Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy.\u00a0Learn more<\/em><\/p>\n\n\n\n Vibe coding has been all the rage in recent months as a simple way for anyone to build applications with generative AI.<\/p>\n\n\n\n But what if that same easy-going, natural language approach was extended to other enterprise workflows? That\u2019s the promise of an emerging category of agentic AI applications. At VB Transform 2025 today, one such application was on display with the Genspark Super Agent, which was originally launched earlier this year.<\/p>\n\n\n\n The Genspark Super Agent\u2019s promise and approach could well extend the concept of vibe coding into vibe working. A key tenet of enabling vibe working, though, is to go with the flow and exert less control rather than more over AI agents.<\/p>\n\n\n\n \u201cThe vision is simple, we want to bring the Cursor experience for developers to the workspace for everyone,\u201d Kay Zhu, CTO of Genspark, said at VB Transform. \u201cEveryone here should be able to do vibe working\u2026 it\u2019s not only the software engineer that can do vibe coding.\u201d<\/p>\n\n\n>>See all our Transform 2025 coverage here<<<\/strong>\n\n\n According to Zhu, a foundational premise for enabling a vibe working era is letting go of some rigid rules that have defined enterprise workflows for generations.<\/p>\n\n\n\n Zhu provocatively challenged enterprise AI orthodoxy, arguing that rigid workflows fundamentally limit what AI agents can accomplish for complex business tasks. During a live demonstration, he showed the system autonomously researching conference speakers, creating presentations, making phone calls and analyzing marketing data.\u00a0<\/p>\n\n\n\n Most notably, the system placed an actual phone call to the event organizer, VentureBeat founder Matt Marshall, during the live presentation.\u00a0<\/p>\n\n\n\n \u201cThis is normally the call that I don\u2019t really want to do by myself, you know, in person. So I let the agent do it,\u201d Zhu explained as the audience listened to his AI agent attempt to convince the moderator to move his presentation slot before Andrew Ng\u2019s session. The call connected in real-time, with the agent autonomously crafting persuasive arguments on Zhu\u2019s behalf.<\/p>\n\n\n\n The calling feature has revealed unexpected use cases highlighting both the platform\u2019s capabilities and users\u2019 comfort with AI autonomy.\u00a0<\/p>\n\n\n\n \u201cWe actually observe a lot of people are using Genspark to call\u2026 to do different kinds of things,\u201d Zhu noted. \u201cSome of the Japanese users are using this to call to resign from their company. You know they don\u2019t like the company, but they don\u2019t want to call them again. and some of the people are using call for me agents to break up with their boyfriend and girlfriend.\u201d<\/p>\n\n\n\n These real-world applications demonstrate how users are pushing AI agents beyond traditional business workflows into deeply personal territory.<\/p>\n\n\n\n The system accomplishes all of that without predefined workflows. The platform\u2019s core philosophy of \u2018less control, more tools\u2019 represents a fundamental departure from traditional enterprise AI approaches.<\/p>\n\n\n\n \u201cWorkflow in our definition is the predefined steps and these kinds of steps often break on edge cases, when the user asks harder and harder questions, the workflow cannot hold,\u201d Zhu said.<\/p>\n\n\n\n Genspark\u2019s agentic engine represents a significant departure from traditional workflow-based AI systems.\u00a0<\/p>\n\n\n\n The platform combines nine different large language models (LLMs) in a mixture-of-experts (MoE) configuration, equipped with over 80 tools and 10+ premium datasets. The system operates on a classic agent loop: plan, execute, observe and backtrack. Zhu emphasized that the power actually lives in the backtrack stage.<\/p>\n\n\n\n This backtracking capability allows the agent to intelligently recover from failures and find alternative approaches when unexpected situations arise, rather than failing at predefined workflow boundaries. The system uses LLM judges to evaluate every agent session and attributes rewards to each step, feeding this data back through reinforcement learning and prompt playbooks for continuous improvement.<\/p>\n\n\n\n The technical approach differs markedly from established frameworks like LangChain or CrewAI, which typically require more structured workflow definition. While these platforms excel at orchestrating predictable multi-step processes, Genspark\u2019s architecture prioritizes autonomous problem-solving over deterministic execution paths.<\/p>\n\n\n\n Genspark\u2019s rapid scaling, from launch to $36 million ARR in 45 days, demonstrates that autonomous agent platforms are moving beyond experimental phases into commercial viability.\u00a0<\/p>\n\n\n\n The company\u2019s \u2018less control, more tools\u2019 philosophy challenges fundamental assumptions about enterprise AI architecture.\u00a0<\/p>\n\n\n\n The implications for enterprises leading in AI adoption are clear: start architecting systems that can handle predictable workflows and autonomous problem-solving. The key is designing platforms that gracefully escalate from deterministic processes to agentic behavior when complexity demands it.\u00a0<\/p>\n\n\n\n For enterprises planning later AI adoption, Genspark\u2019s success signals that vibe working is becoming a competitive differentiator. Organizations that remain locked into rigid workflow thinking may be disadvantaged as AI-native companies embrace more fluid, adaptive approaches to knowledge work.\u00a0<\/p>\n\n\n\n The question isn\u2019t whether autonomous AI agents will reshape enterprise workflows\u2014it\u2019s whether your organization will be ready when the 20% of complex cases becomes 80% of your AI workload.<\/p>\n Daily insights on business use cases with VB Daily<\/strong><\/p>\n If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.<\/p>\n \n\t\t\t\t\tThanks for subscribing. Check out more VB newsletters here.\n\t\t\t\t<\/p>\n An error occured.<\/p>\n<\/p><\/div>\n
\n<\/div>Less is more when it comes to enterprise agentic AI<\/h2>\n\n\n\n
Technical architecture: Why backtracking is good for enterprise AI\u00a0<\/h2>\n\n\n\n
Enterprise Strategy: Workflows today, vibe working agents tomorrow<\/h2>\n\n\n\n
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