Vibeathons Are Taking Over Hackathons To Rapidly Increase Innovation
It's 10 a.m. on a Thursday. Instead of back-to-back meetings and project updates, a team huddles over laptops in a buzzing workspace. Code is flying. AI tools are generating UI prototypes in real time. There's an energy that feels less like a corporate grind and more like a creative sprint. By 2 p.m., teams test a working prototype of an idea that didn't exist that morning but could lead to the next big innovation.
Welcome to the age of vibathons, also known as vibe coding: high-speed, AI-powered innovation sprints designed for the next generation of problem-solving. Organizations such as Microsoft host these coding jam events where energy meets innovation.
A vibathon is a shorter, more intense version of a hackathon that prioritizes speed, creativity and the use of AI tools to accelerate innovation. Unlike traditional hackathons that may stretch over 48 hours, vibathons often run for four to six hours. It reduces the risk of burnout.
The goal isn't to ship a perfect product. It's to build something tangible and unleash creative momentum.
Where hackathons reward brute-force effort and deep technical stacks, vibathons focus on velocity, product thinking andcross-functional collaboration. It's less about raw code and more about rapid prototyping and inspired decision-making.
Speed Is The New Strategy
In an era where the biggest bottleneck isn't technology but time, speed is a competitive advantage. Vibathons compress the innovation cycle, utilizing AI tools such as code generators, design assistants and smart workflows to transform rough ideas into usable prototypes within hours.
Vibeathons aren't about aiming for flawless execution. Teams rapidly bring ideas to life through immediate, hands-on experimentation. They uncover what works by quickly exposing what doesn't, turning fast failures into valuable feedback loops.
Why AI Is At The Center
Participants are encouraged to use generative AI to streamline development. Writing code, generating wireframes, crafting product copy, even simulating user feedback focuses less on busywork and more on solving the actual problem; making the process more efficient positions the company as a leader in its particular market.
Here's how to run a high-impact vibathon:
Frame the sprint around a specific question or challenge. For example, you could ask:
A cross-functional group collaborates in real time, transforming bold prompts into tangible ... More solutions.
This shift opens the door to designers, product thinkers, marketers and team members without any coding experience to contribute meaningfully using AI tools as force multipliers.
Use a timer. Limit each build phase to 60–90 minutes. Encourage quick, scrappy progress. Remind teams: this is about proof of concept, not production code.
Provide access to a variety of AI tools such as coding assistants that generate code snippets, design generators that create UI mockups and no-code tools that automate repetitive tasks. Offer quick tutorials to level the playing field early, ensuring that everyone makes the most of these powerful tools.
This step is crucial in fostering a collaborative environment. End with brief, high-impact demos. Focus the debrief on what teams learned, not just what they built. The real outcome is insight.
Avoid turning this into a meeting recap. Instead, document big takeaways and new ideas sparked by the sprint. Let the momentum carry into the next work cycle.
Real industry disruptors are those who rapidly experiment and learn. Vibathons create a container for that kind of thinking. They push teams to transition from planning mode to building mode without waiting for approval from above.
They're not just fast. They're focused, energizing and deeply instructive. Because in the age of AI, the next big thing isn't built by committee. It's prototyped in an afternoon.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Entrepreneur
a minute ago
- Entrepreneur
World Wide Web Day 2025: Is India Ready for Web 4.0?
As the global shift toward AI-powered Web 4.0 accelerates, India risks being left behind due to patchy Web 3.0 adoption, rural digital gaps, and uneven infrastructure Opinions expressed by Entrepreneur contributors are their own. You're reading Entrepreneur India, an international franchise of Entrepreneur Media. Tech giants such as Microsoft, Google, Apple, ChatGPT, and Perplexity are racing to build the next generation of AI-powered web browsers. The latest entrant, Perplexity's AI-powered browser Comet, marks a bold step toward this future. As highlighted in a previous article, pricing remains a potential barrier for new players like Perplexity to dominate cost-sensitive markets like India, where traditional browsers remain free to use. However, Perplexity took a strategic leap by partnering with Airtel to offer a one-year subscription worth INR 17,000 at no cost to Airtel SIM users. This mirrors a tried-and-tested method of entering the Indian market, reminiscent of Jio's disruptive strategy to democratise smartphone access through free and subsidised distribution. Yet, with the arrival of AI-powered browsers and the growing shift toward intelligent web ecosystems (Web 4.0), a pressing question emerges: will this wave accelerate digital progress for all Indians, or deepen the existing digital divide between the tech-haves and tech-have-nots? So, what exactly does Web 4.0 entail? "The Web 4.0, also known as the 'Symbiotic Web,' is a highly intelligent, intuitive, and interconnected digital ecosystem powered by artificial intelligence (AI), decentralisation, ambient computing, and advanced human-machine interaction," explains Karthikeyan VS, Director and Head of Asia at Expleo. While he acknowledges India's progress in Web 3.0, he points out that growth has been uneven, especially in areas like blockchain adoption and digital innovation. Aditya Joshi, COO of SA Technologies, adds that India recorded 886 million internet users in 2024, with 55 per cent from rural regions. Still, he says, "adoption of Web 3.0 is patchy." Highlighting data from Oxfam's report (2022), he says the gap is more stark. Only 31 per cent of rural residents have internet access, compared to 67 per cent in urban areas. Among rural women, access is particularly limited. Many still depend on shared devices and often lack basic digital literacy. Joshi notes, "A lack of awareness about blockchain technology and the burden of high transaction fees continue to hold back innovation and widespread adoption." Matthew Oostveen, Vice President and Chief Technology Officer for Asia Pacific and Japan at Pure Storage, makes an even sharper point. "India is not a Web 3.0 nation yet. We've seen selective adoption in crypto (in silos), blockchain experiments, AI pilots but not systemic transformation." For him, the digital divide in India is not just rural versus urban. "It's experiential. Most Indians aren't engaging with Web 3.0." Where does that leave us with Web 4.0? "Web 4.0 will demand far greater coordination between public and private sectors than previous digital waves. The government's role is to provide the enabling environment, robust digital infrastructure, clear and adaptive policy frameworks, and investment in digital literacy. The private sector brings speed, innovation, and scalable platforms. But success depends on aligning incentives, co-developing open standards, supporting public digital goods, and ensuring that solutions are not just profitable but inclusive. Collaboration isn't optional, it's foundational," Oostveen emphasises. Venugopal Ganganna, Co-founder and CIO at LS Digital, views Web 4.0 as a potential tool to bridge the digital divide but only if the mistakes of Web 2.0 and 3.0 aren't repeated. "Web 4.0 could bridge divides if marketers stop thinking in language silos and start thinking in intent. Imagine localised AI agents helping rural entrepreneurs market their products, or interactive storytelling tools that let regional creators compete globally. It's very doable, but the approach needs to be bottoms-up. The opportunity isn't just to communicate better, it's to create new communicators." Ganganna further points out, "The mobile is already the most powerful storytelling device in Bharat. But the success of Web 4.0 will depend on whether the ecosystem can build trust, relevance, and simplicity into every layer, from infrastructure to user interface to value proposition." Oostveen agrees but cautions that inclusion must be a core design principle, not an afterthought. "Web 4.0, with its emphasis on AI, decentralised architectures, and edge computing, has the potential to localise services and reduce dependence on central infrastructure. For example, AI models trained on regional languages could unlock access for millions." Still, Karthikeyan believes several fundamental issues contribute to the deepening digital divide, particularly in rural connectivity, digital literacy, and access to core infrastructure. "As India transitions to Web 4.0, 5G penetration in remote areas will remain inadequate, leaving some uncertainties unresolved. These include policies and regulations governing emerging technologies, the availability of skilled talent, and ongoing cybersecurity concerns." To fully harness the promise of Web 4.0, he suggests a layered policy approach. "If India intends to utilise the potential of Web 4.0, there must be policy layers that support innovative approaches and foster inclusive digital growth so that no community is left behind in this next iteration of the web," Karthikeyan concludes.
Business Wire
a minute ago
- Business Wire
Strategic Insights of Generative AI and Its Automotive Use Cases, 2025 Research Report - AI-Driven Voice Assistants to Become Standard in Vehicles by 2033
DUBLIN--(BUSINESS WIRE)--The "Strategic Insights of Generative AI and Its Automotive Use Cases" report has been added to offering. Generative AI (Gen AI) continues to create an impact across industries including automotive. In the next decade, Gen AI is expected to significantly influence automotive value chains, increase efficiency, productivity, and reduce wastes. In the supply chain, it will be used to optimize inventory and demand forecasting while in product development it can be used to generate design ideas, accelerate prototyping, testing and to shorten the time-to-market. In manufacturing, it can be used to reduce bottlenecks on the assembly line and provide real time insights to production engineers to make informed decisions. In retail, it can be used to provide 24x7 sales support to dealerships executing human- like interactions with potential customers. Inside the vehicle, Gen AI- driven voice assistants will become standard features in the next decade. Beyond the automotive lifecycle, Gen AI will make a significant contribution towards autonomous vehicle development and operation. Gen AI start-ups which focus on solutions for autonomous vehicles will crop up in the coming decade driving innovation and fast tracking the development of such vehicles. Gen AI will support shared mobility by helping increase the efficiency of fleet management, ride booking, pricing, and route planning. In logistics, it will play a key role in choosing the optimal vehicle for a trip, plan routes based on real time traffic data, and customer support functions. Gen AI will also play a key role across various corporate functions including Finance, Human Resources, and Marketing. Growth Drivers The Rapid Technological Transformation in the Automotive Industry: The automotive industry has seen transformational shifts in the past decade, with automakers embracing innovative technologies to digitize operations. GenAI will augment this transformation. The automotive industry has seen transformational shifts in the past decade, with automakers embracing innovative technologies to digitize operations. GenAI will augment this transformation. Endeavor to Enhance the In-Cabin Experience: Automakers are always on the lookout for ways in which they can enhance the in-cabin experience for their customers. GenAI will enable OEMs to offer next-generation human-machine interfaces through GenAI-powered voice assistants. Automakers are always on the lookout for ways in which they can enhance the in-cabin experience for their customers. GenAI will enable OEMs to offer next-generation human-machine interfaces through GenAI-powered voice assistants. Improve Efficiency and Profitability: GenAI can help automate redundant tasks and, coupled with a voice assistant, provide real-time status updates on active tasks, thereby increasing the efficiency of decision-making. This leads to reduced operational tasks and a better bottom line. GenAI can help automate redundant tasks and, coupled with a voice assistant, provide real-time status updates on active tasks, thereby increasing the efficiency of decision-making. This leads to reduced operational tasks and a better bottom line. Focus on Increasing the Quality of Customer Engagement: Companies intend to enhance customer engagement and satisfaction by leveraging new technologies. GenAI enables companies to increase the efficiency of customer support chatbots, facilitating 24/7 support in natural languages. Growth Restraints Data Privacy Concerns: Instances of sensitive company data leaking into the public domain through GenAI applications make companies uneasy and apprehensive about adopting this technology. Instances of sensitive company data leaking into the public domain through GenAI applications make companies uneasy and apprehensive about adopting this technology. Issues with Reliability: GenAI tools have been found to hallucinate and give out factually incorrect information, which could be seen as an unreliable technology in the short term. As the technology matures, the accuracy will improve. GenAI tools have been found to hallucinate and give out factually incorrect information, which could be seen as an unreliable technology in the short term. As the technology matures, the accuracy will improve. Regulatory Issues: Governments could view GenAI suspiciously over the ethics around the use of it by companies and common citizens, and the negative impact it can have on various facets of society. This could result in adverse regulations against the use of GenAI. Governments could view GenAI suspiciously over the ethics around the use of it by companies and common citizens, and the negative impact it can have on various facets of society. This could result in adverse regulations against the use of GenAI. Practicality: For organizations to effectively leverage the power of GenAI, they need large datasets and significant computing power. This could be difficult to achieve for organizations in the short term. Impact of the Top 3 Strategic Imperatives on GenAI in Automotive Market Customer Value Chain Compression Generative AI (GenAI) can automate customer interaction touchpoints that could not be automated efficiently earlier. GenAI can understand customer requirements and respond accordingly, almost creating a humanlike conversation when coupled with a voice assistant. Disruptive Technologies GenAI is a disruptive technology that can ease the workload and support employees in an organization to achieve their goals faster and with greater accuracy and efficiency. Industry Convergence GenAI large language models (LLMs) offer numerous possible use cases for all industries, including automotive. GenAI has the potential to accelerate innovations in next-generation technologies and products. Scope of Analysis Examine possible generative AI use cases in the automotive value chain. Look at evolving use cases and analyze them to understand their impact on the future automotive value chain. Break down the automotive value chain into subsegments and discuss potential applications. Analyze generative AI's potential integration into existing automotive products and solutions. Examine the challenges associated with generative AI in the workplace and use cases that highlight the concerns regarding this technology. Derive growth opportunities and key takeaways stemming from the analysis. Key Topics Covered: Scope Scope of Analysis Why is it Increasingly Difficult to Grow? The Strategic Imperative Impact of the Top 3 Strategic Imperatives on GenAI in Automotive Market Growth Environment: Transformation of GenAI in Automotive Key Takeaways Key Automotive Ecosystem Players Using GenAI Key Automaker GenAI Use Case By Value Chain GenAI Types and Impact on Automotive Use Case by 2030 Potential Applications of GenAI in Key Corporate Functions Car Models with GenAI Voice Assistants Price to Access GenAI Voice Assistants in Cars GenAI in Automotive - Current Adoption vs Future Impact Case Study - Valeo Growth Generator in GenAI in Automotive Growth Drivers Growth Restraints Overview of GenAI Key Reasons for Organizations to Adopt GenAI GenAI Vs Traditional AI The Automotive GenAI Ecosystem - Key Stakeholders Select GenAI Tools by Application Most Popular GenAI Tools IT Decision-Makers' Perception Towards GenAI Challenges - Concerns Around GenAI in Organizations Emerging AI Regulations by Key Regions Overview of GenAI - Key Takeaways GenAI in Supply Chain Snapshot of Possible GenAI Applications in Automotive Possible Use Cases of GenAI in Automotive Supply Chain GenAI in Automotive Supply Chain - Certainty of Application GenAI in Supply Chain - Key Takeaways GenAI in Manufacturing Possible Use Cases of GenAI in Automotive Product Design Select GenAI Image Generator Tools Case Study - Product Design-Toyota Case Study - Ferrari GenAI in Automotive Design - Certainty of Application Possible Use Cases of GenAI in Automotive Production GenAI in Automotive Production - Certainty of Application GenAI Adoption by OEMs in Production Case Study - Mercedes-Benz Overview of GenAI in Manufacturing - Key Takeaways GenAI in Automotive Retail Possible Use Cases of GenAI in Automotive Retail Case Study - Marketing: Lexus/Toyota Automotive Retail - Sales Scenario Using GenAI Case Study - Sales: Fullpath Case Study - Sales: BMW + Accenture Case Study - Customer Management: Ford GenAI in Automotive Retail - Certainty of Application Overview of GenAI in Retail - Key Takeaways In-Vehicle GenAI Possible Use Cases of In-Vehicle GenAI OEMs with GenAI-Powered Voice Assistants Case Study - Nio AI Voice Assistant Case Study - Mercedes-Benz Case Study - Linguistic Localization: KIA Automotive Suppliers Focus on GenAI Voice Assistant Case Study - Soundhound AI Case Study - Continental & Google Case Study - Cerence-Skoda GenAI in the Vehicle Cabin - Certainty of Application GenAI in the Vehicle Cabin - Key Takeaways Beyond the Automotive Life Cycle Possible Use Cases of GenAI in Autonomous Vehicles Evolving GenAI Case Studies in Autonomous Driving Case Study - Forvia Hella Possible Use Cases of GenAI in Shared Mobility Case Study - Turo Possible Use Cases of GenAI in Logistics GenAI Use Case Scenario in Logistics GenAI Beyond Automotive Life Cycle - Key Takeaways Growth Opportunity Universe Growth Opportunity 1: Subscription Revenue Through Generative AI Powered Voice Assistants Growth Opportunity 2: Usher in an Era of AI-driven Manufacturing Growth Opportunity 3: Transform Customer Engagement Appendix & Next Steps Benefits and Impacts of Growth Opportunities Next Steps Companies Featured Accenture BMW Cerence-Skoda Continental Ferrari Ford Forvia Hella Fullpath Google KIA Lexus/Toyota Mercedes-Benz Nio Soundhound AI Toyota Turo Valeo For more information about this report visit About is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.
CNET
a minute ago
- CNET
Save $150 on This Ecovacs RTK Robot Lawn Mower Before Amazon Pushes the Price Back Up
Mowing the lawn during peak summer heat isn't exactly a good idea, and definitely not how most of us want to spend our weekends. Add in the extra growth from recent rains, and you're looking at quite a time and energy-consuming task. This is where a robot lawn mower can help, and right now, you can snag a powerful machine at a discount. Right now, Amazon is being generous with a 15% discount on the Ecovacs Goat O1000 RTK robot lawn mower, bringing the price down to $850. It's still an investment, but considering how it does the entire job for you, it's worth the price. Just note that the discount might not last too long, so we recommend acting fast. This machine comes with an advanced automated mapping system that generates a layout of your entire yard before getting to work. You can customize the map by adding or removing zones, splitting areas, and adjusting your mowing preferences directly from the app. Hey, did you know? CNET Deals texts are free, easy and save you money. Mowing is consistent. Ecovacs Goat goes through your lawn in U-shaped patterns that ensure no spots are missed for you to deal with later. It cuts right up to the edges and also lets you set the cutting height anywhere between 1.2 and 3.1 inches. You won't have to worry about obstacles either. The built-in 3D obstacle detection helps it avoid both pets and other small objects. Got an uneven, hilly yard? This mower can move through spaces as narrow as 2.3 feet, and even climb slopes of up to 24 degrees. Once it finishes its job, you can give it a nice rinse to clean it up quickly, since it's also IPX6 waterproof. Why this deal matters Robot lawn mowers, especially those with advanced features, sit well over $1,000. If you've been thinking of investing in one, this deal brings the price down of a reliable, powerful option to $850, which is a pretty solid drop for a model this feature-packed. Just be sure to place your order before Amazon pushes the price back up.
