Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders.<\/em> Subscribe Now<\/em><\/p>\n\n\n\n Traditionally, product releases can be cumbersome, requiring multiple sign-offs, endless tinkering, bureaucracies and friction points.\u00a0<\/p>\n\n\n\n Genspark has developed a much different approach.\u00a0<\/p>\n\n\n\n The AI workspace company\u2019s lean team practices AI-native working \u2014 or \u2018vibe working,\u2019 if you will \u2014 so that they can move at what they call \u201cgen speed.\u201d This allows them to release new products and features in rapid-fire succession (nearly every week or so), steadily driving up annual recurring revenue (ARR). As the company boasts, it could be \u201cthe fastest-growing startup ever in terms of ARR.\u201d<\/p>\n\n\n\n \u201cWhen people are working the AI-native way, basically everybody is the manager,\u201d Kaihua (Kay) Zhu, co-founder and CTO, told VentureBeat. \u201cThey are equipped with a team of AI agents, which are kind of their reportees, and they are capable of, single-handedly, delivering the feature end-to-end. \u201c<\/p>\n\n\n\n Power caps, rising token costs, and inference delays are reshaping enterprise AI. Join our exclusive salon to discover how top teams are:<\/p>\n\n\n\n Secure your spot to stay ahead<\/strong>: https:\/\/bit.ly\/4mwGngO<\/p>\n\n\n\n Genspark, launched in June 2024 by MainFunc, was initially focused on AI search. But despite reaching an impressive 5 million users, the company pivoted away from that initial product to Super Agent, which, instead of following a static sequence of steps as in traditional search, chooses the best tools or sub-agents for the job, gauges results and adjusts in real time.\u00a0<\/p>\n\n\n\n Launching on April 2, Super Agent is powered by Anthropic\u2019s Claude and can condense an afternoon of white collar office work into 5 minutes, Zhu claims. For instance, it can make calls, download, fact check, produce podcasts, draft documents, perform deep research and pull together spreadsheets and slides.\u00a0<\/p>\n\n\n\n \u201cWe still see it as a kind of search, but it\u2019s more technically advanced,\u201d said Zhu, who has more than 20 years of experience working in search at Google and Baidu.\u00a0<\/p>\n\n\n\n The company has aggressively added more and more features over the last four months; here\u2019s a rundown of its rollouts and milestones:\u00a0<\/p>\n\n\n\n Genspark is also heating up the AI agent space with friendly competition. After OpenAI announced its ChatGPT agent in mid-July, Genspark performed a comparative analysis and is \u201cvery confident\u201d in its ability to overperform the rival. To drive home this point, the company launched a \u201c1 Million Dollar Side-by-side AI Showdown,\u201d challenging users to hunt for cases where other platforms outperform Genspark Super Agent.\u00a0<\/p>\n\n\n\n In the first round, users were tasked with building a 12-page financial slide using Genspack and ChatGPT Agent; users identified 429 cases where the latter outperformed the former, each earning $100 for their efforts.\u00a0<\/p>\n\n\n\n In round 2 (which ended Monday, August 4), Genspark upped the ante to $200 per win and opened the competition to any AI tool as an opponent. Users were challenged to use exactly the same prompt to build slides on Genspark and their chosen AI tool, then upload them to Gemini for evaluation.\u00a0<\/p>\n\n\n\n \u201cNot trying to start any drama here \u2014 just genuinely excited about how far the entire AI agent ecosystem has come,\u201d the company posted on X. \u201cIt shows we\u2019re all pushing the boundaries in the right direction.\u201d<\/p>\n\n\n\n Some user reactions:\u00a0<\/p>\n\n\n\n Genspark\u2019s secret is its lean, AI-native team of 20 people and engineering philosophy of \u201cless control, more tools.\u201d Zhu explained that more than 80% of its code is written by AI, which isn\u2019t vibe coding per se, \u201cbecause vibe coding kind of indicates you never look at the code.\u201d Rather, Genspark has a \u201cvery rigid\u201d code review process to help guarantee the quality of their code base.\u00a0<\/p>\n\n\n\n \u201cWe only need a very small AI-native team to operate in a kind of superhero mode, like The Avengers<\/em>,\u201d said Zhu, who said they\u2019ll gradually add team members as needed. \u201cThe AI coding and AI workflow are so powerful, it\u2019s a magnifier.\u201d<\/p>\n\n\n\n Today\u2019s enterprise teams must be reorganized \u201ctotally differently,\u201d he said. He\u2019s managed 1,000-member teams with different levels of management and seen how office politics can introduce friction.\u00a0<\/p>\n\n\n\n Genspark\u2019s team, by contrast, communicates in \u201ca very transparent way,\u201d and productivity is \u201csuper high.\u201d \u201cEverybody is working on a product that can ship,\u201d said Zhu. \u201cI believe that that will be the norm looking forward, since AI is actually helping more and more people do their work better.\u201d<\/p>\n\n\n\n He also emphasized the importance of immersing yourself in your own product. From designers themselves to the marketing team, \u201cwe actually eat our own dog food. We are our own product consumer. That\u2019s how we will keep improving the experience.\u201d<\/p>\n\n\n\n Zhu noted that, when Perplexity launched in December 2022, it ignited excitement about AI\u2019s potential to transform search. Still, it followed rigid workflows, with platforms having to:\u00a0<\/p>\n\n\n\n This was adequate for basic stuff, but \u201ccrumbled\u201d in more complex scenarios like technical comparisons, in-depth research and multi-step and multi-factor purchases. \u201cIn essence, it was like trying to navigate a maze with only fixed turns,\u201d said Zhu.\u00a0<\/p>\n\n\n\n Genspark built its search engine on this same kind of foundation, layering on incremental improvements including specialized data sources, parallel search for deeper investigation into complex queries and cross-checking of asynchronous agents to verify statements too complex for \u201cquick, on-the-fly handling.\u201d But they realized they were still \u201cshackled\u201d by fixed, predefined workflows, Zhu reported.\u00a0<\/p>\n\n\n\n Super Agent uses nine differently-sized, differently-specialized large language models (LLMs) in a mixture-of-agents (MoE) system. Models break tasks down into steps, delegating based on specialty and strength, then cross-verify one another. Super Agent is also equipped with more than 80 tools (from sub-agents that can generate Python code to ones that can autonomously make phone calls) and more than 10 datasets curated from the web, partners and repositories.\u00a0<\/p>\n\n\n\n Genspark gives tasks to Claude, OpenAI, Google Gemini, DeepSeek., AI\u2019s Grok 4 and others, \u201cthen we let everybody produce their output, and we have an aggregator model to look through the results and analyze which process is most cost-effective,\u201d Zhu explained. \u201cIn this way, we improve the accuracy, reduce hallucinations.\u201d\u00a0<\/p>\n\n\n\n The company also fine-tunes its own frontier model. However, they are not overly aggressive about creating state-of-the-art systems like DeepSeek v3 or v4, Zhu emphasized. The goal is to have the model perform low-level but heavy lifting work.\u00a0\u00a0<\/p>\n\n\n\n \u201cWe are not trying to push the boundary of the frontier model,\u201d he said. \u201cWe are trying to bring down the cost and the latency, because a lot of proprietary models are too big, too slow and too expensive for a lot of relatively simple tasks.\u201d<\/p>\n\n\n\n As for the vibe coding trend, Genspark\u2019s goal is to allow everyone to experiment, even for non-programmers where the concept may be a little \u201ctoo distant.\u201d\u00a0<\/p>\n\n\n\n \u201cA lot of people think, \u2018vibe coding, I\u2019ve heard about it, it sounds cool, but I\u2019m not familiar with the integrated developer environment (IDE), I\u2019m not familiar with code,\u201d said Zhu. \u201cUsing Genspark, people can actually vibe.\u201d\u00a0<\/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
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\n<\/div>Aggressive rollouts, stoking competition<\/h2>\n\n\n\n
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Inside Genspark\u2019s flagship Super Agent<\/h2>\n\n\n\n
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