Latest news with #Andela
Forbes
02-07-2025
- Business
- Forbes
Letting Go: Transformational Leadership In The Age Of AI
In the age of AI, real leadership means letting go of control to unlock collaboration, curiosity, ... More and human-AI co-creation. In a world defined by complexity, velocity, and AI-driven change, the most significant transformational leadership act isn't holding on. It's letting go. For decades, leadership meant control of teams, budgets, decisions, and narratives. But in today's fluid, networked, and talent-distributed world, that grip has become a liability. The leaders thriving now are the ones who have learned to loosen their grip, to empower, co-create, and operate with humility. Letting go is no longer a weakness; it's a strength. It's a strategic necessity. The rise of the open talent economy demonstrates this shift in real-time. Platforms like Torc, Andela, and Upwork are reshaping labor from a fixed cost to a fluid capability. The question is no longer 'Who do we employ?' but 'Who can we access?' Forward-thinking companies are embracing dynamic talent ecosystems. They're dissolving the boundaries between internal and external contributors, assembling purpose-driven teams from a global pool of expertise. They're not just filling roles. They're orchestrating skills. And that orchestration only works when leaders let go of perfection, embrace iteration, and build environments where trust and autonomy can flourish. Leadership today isn't about having the plan. The pace of change is too fast, and the problems are too complex. What matters now is curiosity. The most effective leaders aren't heroes; they're curators. Like great editors or museum directors, their job is to discover, elevate, and connect. It's about shaping the conditions for others to do their best work. This approach demands humility. It means listening more, interrupting less, and creating systems where freelancers, full-timers, and AI agents alike can contribute meaningfully. It's not about owning every answer. It's about asking better questions. One of the biggest hurdles to this mindset shift is fear, especially fear of AI. Leaders often ask, 'Will it replace me?' Replace my team? The better question is: what can it amplify? When we stop seeing AI as a threat, we begin to see it as a teammate. It can process data, simulate outcomes, and streamline workflows. But it can't connect unseen dots. It can't empathize, imagine, or lead. At Harvard Business School, our research on cybernetic teammates reveals that hybrid teams, comprising AI paired with human talent, consistently outperform either AI or human talent alone. However, to harness that potential, leaders must relinquish traditional workflows and learn to lead at the intersection of intelligence and intuition. Letting go isn't surrender. It's space-making for people, for ideas, for possibility. It's about shifting from command to co-creation, from headcount to capability, from ownership to access. The future belongs to companies that treat talent as a network, not a department, that invest in open platforms as core infrastructure, not side experiments, and that see flexibility not as a perk, but as a principle. So here's the challenge. Let go of one decision a day. Invite outside talent into one project, and pilot one AI-human collaboration. Redesign one role around outcomes, not ownership. In this era of work, access often beats ownership. Curation beats control. And letting go isn't the end of leadership. It's where real transformational leadership begins.
Yahoo
03-06-2025
- Business
- Yahoo
SmartBear Strengthens Executive Leadership Team with Amazon and Atlassian Veterans to Drive Global AI-Powered Growth
Six-time CMO Kelly Wenzel and global CRO Martin Musierowicz join to accelerate SmartBear's next phase of innovation and worldwide growth SOMERVILLE, Mass., June 03, 2025--(BUSINESS WIRE)--SmartBear, a leading provider of software quality and visibility solutions, has appointed Kelly Wenzel as Chief Marketing Officer and Martin Musierowicz as Chief Revenue Officer. Kelly brings a track record of driving growth at Andela and Amazon Alexa, whose global developer communities reach nearly half a million technologists worldwide. Martin spent seven years at Atlassian, one of SmartBear's key partners, where he scaled the company's worldwide channel sales from $25 million to over $1.3 billion. Together, their leadership will accelerate SmartBear's AI-powered transformation to help developers deliver high quality software at unprecedented speed. "Kelly and Martin bring exactly the proven leadership we need to advance our mission," said Dan Faulkner, CEO of SmartBear. "Their shared commitment to customer-obsessed growth and scalable innovation will strengthen our ability to deliver exceptional value to our customers and partners around the world as we enter this next phase of AI-driven development, where software quality has never been more essential." Martin brings more than two decades of experience in global sales and go-to-market leadership. He played a pivotal role in building Atlassian's partner ecosystem, transitioning to a SaaS subscription model and supporting Atlassian's IPO and continued growth as a public company. As CRO at Keyfactor, Martin scaled revenue from $32M to $130M ARR by operationalizing the sales and channel GTM model. Early in his career, he held sales leadership roles at IBM and Alfresco. "SmartBear's commitment to visibility, automation, and ethical AI resonates with my passion for customer-obsessed growth," said Martin Musierowicz, CRO of SmartBear. "Together with Kelly, we will build a unified growth engine that delivers value at every stage of the software lifecycle." With more than 30 years of experience, in addition to Andela, Kelly has led marketing for high-growth startups like Contently, Basis, Tideway Systems, and DataSynapse, as well as scaled global enterprises like Amazon Alexa and Amazon Pay. A career B2B tech leader, she brings deep expertise in complex B2B2C and marketplace models. Known for building go-to-market strategies that drive revenue and brand differentiation, Kelly is a recognized change agent who creates scalable teams, processes, and infrastructure. "SmartBear has an unprecedented opportunity to define how development teams build software in the AI era," said Kelly Wenzel, CMO of SmartBear. "I'm here to accelerate that transformation and create experiences that drive growth, category leadership, and advocacy." SmartBear is hiring in sales and marketing. For open positions, visit: About SmartBear SmartBear is pioneering innovation in software quality, embracing AI's transformative potential. The company's powerful solution hubs, including SmartBear API Hub, SmartBear Insight Hub, and SmartBear Test Hub, featuring HaloAI, give software development teams around the world visibility and automation that provide end-to-end quality. SmartBear is trusted by over 16 million developers, testers, and software engineers at 32,000+ organizations – including innovators like Adobe, JetBlue, FedEx, and Microsoft. With an active peer-to-peer community, SmartBear meets customers where they are to help make our technology-driven world a better place. The company is committed to ethical corporate practices, including responsible AI that integrates accountability and transparency across its technology stack, and to social responsibility, promoting good in all the communities it serves. Learn more at or follow on LinkedIn, X, or Facebook. All trademarks recognized. View source version on Contacts Tracy WemettBroadPR+1-617-868-5031tracy@ Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Forbes
25-03-2025
- Business
- Forbes
Crowdsourced Wisdom: How AI Labs Are Tapping Contest Data To Build Smarter Models
AI labs are using crowdsourced contest data to infuse human creativity into smarter, more adaptable ... More models. Artificial Intelligence (AI) is evolving at a breakneck pace, fueled by large language models (LLMs) that devour vast amounts of text and code from across the internet. Yet, as AI Labs search for the next competitive edge, they've begun to realize something remarkable: the most transformative insights come directly from the nuanced, creative, and often untapped depths of human problem-solving. Rather than relying solely on curated repositories or scraping the internet at scale, forward-looking organizations are turning to crowdsourcing platforms such as Wazoku's Data as a Service (DaaS), Codewars (part of Andela), and Topcoder. These platforms host historical contest data—real human-generated solutions to real problems—and provide a treasure trove of 'in-the-wild' problem statements and solutions. This data captures the very essence of human intelligence at work: creativity, collaboration, and iterative Crowdsourced Data Matters AI models depend on high-quality training data. If the only information we feed them is static or generalized, we risk producing static, generalized models. Instead, when LLMs learn from dynamic human interactions, through solutions crafted by global teams of expert solvers, they can capture the diversity of thought and resourcefulness that only humans can deliver. Simon Hill, CEO of Wazoku, has seen this phenomenon firsthand: 'As we get to the next evolution of language models, the data we need to start bringing in to train the machine better is just data that's harder to find. Whether it's tacit data that isn't yet codified or analog data that we don't even know exists, that's where you need a globally diverse but highly skilled network of people. That is exactly where crowdsourcing plays.' What Hill points to is a fundamental shift: AI Labs aren't just mining readily available digital text; they are seeking expert, experience-based, and context-rich data. The Power of Human Iteration The Codewars platform, part of Andela, exemplifies how contests can surface world-class coding solutions. It invites developers of all skill levels to solve programming challenges in multiple ways, and then upvotes the most effective approaches. Carrol Chang of Andela, which oversees Codewars, puts it succinctly: 'The ironic thing about synthetic intelligence is that the best kind is built on the best human intelligence, and that's what the Codewars platform was built to draw out. People come to Codewars because they want to improve their mastery of coding. Our slogan is mastery through challenge. You have human coders answering the same coding challenge in hundreds of different ways, and the community votes up the best answers… all of that is a gold mine.' Chang's insight underscores that these solutions aren't just theoretical examples—they're dynamic, tested, and vetted by other practitioners. This style of iterative improvement mimics how real innovation occurs in the wild: through trial, feedback, and refinement. Traditional training sets—like static text or curated code repos—lack that valuable, iterative community input. Surfacing Hidden Insights One of the most significant hurdles in AI is finding data that represents a breadth of perspectives, cultures, and creative approaches. According to Hill, 'most of the world's data is still locked inside human minds.' Even if extensive text archives exist, not all best practices or novel ideas make it into neatly formatted repositories. Often, it's only through competition or collaboration that these nuanced insights emerge. That's where platforms like Wazoku's DaaS come in. By connecting organizations with diverse, global solvers, Wazoku can unearth latent information. AI Labs can then harness that data to train models capable of performing specialized tasks, from designing innovative products to improving coding efficiency. How Crowdsourced Data Stacks Up Against RLHF Increasingly, developers of large language models turn to Reinforcement Learning from Human Feedback (RLHF) to fine-tune and align their models. Yet crowdsourced data can sometimes be even more valuable than RLHF, because it originates from broader, more organic interactions rather than feedback from a smaller, curated group of annotators. This broader lens on real-world problem-solving captures a richness of creativity, debate, and iteration that helps models learn more versatile and context-sensitive solutions. The Future of Contest Data While historical datasets are already proving invaluable, Tony Jefts of Topcoder highlights the growing value of future contest data: 'Every new challenge that goes live generates a set of fresh ideas, codes, and approaches, and these 'in-the-moment' solutions are just as important, if not more than, the archived solutions,' Jefts explains. 'It's a continuous process of problem-solving, and each competition becomes another building block for training more adaptable, future-proof AI models.' In other words, the competitions themselves—not just the archived solutions—will produce new training sets that will be just as (if not more) important than what's been gathered so far. The continuous loop of 'challenge → diverse solutions → refined data → updated LLM' fosters a positive feedback cycle that keeps AI relevant and continuously improving. It's not just about unlocking old data; it's about co-creating new data that captures the evolving frontier of human knowledge. A Human-Machine Symbiosis We often think of AI and humans in opposition—one replacing the other. But as these crowdsourcing platforms prove, the most significant AI models may be the ones that most effectively leverage human creativity. In this hybrid model, humans provide the experimentation, variety, and real-world insights; the AI aggregates these solutions, learns patterns, and refines capabilities. 'Human plus machine is where the real value is,' Hill reminds us. 'Why not use the human to accelerate the training of the algorithm and achieve better outcomes for everyone involved?' Strategic Considerations for Organizations Crowdsourced data from historically rich contest platforms offers AI Labs a potent way to train more adaptive, creative, and reliable LLMs. By capturing the dynamic and diverse nature of human problem-solving, these platforms provide a steady stream of high-impact insights that traditional data sources simply can't replicate. Crowdsourced platforms such as Codewars, Topcoder, and Wazoku's DaaS are poised to fuel the next wave of AI innovation, reminding us that, ultimately, people remain the most crucial input in the AI equation.
