Author: Nataraj Sindam

In a landscape saturated with software solutions and ever-evolving technological demands, effectively marketing a deeply technical product requires a nuanced approach that transcends traditional marketing playbooks. Madhukar Kumar, Chief Marketing Officer at Single Store (formerly MSQL), a cloud-native database powerhouse, recently shared his insights on navigating this complex terrain in a podcast interview. His conversation with Nataraj delved into the intricacies of product marketing, growth strategies, and the evolving role of marketing in a world increasingly shaped by AI.

For Single Store, a company that has garnered over $300 million in funding and serves Fortune 100 clients, the challenge lies in bridging the gap between cutting-edge database technology and the developers and enterprise decision-makers who need it. Kumar’s strategy, built on three pillars – branding, product-led growth (PLG), and product-led sales (PLS) – offers a compelling framework for technical product marketing.

Branding Beyond Buzzwords: The Technical Product Imperative

Kumar emphasizes that branding for technical products, especially those aimed at developers, cannot be divorced from the product itself. While aesthetics and catchy slogans are important, they are secondary to demonstrating genuine value. Developers, he argues, are discerning and pragmatic. They prioritize functionality and technical merit above marketing fluff. Therefore, branding for a database company like Single Store must be product-centric and focus on being “memorable” in a noisy digital world.

This memorability, Kumar suggests, can be achieved through a combination of crisp, direct messaging, a touch of developer-appropriate humor, and, crucially, a clear call to action that encourages product trial. For developers, the brand message must ultimately lead to a tangible experience: “Go try out my product,” not “Come talk to my sales team.” This reflects the bottom-up nature of developer adoption, where hands-on experience trumps marketing promises.

Product-Led Growth: Reaching Developers in Their Natural Habitat

The concept of product-led growth is central to reaching developers. Kumar points out the sheer volume of databases available today, highlighting the challenge of standing out. He emphasizes that Single Store, positioned uniquely between transactional and analytical databases, offers a powerful solution capable of both. However, awareness is the first hurdle.

Traditional marketing methods often fall short when targeting developers. Kumar argues that you cannot simply “market to” or “sell to” developers. Instead, you must engage them where they naturally congregate – online communities, forums, and platforms like Twitter, YouTube, Stack Overflow (despite its current challenges), and Reddit. The strategy is to be present in these “watering holes” and offer solutions when developers are actively searching for answers to their problems.

This approach hinges on a strong product that delivers real value. Kumar stresses the importance of unwavering faith in the product, highlighting his own personal use of Single Store for experimentation. The challenge, he acknowledges, is overcoming the developer preference for open-source databases like MySQL and Postgres. PLG, in this context, becomes about demonstrating superior performance and capabilities through accessible product trials and community engagement.

Product-Led Sales: Navigating the Enterprise Landscape

While PLG focuses on bottom-up adoption, product-led sales targets enterprise buyers through a top-down approach. Kumar underscores the power of customer validation in this realm. He believes that the most compelling value proposition comes directly from existing customers. Connecting prospects with satisfied Single Store users often eliminates the need for extensive marketing pitches.

For enterprise buyers, brand awareness is still necessary, but it serves as a foundation for building trust and credibility. Kumar highlights the “people do what they see other people do” phenomenon. Similar to the neighborly influence on solar panel adoption, enterprise buyers are more likely to consider a product that is already being successfully used by their peers or within their developer teams.

This necessitates a two-pronged approach: nurturing developer adoption within organizations and leveraging account-based marketing to target key decision-makers in enterprises that align with Single Store’s ideal customer profile. The ultimate goal is to create a seamless overlap between developer enthusiasm and enterprise demand, driven by product adoption and demonstrable value.

A Career Forged in Curiosity and Adaptability

Kumar’s own career path, marked by transitions from journalism to engineering, product development, and finally marketing, exemplifies the value of adaptability and a thirst for learning. He describes his journey as organic, driven by a desire to build and create. His willingness to embrace new opportunities, coupled with a diverse background, has equipped him with a unique perspective on marketing technical products.

Marketing Skills for the AI-Powered Future

The rise of AI is transforming every profession, including marketing. Kumar emphasizes that AI tools can significantly enhance productivity, but they cannot replace fundamental skills and experience. He argues that a deep understanding of the “how” behind the “what” is crucial for effectively leveraging AI in marketing.

In today’s landscape, Kumar seeks marketers who are technically proficient, generalists capable of handling diverse tasks, and ideally, specialists in a particular area. This “unicorn” marketer combines broad understanding with deep expertise, allowing them to maximize the potential of AI while retaining strategic insight and nuanced judgment.

Beyond Performance Marketing: Investing in Brand and Inbound

Kumar challenges the conventional wisdom of heavy reliance on paid performance marketing. He argues for a shift towards building a strong brand that drives inbound interest. While acknowledging the immediate gratification of paid campaigns, he questions the quality and sustainability of leads generated through these channels. His preference lies in investing in brand-building activities that cultivate genuine inbound demand and higher-quality leads.

Lessons from Marketing Leaders and the Path Forward

Kumar admires brands like Apple, Webflow, and dbrand for their product-centric approach and cohesive user journeys. He emphasizes the importance of aligning marketing with the entire customer experience, from initial awareness to post-purchase support.

He also notes the changing nature of communication, moving away from overly sanitized, PR-driven messages towards more authentic and direct interactions. While AI can assist in content creation, he cautions against losing the human touch and authenticity that resonate with audiences.

Finally, reflecting on his career, Kumar highlights the importance of prioritizing passion and saying “no” to distractions. He encourages marketers to pursue work that resonates with them deeply, leading to greater satisfaction and impact. His insights offer a valuable roadmap for navigating the complexities of marketing technical products in an increasingly dynamic and AI-driven world.

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The buzz around Artificial Intelligence, particularly Large Language Models (LLMs), is deafening. From boardrooms to break rooms, the promise of AI is touted as transformative, revolutionary, even existential. Yet, beneath the surface of breathless headlines and billion-dollar valuations, a more nuanced reality is emerging. To effectively leverage AI for business advantage, leaders must move beyond the hype and adopt a strategic, long-term perspective.

Pedro Domingos, Professor Emeritus of Computer Science and Engineering at the University of Washington and author of The Master Algorithm, offers a critical yet constructive lens through which to view the current AI landscape. In a recent podcast interview, Domingos, a pioneer in machine learning, cautioned against the inflated expectations surrounding LLMs and urged a more balanced understanding of AI’s true potential – and limitations.

1. Acknowledge Progress, Temper Expectations:

It’s undeniable that AI has made “tremendous progress,” as Domingos acknowledges. Transformers, the architecture underpinning LLMs like GPT, represent a significant leap forward. These models demonstrate impressive abilities in language processing, generation, and even creative tasks. Dismissing them as mere “stochastic parrots,” as some critics do, is inaccurate. LLMs are learning systems exhibiting genuine generalization capabilities.

However, the current hype cycle has outpaced the underlying reality. The narrative that we are on the cusp of Artificial General Intelligence (AGI) thanks to LLMs is, according to Domingos, “farsal.” He warns of a potential “stock market bubble” fueled by unrealistic expectations, echoing historical patterns of technological exuberance followed by inevitable corrections.

For business leaders, this means celebrating genuine AI advancements while avoiding the trap of over-promising and under-delivering. Focus on practical applications and incremental improvements rather than chasing the mirage of near-term AGI. Remember, as Domingos points out, we’ve traveled “a thousand miles in AI,” but there are still “a million miles more to go.”

2. Look Beyond the LLM Hype to Broader AI Capabilities:

The intense focus on LLMs risks obscuring the broader landscape of AI and its diverse applications. Domingos emphasizes that LLMs, despite their current prominence, are “nothing compared to the major applications of AI today.” He points to recommendation systems as a prime example – the algorithms that curate our online experiences, from e-commerce suggestions to social media feeds. These systems, often built on different machine learning techniques, have already profoundly shaped consumer behavior and business strategies for years.

Furthermore, the assumption that deep learning, and specifically Transformers, is the singular path forward is limiting. Domingos argues that “tweaks on Transformers will not get us to human-level intelligence.” He advocates for exploring diverse AI approaches beyond the current deep learning paradigm, emphasizing that true innovation may lie in uncharted territories.

For businesses, this means diversifying AI investments beyond LLMs. Explore applications in areas like computer vision, robotics, optimization, and traditional machine learning techniques. Consider how AI can enhance existing processes and create new value streams across various functions, not just in language-centric tasks. The most impactful AI strategy is likely to be multifaceted and tailored to specific business needs, not solely reliant on the latest LLM breakthrough.

3. Strategic Investment: Prioritizing Diverse Research and Foundational Capabilities:

The influx of capital into AI is unprecedented, yet Domingos questions whether these investments are being directed optimally. He argues that there’s “too much funding of the same narrow kinds of things” and a concerning lack of diversity in AI research compared to previous decades. He advocates for a “thousand flowers bloom” approach, encouraging exploration across a wider spectrum of AI methodologies.

Domingos also highlights the importance of investing in foundational AI research and hardware. He suggests that the next wave of AI innovation may require specialized hardware beyond GPUs, potentially focusing on “primitives for any possible next thing,” like sparse tensors or relational operations. This forward-looking perspective contrasts with the current industry fixation on optimizing existing deep learning infrastructure.

For investors and business leaders allocating capital to AI, Domingos’ insights are crucial. Avoid the allure of chasing the latest hype cycle and instead consider a more diversified investment strategy. Support research into diverse AI approaches, explore hardware innovations that can unlock new capabilities, and prioritize long-term strategic goals over short-term gains driven by hype.

Moving Forward with Realistic Optimism:

Pedro Domingos’ perspective offers a valuable corrective to the current AI exuberance. It’s not a call for pessimism, but for realism and strategic foresight. AI holds immense potential to transform businesses and society, but realizing this potential requires navigating the hype cycles with a clear understanding of both the current capabilities and the long road ahead.

By acknowledging genuine progress while tempering expectations, diversifying AI strategies beyond LLMs, and strategically investing in diverse research and foundational capabilities, businesses can position themselves to harness the true, long-term power of AI. The future of AI is not about chasing fleeting hype, but about building robust, sustainable value through informed and strategic innovation.

Product managers are constantly juggling priorities, navigating market trends, and striving to build products that not only meet user needs but also anticipate the future. In the whirlwind of daily tasks, it’s invaluable to step back and learn from those who have built incredible things, from groundbreaking space missions to cloud infrastructure that powers the internet.

In a recent episode of the Startup Project Podcast, Natraj chats with Kwaja, a seasoned engineer and entrepreneur with a career spanning NASA JPL, Amazon AWS, and now, his own startup, Momento. Kwaja’s journey, filled with experiences ranging from image processing for Mars rovers to building core AWS services, is a treasure trove of insights for product managers. This blog post distills some of the key product management lessons learned from Kwaja’s remarkable career, offering actionable takeaways for PMs at all stages.

Customer Obsession: Beyond a Buzzword, It’s a Way of Life

Kwaja’s journey is deeply rooted in customer obsession, a principle famously championed at Amazon. From his early days at NASA, where he personally used his credit card to leverage AWS for faster image processing, to his time at Amazon AWS and now Momento, the customer has always been central.

“Amazon was a much smaller company… and the customer obsession was really nice because people put themselves in the shoes of the customers and you would get to go work with all kinds of customers around the globe and understand problems in a completely foreign domain that you have no idea about and help them solve deeply technical problems via using the AWS infrastructure.”

For product managers, this resonates deeply. It’s not enough to just say you’re customer-centric; you need to live it. This means:

• Deeply Understanding Customer Pain Points: Go beyond surface-level requests. Dive deep into the why behind customer needs. Kwaja highlights the importance of working with customers in “completely foreign domains” to truly grasp their challenges.
• Empathy and Proximity to the User: Put yourself in your customer’s shoes. Spend time with them, observe their workflows, and actively listen to their frustrations and aspirations.
• Building Solutions, Not Just Features: Focus on solving real customer problems, even if it means building “boring infrastructure.” As Kwaja says, “we sell boring infrastructure, but we take pride in the fact that as more AI applications are formed… people are gonna want more interactivity and that interactivity has to be fuelled by the latest data.” This is about identifying fundamental, enduring needs.

Think Big, Start Small, Iterate Fast: The Amazon Way

Kwaja’s experience at Amazon underscores the power of the “Think Big” leadership principle. While many initially doubted Werner Vogels’ prediction that AWS would surpass Amazon’s retail business, the Amazon leadership team genuinely believed in the potential for massive scale.

“The one thing about Amazon leaders is, you know, they really believe in the think big leadership principle and the leadership principle just says, you know, thinking small is a self-fulfilling prophecy.”

For product managers, this translates to:

• Visionary Thinking: Don’t limit yourself to incremental improvements. Envision the future of your product and industry. What impact can you truly make?
• Breaking Down Big Visions: “Think Big” doesn’t mean building everything at once. It means having a grand vision and breaking it down into manageable, iterative steps. Kwaja’s experience moving the NASA image processing pipeline to AWS using only EC2, S3, and SQS in the early days showcases starting with the essential building blocks.
• Embrace Experimentation: Cloud computing, as Kwaja points out, “was demonetizing infrastructure to make it available for experimentation.” Product managers should foster a culture of experimentation, enabling rapid prototyping and validation of ideas.

Focus: The Unsung Hero of Product Success

One of Kwaja’s key learnings as a founder is the critical importance of focus, especially in the early stages. Initially, Momento’s go-to-market strategy was too broad, targeting every vertical. He learned the hard way that focus is paramount.

“One thing I learned is the focus really matters… once you land a pretty customer, you immediately gotta start looking for look-alikes because when you go to those look-alikes, they know that they’re not the first ones, they’re not the sacrificial lamb that you’re trying with.”

For product managers, this means:

• Defining Your Ideal Customer Profile (ICP): Don’t try to be everything to everyone. Identify your core target audience and their specific needs. Momento found success by focusing on media, gaming, and fintech companies with “spiky workloads and mission-critical needs.”
• Prioritization and Ruthless Scoping: Say “no” to features that don’t align with your core value proposition and target audience. Focus your team’s energy on the most impactful initiatives.
• Look-Alike Customer Strategy: Once you find success with a customer, leverage that to identify and target similar customers. This creates a virtuous cycle of growth and reinforces your product-market fit.

Abstraction and Developer Productivity: Building for the Future

Kwaja’s current venture, Momento, directly addresses a pain point he experienced firsthand at AWS: the complexity of caching solutions. He recognized the need for higher levels of abstraction to boost developer productivity.

“One of the things that we really loved about Dynamo was… you don’t have to learn what instance type, the number of shards, the number of replicas… they just kind of go away with Dynamo and that experience did not exist with any of the caching solutions… they exposed a lot of the knobs to the end-user.”

For product managers, this highlights the importance of:

• Developer Experience (DX): Especially for infrastructure products, prioritize developer ease of use. Reduce cognitive load and abstract away unnecessary complexity.
• Simplicity and Usability: Strive to simplify complex tasks and workflows. Focus on creating intuitive and user-friendly products, even for technically demanding domains.
• Anticipating Future Needs: Kwaja recognized the growing demand for interactive, real-time applications driven by data. Momento is built to address this future need, providing the foundational infrastructure for these applications.

Culture and Team: The Foundation of Success

Throughout the podcast, Kwaja emphasizes the importance of people and culture. From the passionate mission-driven environment at NASA to the customer-obsessed culture at Amazon and the craftsmanship of team building at Momento, people are at the heart of every successful endeavor.

“The people matter, the people matter a lot, and if you have the right team and you know and that team has the right passion, you can accomplish anything.”

For product managers, this underscores:

• Hiring for Passion and Mission Alignment: Seek out individuals who are not just skilled but also genuinely passionate about the problem you are solving.
• Building a Strong Culture: Cultivate a culture of ownership, psychological safety, and customer-centricity. These values, as Kwaja points out, are crucial for fostering innovation and operational excellence.
• Mentorship and Continuous Learning: Surround yourself with mentors and advisors. Embrace continuous learning and encourage your team to do the same.

Embrace the Axioms: Foundational Truths in a Changing World

In closing, Kwaja offers a powerful perspective on the future of technology, particularly in the age of AI. While AI is transformative, he emphasizes the enduring importance of fundamental needs.

“We sell boring infrastructure, but we take pride in the fact that as more AI applications are formed, the undeniable truth, the axioms that are always gonna be true, people are gonna want more interactivity and that interactivity has to be fuelled by the latest data… real-time data and they want it fast. It’s never gonna change.”

For product managers, this is a crucial reminder:

• Focus on Foundational Needs: In the face of rapid technological change, don’t lose sight of the fundamental user needs that remain constant. Interactivity, speed, and real-time data are timeless requirements.
• Build for Enduring Value: Create products that are not just trendy but built on solid foundations and address long-term needs.
• Embrace “Boring Infrastructure”: Sometimes, the most impactful products are not the flashiest but the most reliable and foundational. Investing in robust infrastructure that enables innovation is crucial.

Kwaja’s journey is a testament to the power of customer obsession and a relentless pursuit of solving real problems. By embracing these lessons, product managers can navigate the complexities of product development and build truly impactful products.

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Nataraj is a Senior Product Manager at Microsoft Azure and the Author at Startup Project, featuring insights about building the next generation of enterprise technology products & businesses.

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The technology landscape is in constant upheaval. For entrepreneurs, this environment demands a rare combination of visionary thinking and practical execution. Few individuals exemplify this blend as effectively as the serial entrepreneur Ameesh Divatia who was recently featured on the Startup Project podcast. Across four successful ventures, culminating in his current focus on data-centric security, this founder has not only weathered the tech industry’s storms but consistently leveraged them for growth and acquisition.

His journey, spanning from the networking boom of the late 1990s to the cutting edge of cloud data protection in the era of Generative AI, provides a valuable blueprint for adaptability, market timing, and the enduring principles of building valuable companies. From the heady days of the dot-com boom at Cisco to the complex challenges of securing data in today’s cloud-first world, his insights are essential for founders at all stages – and for leaders guiding established organizations through continuous technological transformation.

The Echo of the Dot-Com Era: The Power of Humility

A particularly insightful moment in our conversation was his reflection on the dot-com boom during his time at Cisco, then the world’s most valuable company. He draws a striking parallel to the current excitement around Nvidia and Artificial Intelligence, observing, “This whole Nvidia story is something that we have lived through.” This isn’t to diminish Nvidia’s achievements, but to offer crucial historical context. “It was Euphoria,” he remembers of the late 1990s, “you would get into the office in the morning and see the stock up six bucks, everybody’s smiling, and we literally thought we could take over the world.”

This experience underscores a vital lesson, especially relevant in times of rapid technological advancement and market exuberance: humility is paramount. When asked for advice for those currently at Nvidia, his response was immediate and direct: “Be humble. That’s it. Just be humble.” This isn’t just good manners; it’s a hard-won lesson from witnessing the cyclical nature of tech dominance. He wisely points out that even established giants like Apple face continuous disruption and evolution. True, sustainable success, he suggests, stems not only from groundbreaking innovation but from a grounded understanding that no market position is guaranteed forever.

Orchestrating the Exit: A Proactive Strategy, Not an Afterthought

Beyond navigating market cycles, our discussion highlighted a strategic approach to company building that prioritizes, rather than shies away from, the idea of acquisition. His advice to aspiring entrepreneurs is refreshingly proactive: “Don’t ever rely on somebody else to find you the exit. It’s something that you have to do over the course of time.” This isn’t about building a company solely to flip it, but rather about strategically positioning your venture for long-term value creation, which often naturally leads to acquisition by a larger entity seeking to expand into new markets or integrate groundbreaking technologies.

He emphasizes the importance of early and consistent engagement with potential acquirers. This doesn’t mean aggressive sales pitches from day one, but a sustained effort to cultivate genuine relationships, openly communicate your unique value proposition, and demonstrate a collaborative and learning-oriented approach. His experience with Lightwire, a silicon photonics company he joined, perfectly illustrates this principle. By proactively engaging with Cisco early in their development, seeking a partnership to help productize their innovative technology, they not only secured crucial investment but ultimately positioned themselves as a strategically vital acquisition target. This proactive, relationship-driven approach stands in stark contrast to a passive stance, where founders might simply hope that an attractive exit will materialize organically.

Beyond the Tech: Focus on Commercial Viability

For founders with a deep engineering background, a common misstep is assuming that revolutionary technology alone will pave the road to success. Our interviewee offers a critical correction to this often-held belief: “As an engineer founder entrepreneur, you always tend to fall back on the fact that the technology will sell itself. That is seldom the case.” While cutting-edge technology is undoubtedly a foundational element, it is simply not enough without an equally intense focus on understanding market needs, validating product-market fit, and developing effective sales and marketing strategies.

He readily acknowledges that earlier in his own entrepreneurial journey, he leaned too heavily on a technology-centric worldview. Through experience, he learned the critical importance of deeply understanding the commercial landscape, clearly articulating a compelling value proposition that resonates with customers, and building a robust and scalable business model that attracts both users and investors. This fundamental shift in perspective – from technology-first to business-first (while still valuing technology) – is essential for engineer-founders to successfully transition from technologists to effective business leaders, recognizing that, ultimately, commercial viability is the key determinant of long-term startup success.

Data-Centric Security: Securing the Next Frontier

His current company, Baffle, is tackling the rapidly evolving landscape of data security, a domain undergoing radical transformation in the cloud era and with the rise of Generative AI. He articulates a compelling vision for “data-centric protection,” arguing that traditional network-centric and even identity-based security approaches are becoming increasingly insufficient in the face of modern threats and distributed data environments. In a world where sensitive data increasingly resides in complex, multi-cloud environments, and where identity perimeters are constantly challenged and breached, securing the data itself – at the most granular level – becomes the ultimate and most effective line of defense.

This proactive, data-first security paradigm is particularly prescient and crucial in the context of Generative AI. The immense power and potential of these transformative technologies hinge on access to and analysis of vast datasets, often requiring organizations to share and collaborate with data in ways that were previously considered too risky or simply impractical. Data-centric security, he argues, provides the necessary framework to enable secure data sharing and collaboration, fostering innovation and progress while simultaneously maintaining stringent data privacy, regulatory compliance, and, most importantly, customer trust. This forward-thinking perspective firmly positions Baffle at the forefront of a critical security evolution, proactively addressing a challenge that will only become more pressing and complex as AI adoption rapidly accelerates across industries.

Enduring Principles for Startup Success

Throughout our insightful conversation, several core principles consistently emerged as foundational to his repeated entrepreneurial successes:

• Unwavering Customer Obsession: A relentless focus on deeply understanding customer needs and building solutions that directly and effectively address their most pressing pain points.
• Strategic and Proactive Networking: A deliberate and consistent effort to build meaningful relationships with potential acquirers, strategic partners, and key industry players, proactively laying the groundwork for future opportunities and potential exits.
• Adaptability and Continuous Learning: An inherent willingness to constantly learn, adapt to rapidly changing market conditions and technological landscapes, and to strategically pivot business strategies and product roadmaps as needed.
• Building Exceptional Teams: A dedication to assembling high-caliber teams of talented individuals who are not only deeply technically proficient but also fully aligned with and passionately committed to the company’s shared vision and mission.
• Strong Commercial Acumen: A recognition that groundbreaking technology must always be coupled with a robust understanding of market dynamics, effective sales and marketing strategies, and a sound and scalable overall business strategy to achieve lasting success.

In a technology world often characterized by fleeting trends and short-lived companies, this serial entrepreneur’s journey provides a valuable reminder of the enduring principles of sustainable value creation.

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The entertainment industry is often viewed through the lens of Hollywood blockbusters and streaming giants. Yet, a colossus quietly dominates in revenue and innovation: gaming. Outpacing movies, music, and books combined, the gaming industry is not just entertainment; it’s an economic engine. For businesses seeking to navigate disruption and understand future consumer trends, the gaming world offers a wealth of strategic lessons. In a recent interview, Ian Bateman, CEO of cloud gaming startup High Score, shared key insights into this often-misunderstood market.

Here are five critical takeaways about the gaming businesses:

1. Content is King, Ecosystem is Queen.

Google’s failed Stadia venture provides a stark reminder: technology alone isn’t enough. Despite Google’s infrastructure and resources, Stadia faltered due to a critical lack of compelling content. As Ian noted, “ultimately Stadia’s failure boils down to games… in gaming at the end of the day it’s all about the games.” Stadia’s limited game library and the difficulty of porting titles to its platform created a content desert.

The Lesson: In gaming, content is paramount. A robust and constantly refreshed content ecosystem is crucial for user engagement and long-term success. Focus on content acquisition and curation as much as – technological innovation.

2. Compatibility Trumps Proprietary Systems.

Stadia’s closed ecosystem, requiring games to be specifically ported to its platform, proved to be a major impediment. In contrast, High Score is leveraging the vast existing library of Windows-compatible PC games, accessible through platforms like Steam. This approach immediately offers users a massive content catalog without relying on developers to create new, platform-specific versions.

The Lesson: Prioritize compatibility and interoperability. In fragmented markets, offering seamless access to existing content and platforms can be a powerful competitive advantage. Avoid walled gardens that limit user choice and content availability.

3. Democratization Drives Innovation.

The gaming industry is experiencing a indie game boom, fueled by increasingly accessible game engines like Unity and Unreal Engine. These tools empower smaller teams and individual developers to create high-quality games, fostering innovation and experimentation outside the confines of large studios. This mirrors trends in other industries, where democratization of technology empowers smaller players to disrupt established markets.

The Lesson: Embrace and leverage democratizing technologies. Lower barriers to entry foster innovation and create new opportunities for smaller, agile players to compete and disrupt established giants. Look for ways to empower individual creators and smaller teams within your own industry.

4. Ride the Right Platform Wave.

The PC gaming market, while massive, is heavily Windows-centric. This creates a significant accessibility gap for users of macOS and ChromeOS. High Score is directly addressing this by offering cloud-based Windows gaming PCs, effectively bridging the compatibility gap and unlocking the vast PC game library for a wider audience.

The Lesson: Identify and capitalize on dominant platforms. Understanding platform dynamics and addressing accessibility gaps can unlock significant market opportunities. Look for ways to leverage existing infrastructure and ecosystems rather than always building from scratch.

5. Gaming is the New Media Frontier.

Major media and tech companies, including Netflix, YouTube, and LinkedIn, are increasingly investing in gaming. This isn’t simply a fleeting trend; it’s a recognition of gaming’s immense market size and its evolving role as a primary form of entertainment and social interaction. Gaming is no longer a niche; it’s becoming central to the digital media landscape.

The Lesson: Recognize the growing importance of interactive entertainment. Gaming is not just for gamers; it’s shaping the future of media consumption and user engagement. Explore opportunities to integrate game-like elements, interactive experiences, and gamified strategies into your own business to capture attention and drive engagement.

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For years, the promise of “no-code” development has been whispered in the tech industry, often met with a healthy dose of skepticism. Could software development truly be democratized, moving beyond the realm of specialized engineers? Like many, I’ve been cautiously optimistic, observing various iterations of no-code tools emerge, each with varying degrees of success. However, a recent conversation with Prakash Chandran, founder of the no-code backend platform Xano, has shifted my perspective from cautious observer to genuine believer.

Chandran, a seasoned product and UX leader whose career spans Google’s early days (think Picasa and Google Calendar) and the tumultuous startup trenches, didn’t arrive at no-code through abstract theorizing. His journey was forged in the fires of practical experience, recognizing a persistent, often overlooked bottleneck in software creation: the backend. During our discussion on the Startup Project podcast, he articulated a frustration many product-focused individuals quietly harbor: the opaque and often cumbersome nature of backend development.

The Backend as a Black Box

Chandran’s experience resonated deeply. As someone deeply invested in the product side – the design, the user experience, the core functionality – he felt a tangible disconnect from the underlying engineering process. “You have to pay for an expensive engineer,” Chandran explained, “They’re kind of like a car mechanic. If they tell you something is going to take a month and tens of thousands of dollars, you just kind of have to believe them.” This sentiment highlights a crucial, often unspoken tension in product development. Product leaders, designers, and even business stakeholders are frequently reliant on engineering timelines and cost estimates that can feel arbitrary, lacking transparency and direct control.

This isn’t to diminish the crucial role of backend engineers, but rather to acknowledge an evolving challenge. As software systems grow more intricate, distributed, and demanding, the backend – the unseen infrastructure powering every application – has become a domain of increasing specialization and complexity. Even for seasoned full-stack developers, navigating the ever-shifting landscape of backend technologies can feel like an uphill battle. The initial promise of cloud computing to abstract away infrastructure complexities has, in some ways, been replaced by a new layer of abstraction that can be just as daunting to navigate. The very act of starting a new application, even a relatively simple one, can involve a steep learning curve and a significant investment of time and resources simply to establish the foundational backend.

Xano’s No-Code Solution: Reclaiming Simplicity and Scale

Chandran’s solution, embodied in Xano, is a radical proposition: a fully scalable, enterprise-grade backend platform that requires absolutely no code. This isn’t another iteration of website builders or simplified database tools. Xano, as Chandran describes it, represents a “new part of no-code,” engineered from the ground up to handle the demands of production applications, not just prototypes. The key differentiator lies in its singular focus: the backend. While other no-code platforms often attempt to be full-stack solutions, Xano deliberately concentrates on the server, database, and API layers, allowing users to connect it to any frontend they choose. This focused approach, Chandran argues, allows for both unprecedented simplicity and robust scalability.

During our conversation, Chandran emphasized that Xano isn’t just about simplifying the interface; it’s about fundamentally rethinking the development process. He positions Xano as a “visual programming language,” one that empowers users to articulate complex application logic without writing a single line of code. This isn’t about dumbing down development; it’s about making the core concepts of software engineering – variables, loops, conditionals – accessible to a broader audience through a visual, intuitive interface.

Empowering the Citizen Developer and Embracing AI

Xano’s target user is the “citizen developer,” a Gartner-defined persona representing product owners, system thinkers, and business experts who understand the intricacies of application logic but lack traditional coding skills. These are the individuals who possess deep domain expertise and a clear vision for software solutions but have historically been reliant on engineering teams to translate their ideas into reality. Xano aims to bridge this gap, empowering these citizen developers to directly build and deploy their own applications, reclaiming control over the backend and accelerating the entire development lifecycle.

Looking ahead, Chandran is keenly focused on the intersection of no-code and artificial intelligence. He doesn’t envision AI replacing no-code platforms, but rather as a powerful synergistic force. He suggests AI could serve as a generative tool, creating initial application scaffolding, while platforms like Xano provide the crucial visual canvas for refinement, customization, and the infusion of human intention. This partnership, he argues, will unlock a new era of software creation, where AI augments human creativity and no-code platforms provide the accessible, powerful tools to bring those visions to life.

Beyond the Hype: A Glimpse of the Future?

My conversation with Chandran left me with a sense of optimism I hadn’t anticipated. Xano isn’t just another no-code tool; it represents a potentially significant shift in how we approach software development. By squarely addressing the complexities of the backend and empowering a new generation of “citizen developers,” Xano is challenging the traditional paradigms of software creation. While the no-code space has often been associated with limitations and compromises, Xano’s architecture and vision suggest a future where powerful, scalable applications can be built with unprecedented speed and accessibility. It’s a future where product leaders and business innovators can reclaim control over the entire development process, moving beyond the backend bottleneck and focusing on what truly matters: building impactful, user-centric solutions. Whether Xano will fully realize this ambitious vision remains to be seen, but my conversation with Prakash Chandran has certainly made me a believer in the transformative potential of no-code backends, and the exciting possibilities they unlock.

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When Shanker left a senior post at Symantec to found Assembly, he thought he understood hard problems. He had managed billion‑dollar product lines, helped design the iPhone 3G modem, and spent years mapping out Symantec’s IoT strategy. Yet the moment he stepped away from corporate infrastructure—“me, myself, and PowerPoint slides,” as he jokes—he discovered something tougher: bringing order to the chaotic, heterogeneous world of connected devices that power hospitals, factories, and entire cities.

Today, Asimily is one of Gartner’s highest‑ranked vendors for medical‑ and industrial‑IoT security, but the path there reveals as much about the state of critical‑infrastructure security as it does about start‑up grit. Below are five takeaways from Shankar’s recent appearance on Startup Project podcast—and why they matter to anyone watching the next wave of connected systems.

1. Healthcare Is the Ultimate “System of Systems”

Asimily’s origin story begins in hospitals, where device diversity and regulatory complexity collide. A single facility may run MRI scanners, infusion pumps, HVAC controllers, and paging systems—all from different manufacturers, all speaking their own arcane protocols, and all subject to HIPAA or GDPR restraints that forbid tampering with patient data. Shankar calls it “the most challenging environment in any vertical.” By focusing first on healthcare, Asimily forced itself to solve for the hardest edge cases—passive network monitoring that never interrogates a life‑critical device, on‑prem deployments for data sovereignty, and integrations with everything from CMDBs to SIEMs. If it works in an ICU, it will probably work anywhere.

2. Visibility Still Beats AI Hype … But Context Is King

Five years ago hospital CISOs wanted one thing: a real‑time asset inventory. They still do, yet visibility alone can no longer keep pace with ransomware crews that treat unpatched ultrasound machines the way pickpockets treat unlocked cars. Asimily’s answer layers device‑aware context over classic network telemetry: Which vulnerabilities are actually reachable from a given subnet? How would malware laterally move through an OR? When every medical device vendor warns that patching voids the warranty, prioritization and compensating controls—micro‑segmentation, firmware‑level mitigations, or even simple network throttling—matter more than a tidy CVE list. That depth of analysis, Shankar argues, is where Assembly now outpaces look‑alike scanners.

3. Smart Cities Are Less Sci‑Fi, More Plumbing

“Smart city” once conjured Jetsons‑style streets that anticipate traffic and locate parking spots. The reality, Shankar says, is prosaic: wastewater plants, traffic lights, environmental sensors—all suddenly IP‑addressable. At 5 percent connectivity the risk felt hypothetical; at 40 percent it is an urgent operational question. A stalled sewage pump or frozen signal grid cripples civic life faster than a consumer website outage. Asimily ports its healthcare playbook here: passive collectors, cloud or fully on‑prem analytics, and APIs that enrich the municipality’s existing SOC. The lesson is simple: critical infrastructure rarely needs bleeding‑edge features; it needs tools that respect uptime, safety, and long equipment lifecycles.

4. Hardware Is Just a Delivery Vehicle

Despite shipping its own appliance, Asimily thinks of itself as a pure‑software firm. Off‑the‑shelf boxes (or virtual machines) sit inside a customer’s network, siphon mirrored traffic, strip out any patient or personally identifiable information, and forward only device metadata for analysis. Where policy forbids the cloud, everything runs on‑prem. That architectural choice—commodity hardware plus software smarts—keeps margins healthy while side‑stepping import‑control nightmares and silicon shortages. It also lets Assembly pivot quickly when customers ask for AI‑assisted incident forensics or automated compliance reports; new modules roll out as firmware updates, not forklift refreshes.

5. Sales Motions Mature, but Trust Stays Personal

Shankar closed Asimily’s first deal himself, armed with a demo and a handful of Symantec‑era relationships. Today the company runs a channel‑first model, complete with solution engineers and VAR partners. Yet decision makers remain largely the same: CISOs who balance MRI uptime against cyber risk, wastewater supervisors who fear midnight phone calls, operations chiefs who know that a security product which bricks a CT scanner on day one will be ripped out on day two. For all the talk of AI copilots and self‑healing networks, enterprise buyers still reward vendors that obsess over patient safety, regulatory nuance, and the gritty details of packet capture in a 15‑year‑old PLC.

Asimily’s roadmap hints at where industrial security is heading. New modules for configuration control and richer forensic replay will appear this year, and the company is quietly weaving generative‑AI techniques into both engineering workflows and customer‑facing features. Shankar is cautious—no customer data touches public LLMs—but optimistic that the technology can shrink incident‑response time without adding headcount.

The bigger story, though, is that critical‑infrastructure security is far from “solved.” Hospitals, factories, and cities are still climbing Maslow’s hierarchy: first inventory, then analytics, then autonomous defence. Ten years from now, winners will be the platforms that layered innovation upon pragmatic foundations—partners who remembered that a traffic signal or infusion pump is not an endpoint but, quite literally, a lifeline.

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