Thanks to the advent of cloud computing and distributed digital infrastructure, the one-person micro-enterprise is far from a novel concept. Cheap on-demand compute, remote collaboration, payment processing APIs, social media, and e-commerce marketplaces have all made it easier to “go it alone” as an entrepreneur.But what about scaling that one-person business into something meatier — an enterprise of unicorn proportions?Historically, this would have been an unfathomably tough task, due to the skills and resources required, not only to scale a product but also to grow and maintain a sufficiently bountiful customer base. But AI agents could unshackle the would-be solo-preneurs of the world.AI agents are all about embedding human workflows into software, freeing the human to do more in less time. Agents can be assigned tasks, and they can make decisions with varying degrees of autonomy. Multiple AI agents could even collaborate on complementary tasks, paving the way for getting some real work done entirely autonomously.In an interview last year with Reddit co-founder Alexis Ohanian, OpenAI’s Sam Altman predicted this exact scenario.“In my little group chat with my tech CEO friends, there’s this betting pool for the first year that there is a one-person billion-dollar company,” Altman said. “Which would have been unimaginable without AI — and now [it] will happen.”In a discussion at the World Economic Forum’s annual meeting in Davos last week, a panel of entrepreneurs and investors also discussed the prospect of the single-person billion-dollar enterprise — and, more importantly, what this might mean for the future of employment.In humans we trustRecent history reveals a slew of svelte billion-dollar companies

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Last year, Cognition started the AI agent wave with a product called Devin — the world’s first AI engineer. The offering was under wraps for several months, but now it’s generally available and learning new chops very quickly. Case in point: the Scott Wu-led startup has just released Devin 1.2, which brings a bunch of new capabilities to take the AI engineer’s ability to handle entire development projects to a whole new level.The biggest highlight of Devin 1.2 is its improved in-context reasoning, which makes the agent better at handling and reusing code. It also includes the ability to take voice messages via Slack, which gives users a more seamless way to tell Devin what it has to do.The development comes at a time when AI-powered agents are being touted as the future of modern work

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreIn the past year, the race to automate has intensified, with AI agents emerging as the ultimate game-changers for enterprise efficiency. While generative AI tools have made significant strides over the past three years — acting as valuable assistants in enterprise workflows — the spotlight is now shifting to AI agents capable of thinking, acting and collaborating autonomously. For enterprises preparing to embrace the next wave of intelligent automation, understanding the leap from chatbots to retrieval-augmented generation (RAG) applications to autonomous multi-agent AI is crucial. As Gartner noted in a recent survey, 33% of enterprise software applications will include agentic AI by 2028, up from less than 1% in 2024.As Google Brain founder Andrew Ng aptly stated: “The set of tasks that AI can do will expand dramatically because of agentic workflows.” This marks a paradigm shift in how organizations view the potential of automation, moving beyond predefined processes to dynamic, intelligent workflows.The limitations of traditional automationDespite their promise, traditional automation tools are constrained by rigidity and high implementation costs. Over the past decade, robotic process automation (RPA) platforms like UiPath and Automation Anywhere have struggled with workflows lacking clear processes or relying on unstructured data