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The Vision for AI Coding Agents Cognition CEO Scott Wu made headlines again this week when his two-year-old AI coding agent startup raised $1 billion at a $26 billion valuation. Cognition is the maker of Devin, one of the first and, arguably, most successful AI coding agents. Devin, the CEO says, “naturally owns tasks end to end.” The Future of Software Development In fact, in the blog post announcing that raise, Cognition laid out a vision where “we are shifting to a world of self-driving software development.” So, could Devin replace, say, a mid-level L4 programmer? Yes, and no, Wu told TechCrunch. “We’ve never thought about it as replacing humans. I know it’s like a scenario, folks have said these things. It has never been our view.” Preserving the Joy of Programming Wu emphasizes that the goal is not to make human programmers obsolete. “We are all programmers ourselves,” he explained. “I started coding when I was nine.” He views agents as another layer of abstraction between envisioning a software product and producing it, similar to how visual development environments abstracted software creation away from machine instructions. The Role of Devin in Cognition Cognition says that Devin’s role in its own company is to ship nearly all the software. The company says that 89% of code committed by its engineers was committed by Devin, and the rest by local agents. Wu explains that his agent’s role is largely to do the kinds of long-tail maintenance tasks that many programmers don’t like to do anyway: bringing old software up to date; moving applications off one platform and onto another. The Future of AI Agents Wu predicts that agents will enter other fields where they will learn tasks, from customer service to medicine, but hopes the goal will be to augment human workers in those areas, too. “Code and software has been the first to move, but we’ll see this happen in all these other industries,” he predicts. “One thing that’s been clear to us since the beginning is, it should always be up to the human what to do … you really see this in software engineering, but I think it’s true in all these other professions too.”

The LeadBlue Origin's New Glenn rocket exploded during a test in Florida on Thursday, an incident which the aerospace company called an "anomaly." All personnel have been accounted for, and the company has promised to provide updates as they learn more about what caused the explosion.The Explosion DetailsA livestream posted by NSF, an aerospace news organization, captured the fiery plume of the explosion. Homes shook in nearby Cape Canaveral and Cocoa Beach around 9pm, with residents turning to social media to ask what happened. Cape Canaveral Space Force Station's Launch Complex 36 is visible from the beach, and the internet quickly filled with photos of the orange fireball. Emergency officials confirmed there was no threat due to fumes or other potential hazards.Recent Setbacks for Blue OriginThis explosion marks another setback for Blue Origin, which is owned by Amazon founder Jeff Bezos. The New Glenn rocket was already grounded in April, as the Federal Aviation Administration required Blue Origin to investigate an engine mishap. The FAA has not yet commented on whether Thursday's explosion will trigger another investigation.Industry Competition ImplicationsThe incident comes at a critical time for Blue Origin's space ambitions. Earlier this week, NASA announced it had chosen Blue Origin over Elon Musk's SpaceX to conduct the first of three uncrewed lunar missions this year to kickstart construction of a $20 billion moon base. Both companies are competing to provide crew landers for upcoming Artemis missions, including the planned 2028 return of humans to the moon on Artemis IV. Both companies have built large new facilities in or close to Cape Canaveral's Kennedy Space Center to support crewed and cargo missions in partnership with NASA.Future Outlook for Blue OriginDespite the explosion, Blue Origin's space ambitions remain significant. The company has a vested interest in space tourism, having sent an all-female, star-studded crew including Gayle King and Katy Perry into space last April. Elon Musk, whose SpaceX lost the NASA contract to Blue Origin, commented on the incident, writing "Most unfortunate. Rockets are hard." This latest explosion may delay Blue Origin's timeline but is unlikely to derail their long-term space exploration goals, though it may create opportunities for competitors like SpaceX to gain ground in the increasingly competitive private space race.

The Rise of Machine-Generated Traffic Cloud infrastructure has long been designed around humans who search, click, scroll, and stream in a steady and predictable fashion. However, AI agents behave differently. They can unleash a swell of activity, spinning up multiple sub-agents that query hundreds of databases, search documents, and call APIs in seconds and then disappear as quickly as they arrived. AWS's Next-Gen OpenSearch Serverless Under that premise, Amazon is redesigning a core piece of its cloud infrastructure. On Thursday, AWS launched its next generation of OpenSearch Serverless, a fully managed search and vector database — essentially a system for storing and retrieving information at scale — that's designed specifically for agentic workloads. AWS says the new system can instantly scale up when agents trigger tasks and scale back down to zero when idle. The Data Analysis Cloudflare says bots accounted for 31% of overall HTTP traffic over the last six months. AI crawlers, search engines, and assistants made up roughly a quarter of all bot requests during that period. 'Non-human traffic will exceed human traffic sometime in the first half of 2027,' said Lai Yi Ohlsen, senior product manager at Cloudflare. The Impact Analysis The launch reflects a growing realization across the tech industry: Infrastructure originally designed for a human-driven internet doesn't work as well in a world increasingly populated by agents. As AI agents still represent a relatively small portion of internet activity, machine-generated traffic is already significant, and poised to grow. The Prediction As a result, cloud providers and infrastructure companies have been reckoning with how to adapt systems built for humans to a world of agents that are constantly and autonomously retrieving information, invoking tools, and generating machine-to-machine traffic. The more companies deploy AI agents, the more pressure there will be to redesign infrastructure around machine-generated workloads, which in turn could make agents cheaper and easier to deploy at larger scales.

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.

The Lead: China's Bold Leap into Long-Duration SpaceflightChina has launched its Shenzhou-23 mission in which an astronaut will spend a full year in orbit for the first time, a crucial step in Beijing's ambition to send humans to the moon by 2030. The Long March 2-F rocket lifted off from the Jiuquan launch centre in north-western China on Sunday, carrying three astronauts to the Tiangong space station.The Mission Details: Historic Crew CompositionThe mission marks the first spaceflight ever undertaken by an astronaut from Hong Kong: Lai Ka-ying, 43, who previously worked for the territory's police. The other crew members are the space engineer Zhu Yangzhu, 39, and the former air force pilot Zhang Zhiyuan, also 39, who will be travelling into space for the first time.The Scientific Objectives: Preparing for Deep SpaceThe crew is expected to undertake numerous scientific projects in life sciences, materials science, fluid physics and medicine. A key experiment will be the full-year stay in orbit by one of the crew to study the effects of a long stay in microgravity, part of China's preparations for future lunar and possible Martian missions.Richard de Grijs, an astrophysicist and professor at Macquarie University in Australia, said the main challenges would be long-term effects on humans, including bone density loss, muscle wasting, radiation exposure, sleep disturbance and behavioural and psychological fatigue. He also underlined the importance of reliable water and air-recycling systems and the ability to manage potential medical emergencies far from Earth.The Lunar Ambitions: China's Moon RoadmapThe Shenzhou-23 mission is part of China's goal to land astronauts on the moon before 2030 in a race with Nasa's Artemis programme. Beijing is also testing the equipment required to reach its goal, with an orbital test flight of its Mengzhou spacecraft set for 2026. It will replace the ageing Shenzhou line and will carry China's astronauts to the moon.China hopes to have built the first phase of a manned scientific base, known as the International Lunar Research Station, by 2035. It also plans to welcome its first foreign astronaut, from Pakistan, to the Tiangong station by the end of this year.The Global Context: China's Space Program EvolutionBeijing has significantly expanded its space programmes over the last 30 years, injecting billions of dollars in a push to catch up with the US, Russia and Europe. It landed the Chang'e-4 probe on the far side of the moon, a world first, in 2019, and a rover on Mars in 2021.China has been formally excluded from the International Space Station since 2011, when the US banned Nasa from collaborating with Beijing, prompting it to develop its own space station project. This isolation has accelerated China's indigenous space capabilities, making the Shenzhou-23 mission a milestone in both scientific achievement and geopolitical space competition.

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.

A Journey Through Talybont's LandscapeStarting at the well-maintained cemetery in Talybont, this walk offers a unique perspective on Cors Fochno (Borth Bog) and the surrounding Dyfi Valley. The author begins with the philosophical observation that beginning a walk in a cemetery is infinitely preferable to ending one there, setting the tone for a reflective journey through Wales' natural beauty.The Expansive View of Cors FochnoAfter the early rain clears, the air becomes crisp and colors deepen. The landscape features grassland fields sloping toward the wild expanse of the bog, bounded by wooded hedgerows bright with hawthorn blossom. The first cut of silage has been secured, and cattle graze the remaining grass while red kites traverse overhead. Across the Afon Dyfi, the sand dunes of Aberdyfi are visible, with the eye drawn further to the hills defining the Llŷn peninsula.Exploring the Bog's EdgeAn old track, steep and rough underfoot, drops down to an eroded surface above the bog. Turning east toward Tre Taliesin opens up the impressive view of the Dyfi Valley, constrained by stern ranks of hills on both sides. This lane marks the boundary between well-drained pastures and marginal wetland, with patches of scrub and bands of foliage indicating where rock outcrops rise from the bog's gently domed surface—once true islands that would have provided refuge in times of unrest.Weather Patterns and Natural ObservationsAs the day becomes oppressively thundery, towers of cumulonimbus cloud build above the hills. The mosaic of fields and woods darkens as ragged cloud elements occlude the sun, while bees fumble noisily in the blossoms. The author notes these natural phenomena while trudging uphill into the village, pausing to observe the metal sign marking the former "Telegraph Office" and wondering about temporal quirks that might bring the office back into existence.The Intersection of Nature and HistoryThis walk through Talybont demonstrates how natural landscapes and human history intertwine. The cemetery, the old track, and the telegraph office sign all connect the present-day walker with past generations who inhabited this same landscape. The islands in the bog that once provided refuge in times of unrest now serve as reminders of how humans have always existed in relationship with their environment, adapting to and appreciating the natural world around them.

The World's First Robot Theme Park Opens in SeoulGalaxy Robot Park has opened in Seoul, claiming to be the world's first robot theme park, featuring humanoid robots that perform K-pop concerts. The ambitious project by Galaxy Corporation aims to revolutionize entertainment by having robots perform thousands of shows annually and potentially tour globally.Humanoid Performers Take the StageFour child-sized humanoid robots take the stage at an arena in eastern Seoul, performing synchronized dance moves to K-pop songs by stars like G-Dragon and Taemin. These robots, dressed in wigs and baggy clothes, execute their moves with surprising fluidity across a repertoire of different songs, including G-Dragon's "Home Sweet Home" and Taemin's "Advice and Idea."Behind the project is Galaxy Corporation, an entertainment company that positions itself as an "enter-tech" firm, blending entertainment with technology. The company manages megastar G-Dragon, as well as Taemin from the group Shinee and actor Song Kang-ho, known to western audiences for his role in the film "Parasite."Ambitious Performance Schedule and Global PlansAccording to Choi Yong-ho, Galaxy's chief executive and self-styled "chief happiness officer," the park plans to host three to six K-pop concerts daily, over 1,000 shows annually. By the end of 2026, the company aims to take the robots on a world tour, potentially transforming how concerts are experienced globally.K-pop has long served as a testing ground for experimental tech, from SM Entertainment's Aespa, which pairs real members with virtual avatars, to fully virtual boybands like Plave. The robot performances represent the next frontier in this technological evolution of entertainment.Cultural and Economic ImplicationsCha Woo-jin, a music critic and industry analyst, views the ambitious plan as both a cultural and economic experiment. "If you put a robot in an Elvis museum, fans would be repulsed," he says. "But K-pop is a visual packaging model, so robots feel less alien."A robot tour, he explains, would be like a cover dance crew – the groups that replicate routines of famous K-pop performers – but without hotel bills or per diems. This could significantly reduce production costs while potentially expanding the reach of K-pop performances globally.The Future of Automated EntertainmentThe Galaxy Robot Park represents a bold vision for the future of entertainment, where robots don't just assist humans but perform for them, potentially across continents simultaneously. As technology advances, we may see humanoid robots taking on more complex creative roles in various entertainment sectors, from music to fashion, with the K-pop industry leading this technological frontier.While questions remain about audience acceptance and the artistic authenticity of robotic performances, the project demonstrates South Korea's continued commitment to pushing technological boundaries in entertainment and its position as a global cultural innovator.

The AI Security Imperative At a recent event in Los Angeles, Google Cloud COO Francis deSouza stressed that security can't be an afterthought in AI adoption. He advocated for a platform approach to security, warning against 'shadow AI' where employees use consumer tools without organizational oversight. The Risks of 'Shadow AI' DeSouza highlighted the risks associated with employees using unauthorized AI tools, which can lead to security breaches and data exposure. He emphasized that companies need to demand security, governance, and auditability from their platforms from the start. The Challenge of Keeping Pace with AI Threats The threat landscape has changed fundamentally, with the average time between an initial breach and the next stage of an attack dropping from eight hours to 22 seconds. The attack surface has expanded beyond the traditional network perimeter, and companies need to adapt to this new reality. Google's Own AI Security Challenges Despite deSouza's sound advice, Google itself faces challenges with AI security. The company has refunded developers who incurred large bills due to unauthorized API calls to Gemini models. Google's automated systems had upgraded their billing tiers without explicit consent, leading to surprises for developers. The Future of AI-Native Defense DeSouza sees the emergence of AI-native, fully agentic defense as a solution to the challenges posed by AI threats. This approach involves using agents to drive defense, allowing humans to oversee and focus on high-level decision-making. The Skills Gap in AI Security The industry faces a shortage of people qualified to oversee AI security, and the vulnerabilities introduced by AI are multiplying faster than security teams can address them. According to LinkedIn's CISO Lea Kissner, it may take several years for the industry to understand AI security in a sustainable way.