I started Thriving Springs last year in April. I'm the CEO of this learning platform, which uses AI to make learning and content creation easier. Before this, I spent about 13 years at Google, mainly in product management, not HR. I started as an engineer at Oracle, then moved to Fidelity Investments, and later pursued an MBA in entrepreneurship and strategy, not HR.
At Google, I helped build G Suite (now Google Workspace) to improve collaboration for organizations. Even earlier, while at Oracle, I worked on products for HR. Over my time at Google, I got exposure to HR as I worked closely with teams on collaboration tools and taught a course on emotional intelligence rooted in mindfulness.
Teaching this course for five years made me passionate about combining emotional intelligence and technology. So, I decided to start Thriving Springs to merge these passions into an AI-based learning platform.
Yes, it definitely matters. There are business-oriented product managers and more technical ones. For instance, Amazon often hires more business-focused PMs, while Google places a high emphasis on technical skills for PM roles. At Google, every PM has a rigorous technical interview conducted by an engineer.
Different companies have varying priorities for PM roles based on the company's nature and the individual's background. Also, the product itself influences the focus. For example, a compliance product manager might focus less on the user interface (UI), as compliance products are more about following rules than flashy designs, unlike certain FinTech products.
One of my biggest lessons is the power of understanding someone else's perspective. It's linked to emotional intelligence (EQ), which involves self-awareness, understanding relationships, and being aware of context. Being aware helps you navigate your strengths and weaknesses. Understanding relationships allows you to handle them better, especially if they're tense. Contextual awareness helps in creating successful product ideas and gaining senior management's approval.
I believe EQ is crucial for anyone in a people-centric role, whether it's HR, a manager, or even an engineer leading a team. My advice: work on improving your EQ. I highly recommend reading Daniel Goleman's book on emotional intelligence, as it can significantly boost personal and career growth.
It's not about product managers suddenly becoming coders or vice versa. Mastery of a specific skill takes years. Instead, it's about sharing ideas, giving input, or providing feedback across teams without actually taking over roles.
For instance, some individuals might have a strong passion for coding or design. Companies often offer rotation programs where they can temporarily explore these areas without completely switching roles.
However, simply jumping into coding or design without expertise could lead to significant issues. A person unfamiliar with coding might inadvertently create bugs, impacting the user experience. This could be disastrous, especially for platforms like GP, used by millions weekly. Mastery and caution in each domain are crucial for maintaining quality and user satisfaction.
I believe silos often form due to pressure in service-based companies, where rapid delivery is prioritized over innovation. This emphasis on quick execution for profit squeezes the company financially, impacting culture negatively.
Moreover, the business model of these service-oriented companies often fosters transactional relationships rather than deeper, experience-led connections with customers.
Founders play a crucial role too. When starting my own company, I crafted a culture document outlining principles like respect, high emotional intelligence, customer-centricity, flawless execution, and enjoyment at work.
Establishing this early culture mattered, as it guides day-to-day behaviors, setting boundaries for what's tolerated, promoted, championed, and rewarded.
In larger companies, responsibility for upholding culture spreads from founders to leadership tiers like managers, directors, and VPs. Google's famous principle of 'do no evil' reflects the company's enduring culture, even as it scales to a vast workforce.
I firmly believe that culture takes precedence over strategy, a sentiment reflected in my work at Thriving Springs. While focusing on emotional intelligence in learning, our aim is to instill a high EQ culture through our platform. However, it's crucial for leadership to drive this top-down approach to maintain a company's culture, which can significantly determine its success or failure.
Teaching the EQ course at Google sparked my interest in emotional intelligence's impact on career growth. As I improved my EQ, I noticed faster promotions and increased appreciation, recognizing EQ as a powerful skill.
Seeing leaders like Satya Nadella celebrated globally for qualities like empathy, a key aspect of EQ, fueled my passion for the subject. The rise of AI also intrigued me as one of the most significant disruptions in technology.
I recognized AI's potential to revolutionize learning, addressing the longstanding issue of poor engagement and unclear ROI in workplace learning investments. Combining my passion for EQ with AI, I envisioned a platform to help people develop skills more effectively through personalized, engaging, and AI-enhanced learning experiences.
Leaving Google wasn't easy, but I was driven by this passion and sense of purpose. Pursuing this path became my calling. Securing funding from top VCs and angel investors enabled me to set up the company and embark on this journey focused on transforming learning through AI-powered methods.
AI brings personalization to learning, a factor missing in traditional internet-based learning. Its power lies in processing vast amounts of data to create tailored learning paths based on individual roles, projects, goals, and skill proficiency. AI selects relevant content from various sources, like LinkedIn Learning or YouTube, and delivers it in preferred formats, like bite-sized videos or articles.
Furthermore, AI nudges users to complete these learning paths while they work, akin to Grammarly's real-time grammar suggestions in emails. This integration of learning into regular work tasks elevates efficiency and effectiveness.
At Thriving Springs, we've implemented cutting-edge AI features. For instance, AI generates entire video-based courses from prompts, leading to high user adoption due to engaging bite-sized learning experiences. Additionally, our Emotion Intelligence System (EIS) detects empathy and emotional intelligence in emails and Slack messages, enhancing internal communication by helping users send more thoughtful messages.
In summary, AI enhances learning experiences by personalizing content, integrating learning into work tasks, and providing real-time support for improved communication and skill development.
It's a significant industry challenge. Roughly 20–30% of people are self-motivated learners who'll engage more if learning is curated effectively. Then there's a larger group, about 60%, who do the bare minimum required. For them, tying active learning to their daily tasks becomes crucial. Active learning means seamlessly integrating learning principles into their work, like getting real-time suggestions while writing an email or document.
This method, termed micro-learning, feels effortless as it's just-in-time guidance, enhancing absorption while in the flow of work. Our focus is on this future of learning—micro-learning integrated into tasks to boost efficiency. We aim to make learning suggestions part of customer communications and align them with performance management goals set by managers or companies. This alignment with career growth motivates individuals to take learning more seriously.
In essence, our approach targets both self-motivated learners and those less inclined towards learning, aiming to make learning feel seamless and directly linked to career progression.
Certainly! It's essential to combine various elements for effective learning. One key aspect is engagement through diverse content formats like bite-sized videos, animations, and simulations, creating an interactive and game-like experience.
Additionally, accountability matters; aligning learning goals with performance management ensures employees acquire the necessary skills vital for the company.
Another crucial point is integrating learning seamlessly into the work environment. Features like Gmail's auto-suggestion while typing leverage AI to enhance efficiency, demonstrating how applying learning to everyday work processes is the future of effective learning.
AI can aid in enhancing information retention by integrating learning seamlessly into the workflow. When AI provides necessary learning prompts during work activities, it enables continual practice. Repetition through application in real-time scenarios allows concepts to become ingrained, much like muscle memory in sports. As individuals consistently use these learned concepts in their tasks, retention naturally improves without conscious effort.
To effectively retain and apply learned knowledge in the workplace, using the right learning platform is crucial. Relying solely on willpower isn't reliable. Choosing a platform that encourages active engagement is key. Try experimenting socially, like practicing active listening by having speaking and listening exercises in pairs.
Self-assessment is also vital. For instance, observe your active listening in team meetings as a personal challenge. Practicing gratitude, acknowledgment, and mindfulness at work can be beneficial. In our company, we introduced a Slack channel called "appreciation" where team members can express gratitude freely.
Implementing these small initiatives cultivates a culture of gratitude and authenticity. There's no need to enforce participation; it naturally evolves. These fun processes play a significant role in fostering a learning culture and can be highly effective.
Sure, AGI is getting better and smarter. It's helping us with boring tasks so we can focus on more interesting things. But there's a worry about it being misused, especially for tricking people or causing fraud.
This advanced AI could be used in ways that might harm us, like creating fake messages or pretending to be someone else. It's a concern, especially in places like finance, where it could be misused.
Despite these worries, AGI is a step forward in making AI more like humans. While it might replace some jobs, history shows that as technology grows, new jobs are created. So, even though some tasks might change, it's likely that new opportunities will pop up for people.
I believe the integration of AI into learning will deeply intertwine with productivity tools. It's like merging learning with day-to-day work, where various activities happen simultaneously. For example, during a sales call, inputs and insights are processed in real-time, followed by post-call feedback and suggestions right after. This seamless integration will blur the lines between traditional learning and on-the-job tasks, making learning a more integral part of daily work life.
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Note: All views expressed in this interview are personal and not linked to any organization.
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