areas, right? And there's all the legacy stuff that has to be maintained."
The key distinction, according to Williams, lies in production readiness. Existing AI coding tools excel at rapid prototyping but stumble when applications grow complex or require guaranteed reliability. Reddit forums for these platforms document users hitting insurmountable walls where applications break irreparably, or where AI-generated code introduces security vulnerabilities.
"As the demands and the requirements become more complicated, eventually you can hit a limit, and when you hit that limit, not only can you not go any further, but sometimes your app will get broken and there's no way of going back to where you were before," Williams said. "That can't happen with productive apps, and it also can't be the case that you're getting hacked and losing data, because once you go hands-free, if you like, and there's no tech team, there's no technical people involved, who's going to run the backups and restore your app?"
The Internet Computer's architecture addresses this through Byzantine fault tolerance — even if attackers gain physical control over some network hardware, they cannot corrupt applications or their data. "This is the beginning of a compute revolution and it's also the perfect platform for AI to build on," Williams said.
Inside the vision: A web that programs itself through natural language
Dfinity frames Caffeine within a broader vision it calls the "self-writing internet," where the web literally programs itself through natural language interaction. This represents what Williams describes as a "seismic shift coming to tech" — from human developers selecting technology stacks based on their existing skills, to AI selecting optimal implementations invisible to users.
"You don't care about whether some human being has learned all of the different platforms and Amazon Web Services or something like that. You don't care about that. You just care: Is it secure? Do you get security guarantees? Is it resilient? What's the level of resilience?" Williams said. "Those are the new parameters."
The platform demonstrated this during live demonstrations, including at the World Computer Summit 2025 in Zurich. Williams created a talent recruitment application from scratch in under two minutes, then modified it in real-time while the application ran with users already interacting with it. "You will continue talking to the AI and just keep on refreshing the URL to see the changes," he explained.
This capability extends to complex scenarios. During demonstrations, Williams showed building a tennis lesson booking system, an e-commerce platform, and an event registration system — all simultaneously, working on multiple applications in parallel. "We predict that as people get very proficient with Caffeine, they could be working on even 10 apps in parallel," he said.
The system writes substantial code: a simple personal blog generated 700 lines of code in a couple of minutes. More complex applications can involve thousands of lines across frontend and backend components, all abstracted away from the user who only describes desired functionality.
The economics of cloning: How Caffeine's app market challenges traditional stores
Caffeine's economic model differs fundamentally from traditional software-as-a-service platforms. Applications run on the Internet Computer Protocol, which uses a "reverse gas model" where developers pay for computation rather than users paying transaction fees. The platform includes an integrated App Market where creators can publish applications for others to clone and adapt — creating what Dfinity envisions as a new economic ecosystem.
"App stores today obviously operate on gatekeeping," said Pierre Samaties, chief business officer at Dfinity, during the World Computer Summit. "That's going to erode." Rather than purchasing applications, users can clone them and modify them for their own purposes — fundamentally different from Apple's App Store or Google Play models.
Williams acknowledges that Caffeine itself currently runs on centralized infrastructure, despite building applications on the decentralized Internet Computer. "Caffeine itself actually is centralized. It uses aspects of the Internet Computer. We want Caffeine itself to run on the Internet Computer in the future, but it's not there now," he said. The platform leverages commercially available foundation models from companies like Anthropic, whose Claude Sonnet model powers much of Caffeine's backend logic.
This pragmatic approach reflects Dfinity's strategy of using best-in-class AI models while focusing its own development on the specialized infrastructure and programming language designed for AI use. "These content models have been developed by companies with enormous budgets, absolutely enormous budgets," Williams said. "I don't think in the near future we'll run AI on the Internet Computer for that reason, unless there's a special case."
A decade in the making: From Ethereum roots to the self-writing internet
The Dfinity Foundation has pursued this vision since Williams began researching decentralized networks in late 2013. After involvement with Ethereum before its 2015 launch, Williams became fascinated with the concept of a "world computer"—a public blockchain network that could host not just tokens but entire applications and services.
"By 2015 I was talking about network-focused drivers, Dfinity back then, and that could really operate as an alternative tech stack, and eventually host even things like social networks and massive enterprise systems," Williams said. The foundation launched the Internet Computer Protocol in May 2021, initially focusing on Web3 developers. Despite not being among the highest-valued blockchain projects, ICP consistently ranks in the top 10 for developer numbers.
The pivot to AI-driven development came from recognizing that "in the future, the tech stack will be AI," according to Williams. This realization led to Caffeine's development, announced on Dfinity's public roadmap in March 2025 and demonstrated at the World Computer Summit in June 2025.
One successful example of the Dfinity vision running in production is OpenChat, a messaging application that runs entirely on the Internet Computer and is governed by a decentralized autonomous organization (DAO) with tens of thousands of participants voting on source code updates through algorithmic governance. "The community is actually controlling the source code updates," Williams explained. "Developers propose updates, community reads the updates, and if the community is happy, OpenChat updates itself."
The skeptics weigh in: Crypto baggage and real-world testing ahead
The platform faces several challenges. Dfinity's crypto industry roots may create perception problems in enterprise markets, Williams acknowledges. "The Web3 industry's reputation is a bit tarnished and probably rightfully so," he said during the World Computer Summit. "Now people can, for themselves, experience what a decentralized network is. We're going to see self-writing take over the enterprise space because the speed and efficiency are just incredible."
The foundation's history includes controversy: ICP's token launched in 2021 at over $100 per token with an all-time high around $700, then crashed below $3 in 2023 before recovering. The project has faced legal challenges, including class action lawsuits alleging misleading investors, and Dfinity filed defamation claims against industry critics.
Technical limitations also remain. Caffeine cannot yet compile React front-ends on the Internet Computer itself, requiring some off-chain processing. Complex integrations with traditional systems — payment processing through Stripe, for example — still require centralized components. "Your app is running end-to-end on the Internet Computer, then when it needs to actually accept payment, it's going to hand over to your Stripe account," Williams explained.
The platform's claims about data loss prevention and security guarantees, while technically grounded in the Motoko language design and Internet Computer architecture, remain to be tested at scale with diverse real-world applications. The 26% daily active user rate from alpha testing is impressive but comes from a self-selected group of early adopters.
When five billion smartphone users become developers
Williams rejects concerns that AI-driven development will eliminate software engineering jobs, arguing instead for market expansion. "The self-writing internet empowers eight billion non-technical people," he said. "Some of these people will enter roles in tech, becoming prompt engineers, tech entrepreneurs, or helping run online communities. Humanity will create millions of new custom apps and services, and a subset of those will require professional human assistance."
During his World Computer Summit demonstration, Williams was explicit about the scale of transformation Dfinity envisions. "Today there are about 35,000 Web3 engineers in the world. Worldwide there are about 15 million full-stack engineers," he said. "But tomorrow with the self-writing internet, everyone will be a builder. Today there are already about five billion people with internet-connected smartphones and they'll all be able to use Caffeine."
The hackathon results suggest this isn't pure hyperbole. A dentist built "Dental Tracks" to help patients manage their dental records. A transportation industry professional created "Road Patrol" for gamified infrastructure reporting. A frustrated knitting student built "Skill Sprout," a garden-themed app for learning new hobbies, complete with material checklists and step-by-step skill breakdowns—all without writing a single line of code.
"I was learning to knit. I got irritated because I had the wrong materials," the creator explained in a video interview. "I don't know how to do the stitches, so I have to individually search, and it's really intimidating when you're trying to learn something you don't—you don't even know what you don't know."
Whether Caffeine succeeds depends on factors still unknown: how production applications perform under real-world stress, whether the Internet Computer scales to millions of applications, whether enterprises can overcome their skepticism of blockchain-adjacent technology. But if Williams is right about the fundamental shift — that AI will be the tech stack, not just a tool for human developers — then someone will build what Caffeine promises.
The question isn't whether the future looks like this. It's who gets there first, and whether they can do it without losing everyone's data along the way.
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