In this interview, Sapnil Bhatnagar, a passionate product manager and entrepreneur, shares his journey and approach to leveraging technology to address real-world challenges. From finding inspiration during India’s 2020 demonetization to co-founding a travel-tech startup, Sapnil has consistently focused on creating user-centric solutions that simplify lives.
Sapnil provides insights into his early career, the pivotal experiences that shaped his approach to product management, and the strategies he has employed to develop impactful products. We also explore how he identifies opportunities for AI in product management, the challenges of scaling AI adoption, and his vision for the future of innovation in tech.
This conversation offers valuable lessons for product leaders, aspiring entrepreneurs, and anyone curious about building products with purpose and impact.
What factors initially attracted you in product management, especially in the field of digital technology, can you outline a defining experience that shaped your approach?
What’s most exciting about product management is its potential to generate lasting impact. It’s also about unique value drivers one needs to leverage, which span across functions of strategy, creativity, and problem-solving.
Early in my career, I dawned on me that problem-solving in many industries often led to fragmented solutions and a disjointed way of arriving at a conclusion was a common theme. For me this did not sit well, because, in my professional life, I have focused on streamlined digital solutions that would minimize end-user effort and those which create clear, real, and immediate value.
A defining experience for me came during India’s demonetization back in the year 2020. The abrupt transition away from our national currency created significant challenges for millions trying to access usable cash in the nation. At the time, I saw how a fintech startup stepped up with an innovative solution, a digital payment platform that completely avoided the shortage of cash altogether by enabling digital transactions. Watching how this product revolutionized payment systems and eased people’s lives inspired me to explore more.
The experience highlighted the power of building and scaling digital innovation in solving large-scale user problems while surfacing minimal friction for the users, and I wanted to explore more. It was also a defining factor which fueled my interest in building digital products that can offer intuitive, user-friendly experiences for the users. While building, I found that the principles of product management such as championing user empathy, embracing user feedback, and delivering digital customer experience aligned perfectly with my vision. Unlike every new thing, venturing into product management was initially challenging and there was a steep learning curve, particularly when the space spans across vertical functions and the degree of complexity asymmetrically increases while building at scale. But, adopting an Agile mindset really helped, and it has been incredibly rewarding as I’ve grown in the field.
How has co-founding a startup influenced your approach to outlining a product strategy and utilising product development principles?
When I met my co-founder, we immediately clicked on our approach to solving people’s problems and addressing gaps through technology. I am naturally a creative person and I excel at interpreting ideas through images, making concept visualization my strong suit.
While we were ideating and identifying market gaps, I realized the travel industry lacked visual tech and innovation. Avid travelers and enthusiasts often rely on local people to enhance their travel experiences but cannot explore places or experiences digitally firsthand before committing to travel.
I quickly recognized the need for a digital solution to connect local travel experts with travel enthusiasts and that sparked the founder mindset! Once we spent significant time ideating on the problem, the focus shifted to leveraging product sense and building the solution through continuous feedback and iteration.
The approach spanned across three key levers:
Product Roadmapping and Agile Iteration
Co-founding a startup taught me the value of developing and adhering to a clear product strategy and roadmap. While developing the release plan for the MVP, I realized a phased approach to building the platform was a necessity as we were pivoting quite a bit during the early stages.
Prioritizing MVP features like building a user onboarding flow and a traveler-matching algorithm was at the heart of our product and it could not be compromised. While building, I leveraged the Agile principle of embracing frequent failures during early iterations while treating the failures as learning opportunities to refine the vision and provide wiggle room to align it with user needs.
Customer Validation and Signal-Based Pivots
Early in the building journey, focusing on validating the assumptions by directly engaging with future users (travelers and local travel experts) was necessary. Direct feedback is the most important element of building any product as it helps connect with the users on a personal level. Many product teams make the mistake of building in silos, though it can kill your product quite fast.
To avoid the build trap, I ventured into the market and interviewed over 20 individuals who were actively involved in travel communities, before realizing some product pivots were necessary. While the approach was the longer route and usually less taken, it enabled faster time-to-market and accurate signal generation, which eventually helped shape the product roadmap.
Incremental Product Development with User-Centric Design
Our process revolved around continuous ideation, faster prototyping, and rolling product feature for beta testing to ensure our solution effectively addressed gaps in the travel industry. By iterating rapidly based on insights gained from customer surveys and users who signed on the platform, we aligned our platform with real-world expectations, which eventually helped us establish credibility and find the glorious product market fit.
We spent a good six months deeply analyzing the problem to develop a potential digital solution that directly addressed it. By building a product strategy and incorporating features which aligned to user needs, we shaped the MVP of our product. Together with my team we also curated a social media campaign and began marketing the platform through social media channels and eventually ended up getting 4500+ Instagram followers and 700+ signups within weeks of the platform launch. I strongly feel that it was all made possible because we planned the platform development keeping the user as our central focus.
How do you identify the best use cases for AI in product management to achieve maximum impact?
There is a well-known metaphor we often use interchangeably to emphasize the importance of careful planning – “Measure twice, cut once.”
The next big development in the advancement of AI is where we will see a shift from merely experimenting with AI to actually building AI-powered products, but the outcomes that you would expect out of your product would need to be very carefully planned to the finest detail possible. Since AI models are more probabilistic in nature, a Garbage in (rudimentary planning) will lead to Garbage out (rudimentary output).
I believe the best use cases of AI in product development will involve actively leveraging intelligence to enhance the following areas:
Personalization and Recommendation System Development
Personalization is a product vertical that enables a drastic increase in customer satisfaction and prolongs user engagement. We can achieve deeper consumer understanding by integrating user feedback to generate insights which are driven by data, thus supporting our hypothesis of building a personalised user centric feature.
If we look around, we can see that personalization is already playing its part in platforms like Google Ads, Netflix, and many e-commerce sites such as Amazon, Flipkart, and its prevalence is only expected to grow. According to a McKinsey study, personalized user experiences can increase organizational revenues to 1.15x by contributing to user base expansion and reducing churn. Thus personalization and recommendation systems within the product will take over traditional product development principles and will also broaden the overall market capture opportunity.
Prototyping and Customer Validation
Prototyping is among the main functions of product development, as it enables immediate product validation through customer interaction and helps mitigate long-term release challenges. Effective prototyping also aids in forecasting future scaling needs of the platform as teams can foresee which feature set is most used by consumers and where the most amount of product team’s effort must go.
Recently, an AI application called ‘UIzard’ entered the market, enabling rapid creation of visual prototypes. This tool has been a game changer for me, as it allowed me to communicate with my tech team with greater confidence and evidence and a visual representation. I believe this aspect of AI innovation will continue to evolve and improve.
Sometimes, the journey starts small with pilot projects or proofs of concept, and AI is set to revolutionize this space significantly by reducing time to build and increasing efficiency.
Analyzing Pain Points and Bottlenecks
Identifying areas in the product life cycle for automation or prediction is challenging because businesses often lack clarity in their processes, and employees learn as they go, SMEs roll in and out of the organization so it is not always possible to have a knowledge store, which eventually leads to organizational bottlenecks.
Automating tasks like data entry, triaging, and feedback analysis saves time and removes bottlenecks, thus enabling product teams to focus on innovation. I believe this is the area where AI can improve decision-making by providing data-driven insights, integrating AI in these meticulous processes can also enhance the product team’s knowledge base gradually.
Over time, increasing the use of AI in the product development lifecycle will be an organizational necessity to reduce suboptimal decision-making.
What are the biggest challenges for product-led organizations in adopting AI at scale?
With any technology and digital transformation, challenges are evolutionary, but an organization’s ability to navigate these complexities makes them a winner. The journey of implementing product-led principles in the product development process is no exception.
Organizations will encounter complex hurdles that span across technological, strategic, and human dimensions, but the ability to stay afloat will differentiate. The founders who are also product people will encounter:
Talent and Knowledge Gaps
Acute shortage of AI-skilled professionals, which at its core will limit their capability to conceptualize and execute sophisticated AI solutions. On a personal note I had to scale my knowledge of AI and Machine Learning techniques to better understand the innovation space and integrate the development of recommendation engine into our travel experience platform. This challenge will get easier as AI documentation gets better and becomes more accessible, but upskilling will be a key theme.
Data Ecosystem Complexity
The effective implementation of AI hinges on robust data foundations. When we speak about enterprise-grade tech, it is synonymous with enterprise-grade complexity. Most enterprises grapple with fragmented, inconsistent, and low-quality data repositories. Unstructured documentation further complicates this narrative, thus undermining the potential of AI projects. As organizations expand and grow, It will be more important to maintain a common understanding of the technology estate within product teams.
Technological Infrastructure Limitations
AI needs computation power. The most prominent integration challenge includes the integration of legacy systems and outdated technological architectures. Organizations will also find it difficult to acquire skilled resources who will be well positioned to understand their legacy tech. Hence, product organizations will need to develop a strategy to modernize their infrastructure so that the emerging AI capabilities that are cost effective can replace their legacy tech, ensuring a seamless technological transformation.
Though this is easier said than done!
How do you use data to inform product decisions, especially where traditional KPIs of product development may not apply?
Many times I refer to the Gartner Hype Cycle for AI innovations as a reference. Many AI advancements are still at the conceptual level when it comes to application centric AI and we see that it results in false expectations, AI applications do generate excitement within the product teams for what can be possible, but these advancements have not fully matured. The key here is to make AI a subtle enabler which can help product teams work at a faster pace and focus on complex tasks. I believe the intelligence of AI systems should be veiled so the end-user experience is not muddled with AI features and the product ends up being classified as a feature factory.
By subtle entanglement of AI in existing products more accurate product decisions will be made as humans will be in the loop of this decision making.
Another value I stuck to while developing our travel experience platform was staying focused on core development work. We had many ideas that distracted us, so we were always chasing moving targets and were shifting our focus to shoehorning tactical solutions. I believe that is a big mistake. It’s important in every product team to insulate themselves from over-engineering and avoid feature creep. At some point, your product’s performance will signal you and product teams will have to embrace killing features that aren’t performing for their business.
Looking ahead, how do you envision AI’s role will evolve in product development, and are there trends that particularly excite you?
It comes as no surprise that AI is going to be the next big thing. As more users get comfortable with AI, we will see even bolder innovations. I believe we are on the cusp of seeing some truly groundbreaking products in the travel tech space, where experiences and content creation will be integrated on one singular platform.
The biggest pain point for Connecting Traveller is to automate itinerary development and its digital management. We spend a lot of time curating itineraries for business leads, which drains our technology development bandwidth. To find a solution, we are currently experimenting with Jasper AI that can create text content for our platform automatically. Our biggest challenge lies in integrating the same with the core product ecosystem and fine-tuning the output accordingly, since the AI technology stack is pretty immature.
However, As more and more applications, compute power and use cases become accessible to technologists, I believe that businesses are going to be well positioned to derive higher value from their products and they will be able to move from value extraction to value creation in the product space.
What advice would you give to product teams on fostering a culture of innovation and continuous improvement ?
Of course, every product team wants to be the A-Team, but very few actually reach that level. Somehow, I feel first-principles thinking is disproportionately underrated in product teams. This reverse-engineered approach towards problem-solving helps teams to question the root cause of the problem and resists the urge to make assumptions. In my opinion, being methodical and rigorous is necessary for product teams, and should be imposed on whatever product development process an organization must engrave into its product culture. Product teams, as well as founders, would want to encourage living these values inside of the organization. Following such practices with a first principle thought process asymmetrically increases the chance of success of the product.
Continuing from above, product innovation and improvement begin when one is open to constructive feedback and is committed to recording decisions and details down to the finest granular detail possible. All in all, it’s about finding that lightbulb moment for your consumers and being methodical plays a great role in driving innovation.
For example, with Connecting Traveller, in the last 12 months, we pivoted three times, each one has been a direct outcome of first-principles thinking and painstakingly documenting the ‘what ifs’ and allowing our thoughts and ideas to reveal exactly what lay ahead in terms of failures and nail what will work or will not.
I was also working with a mentor at the time who specialized in digital experience design, and working through his advice, learning from his industry knowledge significantly helped refine my product acumen. Sometimes many of us undervalue external opinions and mentor support, but when it comes from the right person, mentorship can be an incredibly powerful tool.
All other stuff is about living these values, and for product teams to put that into practice as part of product culture. Ultimately, fostering a culture of rigor, openness, and adaptability can drive meaningful innovation and we have all seen that happen within our circles time and time again.
