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The Rise of Recursive Self-Improvement in AIThe word "recursion" is the latest buzzword in AI circles. Two separate startups have taken on the name, and many more have started referencing recursive self-improvement (RSI) in their roadmaps. Like AGI before it, RSI has become a three-letter byword for a cataclysmic AI takeoff – even if there's still a little disagreement about what it exactly means.In basic terms, RSI refers to an AI system that can continuously upgrade itself. Once AI systems can manage the upgrade cycle better than humans, the process can become a closed loop, limited only by the compute power they can access, and humans are no longer necessary or even helpful.Scary or not, that's a vision that a lot of AI labs are eager to chase.Key Players Pursuing Recursive SystemsEarlier this month, well-known AI researcher Richard Socher launched the aptly named Recursive Superintelligence with RSI as an explicit goal. "Our main focus is to build truly recursive, self-improving superintelligence at scale," Socher told TechCrunch at launch, "which means that the entire process of ideation, implementation, and validation of research ideas would be automatic."A number of other prominent researchers are already chasing that same goal, hoping for a breakthrough that will make recursive self-improvement possible.One of the most prominent is Andrej Karpathy, a legendary figure from Tesla and OpenAI, who is using agent swarms to train LLMs on simple tasks for a project he calls Auto-Research. Karpathy has been unusually open about the project, tweeting about milestones regularly and making the building blocks available through a public GitHub repo. So far, the work has mostly been confined to making minor improvements on a GPT-2 scale model — as Karpathy noted in March, "It's not novel, ground-breaking 'research' (yet)" — but it's been enough to convince lots of other researchers to follow the RSI dream. And with Karpathy now working on pre-training at Anthropic, he will have plenty of opportunity to apply the idea at a larger scale.Adaption — founded by Cohere and Google alum Sara Hooker — recently launched a similar tool called AutoScientist in an effort to automate frontier training. Like Karpathy's auto-researchers, the system trains agents to make incremental improvements — but for Adaption, the goal is to make it easier to train a full-scale frontier model. If those same researchers start to push the frontier forward, the system could quickly spiral into something very much like RSI.Disarray founder Doris Xin drew more specific RSI interest when her self-trained machine learning agent took home 28 medals in a recent Kaggle competition, beating out many human-trained agents. As she sees it, the major challenge is reliability."I would argue, given infinite compute and infinite time horizon, we are already there," Xin told me. "I want to make an argument that this is not a creative endeavor, really. It's just a lot of meat-and-potatoes engineering."The Current State of Self-Improving AIThere's also plenty of evidence that the AI industry isn't very close to recursive systems in any meaningful way — and is still grappling with talking to a wary public about its progress. So Google CEO Sundar Pichai basically admitted in a recent podcast interview."It's a continuum, and we are all definitely making progress," Pichai said. "But in the way people describe RSI, that would represent a next level of acceleration and would have a lot of implications, but we aren't quite there yet."But the continuum includes an awful lot of self-improving AI systems.In January, one of Anthropic's lead programmers for Claude Code estimated that "close to 100%" of his team's code was written by the tool — a frank admission that Claude Code was literally writing itself.Just because engineers are using an AI tool doesn't mean the tool can replace them — but Anthropic seems to be getting close to replacing engineers too. In a recent survey tied to the Mythos preview, five out of 18 Anthropic engineers believed that, with harness improvements, this version of Mythos could soon substitute for an L4 engineer — a midlevel programmer who can take on involved projects without supervision.Still, there were some of the same weaknesses you might expect."Some of Claude's major reported weaknesses compared to an L4 include: self-managing week-long ambiguous tasks, understanding org priorities, taste, verification, instruction-following, and epistemics," the report reads.In other words, its weaknesses are everything involved with self-direction, which is the cornerstone for RSI. But sure, for everything else, Claude is ready to step right in.Expert Perspectives on RSI TimelinesJust like the AGI term before it, the AI industry also can't tell us how far away it is from showcasing a meaningful recursive system. When Georgetown's Center for Security and Emerging Technology assembled a group of experts to study RSI last year, the group found a major split in assessments — some expecting an imminent "superintelligence" style explosion while others expected slower progress and an eventual plateau. But all agreed that recursion made the future especially difficult to predict.Helen Toner, director of CSET and a former board member at OpenAI, told TechCrunch that simply using AI tools to do AI research isn't enough to qualify as RSI. "They're just using AI for as much as they can," Toner told TechCrunch. "And I think that is different from the classic definition of RSI, which is really that there are no humans needed."Toner pointed to a recent post by METR's Ajeya Cotra, which distinguishes different milestones on the path to the AI research takeover. One step, which Cotra calls "adequacy," would come when the system can still perform research after all humans are removed — even if the resulting research isn't as valuable or efficient. "Parity" comes when an AI-only system is as good at research as a human-only system. "Supremacy," the final stage, comes when an AI-only system outperforms a collaborative system between humans and AI.Ultimately, Cotra concludes that AI is very close to the adequacy threshold of being able to produce some work on its own — similar to the incremental changes made by Karpathy's Auto-Research system. "I wouldn't be totally shocked if you told me this milestone had already passed, and I expect it to happen in the next couple years," Cotra wrote.She was less clear on when parity will come, but once it does, she thinks it would "massively accelerate the pace of AI progress, leading to AI research supremacy within another year."The Challenges Ahead for Recursive AIWith so much of AI built on scaling laws, there's a strong tendency to think RSI will follow the same curve. Toner thinks that many of those pursuing AI research and development via RSI "think of it as a pretty smooth ladder, where you can just keep scaling up."But even if AI researchers are able to make incremental improvements like Karpathy's auto-researchers, there will be larger challenges in handing off the whole process of research. Toner put it in terms of the history of computing, which has seen human beings handing off more and more of the process while still directing things from the top."We went from machine languages to assembly language and compiled languages; you're getting further and further from the guts of the computer," Toner said. "But the human is still, in some intuitive sense, running the show."Moving beyond that paradigm will take significant challenges, both in engineering and alignment. But even with the massive investments happening, there's no infinite compute available — and the basic trade-off between human labor and machine intelligence will be hard to overcome.The Future of Recursive Self-ImprovementAs for a total recursive AI system of apocalyptic visions? The only thing researchers essentially agree on is that, like AGI, it's not here yet.

Visa has disclosed an undisclosed investment in AI coding platform Replit, aiming to embed its payment suite directly into the developer environment so that both developers and AI agents can accept payments without leaving the platform. Strategic Investment and Joint Exploration of AI‑Powered Payments The two companies are testing how Visa Intelligent Commerce and the Trusted Agent Protocol can be woven into Replit’s workflow. More than 1,000 Visa employees already use Replit for prototyping, and the collaboration remains in an exploratory stage with no formal product announcements. Valuation Surge and Funding Milestones Highlight Replit’s Growth September 2025: Replit reached a $3 billion valuation. March 2026: Raised $400 million in a Series D led by Georgian Partners, pushing valuation to $9 billion. Enterprise self‑serve contracts now allow deals up to $200,000 without sales interaction. Customer churn is described as "very, very low" with net retention hitting 300 % in some cases. Implications for the Emerging Agentic Payments Ecosystem The move underscores a broader race to build infrastructure for "agentic payments," where AI agents transact on behalf of users. Competitors such as Robinhood (agent‑driven trading) and Google (shopping agents) are pursuing similar capabilities, suggesting the market will soon demand secure, verifiable AI‑mediated transactions. Future Trajectory: From Prototype to Mainstream Agentic Commerce If the exploratory projects mature, Replit could become a one‑stop shop for developers to build, host, and monetize AI agents, accelerating adoption of Visa’s Trusted Agent Protocol. Analysts anticipate that as enterprise adoption grows and churn remains low, the partnership may evolve into a commercial product suite within the next 12‑18 months, positioning Visa and Replit at the forefront of the next wave of AI‑driven commerce.

The Lead: Vertu's AI-Powered Foldable Targets Executive Market Luxury smartphone brand Vertu has unveiled the Alphafold, a foldable phone powered by an AI agent designed specifically for executives managing business operations on the move. The device represents Vertu's latest attempt to reinvent itself for the AI era, combining luxury materials with enterprise-focused AI capabilities to target the high-end business market. The Event Details: Luxury Meets AI: The Alphafold's Enterprise Capabilities The Alphafold features Hermes Agent, built on the open-source Hermes project by Nous Research, which can connect to enterprise systems like ERP and CRM. The AI agent coordinates tasks such as approvals, scheduling, sales tracking, travel planning, and operational reporting through natural-language prompts. The device can route requests across multiple AI models including OpenAI's GPT, Anthropic's Claude, Google's Gemini, and selected open-source models, while integrating with more than 80 apps and dozens of native phone functions for cross-platform workflows. Vertu has emphasized the device's privacy-focused architecture featuring a proprietary A5 security chip designed to isolate authentication keys, biometric credentials, and sensitive enterprise information from the main operating system. The company states that commercially sensitive data can be processed locally on the device, while prompts sent to external AI models are redacted or tokenized before leaving the phone. The Data Analysis: Premium Pricing Strategy in the Smartphone Market The Alphafold starts at $6,880 for the calfskin version, with higher-end models featuring bespoke finishes including alligator leather, 18K gold, and natural diamond accents. Vertu's highest-end standard model is currently priced at $46,800, with further customization options available. This pricing strategy positions Vertu firmly in the ultra-premium segment of the smartphone market. While foldable smartphones remain a niche segment globally—with IDC data showing approximately 20 million units shipped in 2025, accounting for less than 2% of total smartphone shipments—Vertu is betting that the combination of luxury materials and AI capabilities will justify its premium pricing. The average price of foldable smartphones was about $1,300 last year, roughly three times the price of non-foldable smartphones. The Impact Analysis: How AI is Transforming Executive Productivity Vertu CEO Molly Ma highlighted that existing AI features on smartphones from major manufacturers remain focused largely on consumer tools such as image editing and voice assistance, leaving room for more advanced AI-agent workflows tied to enterprise systems. The Alphafold aims to address this gap by providing executives with a device that can seamlessly integrate with their business operations and workflows. The device's larger foldable display (8.05-inch inner screen and 6.53-inch outer screen) is better suited for multitasking and productivity-oriented experiences, according to Kiranjeet Kaur, associate research director for mobile phones research at IDC. However, she noted that enterprise AI adoption on smartphones still lags behind computers, with most enterprise smartphone decisions continuing to be driven by ecosystem integration and device management support rather than AI capabilities. The Prediction: The Future of Luxury AI-Powered Mobile Devices The Alphafold represents Vertu's significant step forward from its previous AI-focused device, Agent Q, with Ma noting that AI-agent technology has matured rapidly over the past year, with improvements in memory, automation, and app integration. While the company has not yet undergone third-party security audits for the device, it has confirmed that independent audits and certification remain on its security roadmap. As the first 115-unit batch of Vertu's Alphafold begins shipping across major markets including the U.S., the device will serve as a test case for whether there's a market for luxury smartphones with enterprise AI capabilities. If successful, Vertu's approach could inspire other manufacturers to develop similar devices targeting the executive market, potentially accelerating the integration of AI agents into mobile workflows.

The Rise of AI-Powered Payroll Remote, a seven-year-old Amsterdam-based payroll service provider, has recently surpassed $300 million in annual recurring revenue and become cash-flow positive. However, the company's true achievement lies in its 50% increase in revenue per employee after adopting AI at every level of the organization. AI Adoption Across the Organization According to CEO Job van der Voort, the key to Remote's efficiency gains is AI adoption well beyond the CEO's office or engineering department. Employees across all functions have been launching apps in Remote Labs, an internal marketplace built on the company's own technology. The Data Behind the Growth Annual recurring revenue: over $300 million Revenue growth per employee: 50% Core payroll business growth: over 300% year over year Number of companies served: tens of thousands The Impact of AI on Remote's Business Remote's adoption of AI has not only increased revenue per employee but also improved the company's overall efficiency. The company has reduced its hiring plans and is instead focusing on upskilling its existing employees to use AI tools. The Future of AI in Payroll Remote is now opening up its AI capabilities to clients, allowing them to create custom workflows. The company has also launched Remote MCP, an interface based on the Model Context Protocol, which grants AI agents and external platforms direct access to payroll and compliance data. The Prediction As AI continues to transform the payroll industry, Remote is well-positioned to lead the charge. With its focus on AI adoption and innovation, the company is poised for continued growth and success in the future.

The Lead: NAACP's Strategic Boycott CallSix years after the nation underwent a so-called "racial reckoning", Black America is under comprehensive assault from the country's highest elected, judicial, and legislative branches. In response, the National Association for the Advancement of Colored People (NAACP) has turned to sports, calling for Black athletes to boycott public universities in the Southeastern Conference (SEC), arguably the most powerful football conference in the country and certainly its greatest incubator of Black athletic talent.The Political Landscape: Assault on Black AmericaThe assault comes from multiple fronts: the president has codified into policy the belief that white people are the true victims of racial discrimination; the supreme court has gutted the Voting Rights Act of 1965; and state and federal legislative branches are implementing massive southern redistricting efforts that threaten to erase much of the Black political representation won over the past 60 years. These moves mirror historical patterns of segregation and disenfranchisement.The Athletic Response: Leveraging Cultural InfluenceThe NAACP is betting that Black Americans will recognize the urgency of the moment and realize their power. Black people represent 14% of the population but are more than 14% of American culture, with Black athletes being the most successful, influential, and visible Black employees in the country. A sustained, coordinated movement of Black athletes against hostile states could have profound effects on both sports and politics.The Historical Context: Athletes as Change AgentsBlack athletes have a history of effecting change. In 2015, University of Missouri football players' boycott threat led to the resignation of the school's president and system chancellor. In the 1960s, the exodus of Black high school talent from the south forced southern universities to integrate. Today's athletes have even more power through NIL (name, image, and likeness) deals and the transfer portal, which allows them to change schools without sitting out a year.The Media Silence: Suppressing Black VoicesOver the last half-decade, sports media has willingly eliminated the Black political voice, reducing athletes to "neutered laborers" who entertain predominantly white audiences. While there are Black faces on sports television addressing "representation," they often lack depth and reportage on major national stories. ESPN's minimal coverage of the NAACP boycott exemplifies this pattern of silencing Black perspectives.The Power Dynamics: Economic Influence and ResponsibilityThe NAACP action reminds Black athletes of their power and their connection to the future of Black America. As an economic bloc, they can shift the fortunes of institutions they inhabit. After largely being silent politically since the 2020 Floyd protests, a new generation is being asked to recognize their place in the Black athletic and civil rights heritage that "laid down its life for the comforts that are now being erased." The question remains whether they will choose to use their influence beyond the playing field.

The LeadClickHouse has achieved significant financial growth, crossing $250 million in annualized revenue run rate, which represents a tripling of its business from the previous year. The database company is now positioning itself for an initial public offering within the next few years, signaling confidence in its market position and technology.Revenue Milestone and Growth TrajectoryAccording to Yury Izrailevsky, co-founder and president of product and technology at ClickHouse, the company has successfully reached a $250 million annualized revenue run rate, marking substantial growth from the previous year. Izrailevsky has indicated that the company expects this figure to reach the high-nine digits by the end of the current year, demonstrating an aggressive growth trajectory.Financial Valuation and Market PositionIn January, ClickHouse was valued at $15 billion following a $400 million Series D funding round led by Dragoneer Investment Group. This valuation implies a steep multiple of over 60x annualized revenue, indicating strong investor confidence in the company's technology and market potential. The company has attracted over 4,000 customers, including major tech firms like Anthropic, Meta, Capital One, and Decagon.Strategic Moves Toward Public MarketsThe fast revenue growth and premium valuation position the less-than-five-year-old company for an IPO within the next few years. Last fall, ClickHouse hired Jimmy Sexton, who previously ran investor relations at Snowflake (one of ClickHouse's main competitors), as chief financial officer. This hiring is often viewed as a clear signal that a company is preparing for public markets. Additionally, the company has already acquired six startups, including Langfuse, which helps developers track and evaluate AI agent performance.Future Outlook and Expansion StrategyClickHouse plans to remain acquisitive, looking to scoop up "relatively young, but showing very promising technology" startups, typically open source, that complement its core product suite. The company's open source database is designed to process the massive datasets required by AI agents, and it generates revenue by selling managed cloud services. Izrailevsky claimed that this commercial offering ultimately costs clients less than self-managing the open source version. As the IPO window is expected to be flung wide open by SpaceX's historic June debut, followed by highly anticipated listings from OpenAI and Anthropic later this year, ClickHouse joins a small but growing list of tech startups signaling plans to go public.

The Lead: ClickHouse's Meteoric RiseDatabase provider ClickHouse has crossed $250 million in annualized revenue run rate, tripling its business from last year, signaling strong momentum as it prepares for a potential IPO. The company, which spun out from Russian tech giant Yandex in 2021, is positioning itself for public markets within the next few years.The Event Details: Revenue Milestone and Growth TrajectoryAccording to Yury Izrailevsky, co-founder and president of product and technology at ClickHouse, the company has achieved significant financial growth with its annualized revenue reaching $250 million. Izrailevsky expects this figure to reach the high nine digits by the end of the year. The company's open-source database is specifically designed to process the massive datasets required by AI agents, with revenue generated through managed cloud services.The Data Analysis: Premium Valuation and Market PositionClickHouse was valued at $15 billion in January following a $400 million Series D funding round led by Dragoneer Investment Group. This valuation implies a steep forward multiple of over 60 times annualized revenue, indicating strong investor confidence in the company's growth prospects. The company has attracted over 4,000 customers, including major players like Anthropic, Meta, Capital One, and Decagon.The Impact Analysis: Shifting Database Landscape for AIClickHouse's rapid growth reflects the increasing demand for specialized database solutions that can handle AI workloads. The company's strategy of combining open-source technology with premium managed services has proven effective, with Izrailevsky noting that their commercial offering ultimately costs clients less than self-managing the open-source version. This approach has positioned ClickHouse as a key player in the database market, particularly for AI applications.The Prediction: IPO Path and Future ExpansionWith its strong revenue growth and premium valuation, ClickHouse is well-positioned for an IPO within the next few years. The company has already taken steps toward public markets by hiring Jimmy Sexton, former head of investor relations at Snowflake, as chief financial officer. Additionally, ClickHouse has acquired six startups, including Langfuse, and plans to remain acquisitive, targeting "relatively young, but showing very promising technology" startups that complement its core product suite. The company joins a growing list of tech startups preparing for public offerings, potentially benefiting from an expected IPO window opened by SpaceX's historic debut and anticipated listings from OpenAI and Anthropic.

The Lead A phenomenon dubbed "AI psychosis" is reportedly affecting tech executives, particularly CEOs, who are overestimating artificial intelligence capabilities while simultaneously implementing mass layoffs. This disconnect between perception and reality is creating organizational chaos in the tech industry. The CEO AI Delusion Box founder Aaron Levie has suggested that CEOs are uniquely prone to "AI psychosis" because they're sufficiently distant from the implementation details of AI systems. When executives "play with AI" by developing prototypes or generating contracts, they often make the leap to believing AI agents can fully handle complex work without understanding the limitations. Unlike their technical teams, CEOs aren't responsible for reviewing code, discovering bugs, or training AI models on company-specific requirements. This lack of firsthand experience with AI's limitations doesn't stop them from making decisions based on overoptimistic assessments of AI capabilities. The Layoff Numbers In the first five months of 2026 alone, the tech industry has already seen 115,430 people fired from 152 tech companies. This nearly matches the 124,636 people let go by 275 companies throughout all of 2025, according to industry tracker Layoffs.fyi. The majority of these layoffs have been attributed to AI, though many argue that companies are engaging in "AI washing" - crediting AI productivity gains when other business decisions are really driving the cuts. The ClickUp Experiment Zeb Evans, CEO of project management software startup ClickUp, proudly declared on X that he had laid off almost a quarter of his employees (22%) after implementing approximately 3,000 AI agents for internal work. Evans insisted this wasn't a cost-cutting measure but rather an attempt to create what he calls a "100x org" composed of people who run and review AI agents' work. The Productivity Paradox Research on AI and productivity presents a complex picture. A meta-analysis published in UC Berkeley's California Management Review found "no robust relationship between AI adoption and aggregate productivity gain." Meanwhile, research from the National Bureau of Economic Research concluded that while AI adoption does improve productivity, there's a "productivity paradox" in which perceived gains exceed measured improvements. MIT researchers studying thousands of AI agents found they aren't yet producing human-quality work in many cases. They predict that at the current rate of improvement, large language models will "be able to complete most text-related tasks with success rates of, on average, 80%–95% by 2029 at a minimally sufficient quality level," with additional time needed to outperform humans. The Executive Bottleneck Research published in the Harvard Business Review suggests that when everyone in an organization uses AI to produce more output, the bottleneck simply shifts to executives. Their work awaits authorization of all the content being generated by AI-empowered employees. If everyone is empowered to act, the system risks becoming overwhelmed, as evidenced by OpenAI's experience last year. As Levie advises, CEOs should use AI extensively to understand both its capabilities and limitations. However, with the current trend of mass layoffs and organizational restructuring based on overoptimistic AI assessments, the tech industry may face continued chaos until this balance is achieved.

The Architecture of Agentic FinanceRobinhood is fundamentally redefining the user experience by launching support for AI agentic trading and a new agentic credit card. This initiative allows users to create separate accounts for their AI agents, connecting them to a dedicated wallet. While these agents can analyze portfolios and suggest strategies, they are restricted to executing trades using only pre-loaded balances. The platform ensures safety through a mandatory approval workflow for trade previews and employs a dedicated fraud detection team to review suspicious activities.Protocol Integration: Agents connect via the Model Context Protocol (MCP) to analyze concentration risk and sector exposure.Control Mechanism: Users receive real-time notifications and can monitor all agent activities within the app.Current Scope: The beta feature is currently limited to stock trading.Expanding the Agentic EcosystemThe rollout of these tools represents a significant expansion of Robinhood's capabilities. The company is not only enabling autonomous trading but also introducing a virtual credit card for AI agents to facilitate payments. Currently, this card is exclusive to Robinhood Gold Card holders, who can link their accounts to set monthly limits and approval preferences. The platform has also outlined a clear roadmap for future asset classes.Upcoming Assets: Support for options, crypto, event contracts, futures, and prediction markets is planned for the near future.Platinum Access: The Robinhood Platinum Card will receive similar agentic card features later this year.Redefining the Role of the TraderThis development marks a pivotal shift in the financial services industry, moving from active manual trading to agentic finance. By adopting the Model Context Protocol (MCP), Robinhood allows users to integrate third-party Large Language Models (LLMs) directly into their investment workflow. This reduces the friction of manual data analysis and positions Robinhood as a central node in the growing network of autonomous financial agents.The Future of Autonomous FinanceAs major players like Stripe, Amazon, and Google race to build similar capabilities, the barrier to entry for AI-driven financial management is rapidly dropping. We predict that by the end of the year, the distinction between a traditional trading account and a managed portfolio will blur, with AI agents becoming the primary interface for routine financial transactions and payments.