I first met Steve in 2011, when we were still less than a two year old company, Nutanix. I was young, but he was even younger, probably 10 years younger — a fountain of youth for me as we both grew together, learning from each other, making mistakes along the way. We were hustling for early customers, creating nascent benchmarks, jostling with naysayers on Twitter, defining an MQ with Gartner, losing debates with the skeptics, and of course, winning hearts and minds of innovators and early adopters.

Company building is hard. Finding people who believe in building is even harder — because you have to learn to reset the clock, assume once again that you haven’t achieved anything, and don’t know much. Then you start learning again, having made yourself vulnerable in the new arena, with a new problem statement, new competitors, new peers, and new technologies.

Steve has done exactly that: reset the clock with DevRev after having spent a decade at Nutanix converging IT infrastructure, making machines invisible. He’s back to converging again, this time business infrastructure that is hopelessly fragmented, dispersed, and extremely complex to stitch together.

A 5-people startup is elegantly simple. It has a couple of founders, a few early developers and designers, and a handful of early adopters. Everyone knows the product, and everyone communicates with the customer. They don’t just communicate, they collaborate with the end user, and mostly in real-time as technologies improved this past decade. Everything is real-time and continuous — integration, deployment, nudges, onboarding, feedback… and collaboration.

As companies grow, clouds begin to emerge: an engineering cloud, a production cloud, a support cloud, a marketing cloud, a sales cloud, a customer success cloud, an analytics cloud, and of course, a collaboration cloud separate from all business systems. Everyone is working hard — jostling for growth, trying to contain customer churn — being on the Zoom treadmill early mornings and late evenings, updating Slack channels, responding to emails, being in unnecessary meetings for fear of missing out, and hopelessly searching for answers to do what matters most. The customer and the product are forever lost. The energy vampire of busy work, especially with remote peers, has raised its ugly head.

Simplifying something this fragmented takes immense energy. Manoj and I are so grateful for the early DevRevelers to have put so much effort to define this new paradigm of business software that makes the back office customer-centric, and the front office product-centric — helping businesses support users (not tickets), build products (not projects), and grow customers (not departments). Defining the object and resiliency model, the event model, the security model, the SQL and analytics model, the large language and AI model, and the migration pathways has been hard, really really hard. But it has been fun in a close-knit family that fights together, designs together, and travels together.

Writing is a rare skill. Writing something as it is being created is rarer. Manoj and I are thankful that we founded DevRev with Steve early. The Book of DevRev is a testament that friends can work together for decades, disrupt markets, and be constant students of life and technology. I look forward to seeing The Book evolve along the way, helping you appreciate the effort that goes behind the Effortless…

—Dheeraj Pandey, co-founder and CEO, DevRev, Prior Chairman and CEO, Nutanix

To begin, I would just like to say thank you and welcome! Time is valuable and I hope throughout this work we can provide valuable insight and knowledge.

A key theme in my life has always been not only the pursuit of knowledge but sharing of my learnings with others. Sadly, a lot of people safeguard knowledge; knowledge is not something that should be held close to the chest, it should be exposed.

The power to make a difference lies not only in what we know but also in our capacity to share it.

The original inspiration for this work has roots in our previous company, both figuratively and literally. We realized the power of being transparent, open, and sharing our knowledge with the world with a work called The Nutanix Bible. This allowed us to enable our employees, our partners, and our customers; which led to a much more productive and fruitful environment.

However, we also faced many challenges and frustrations as we grew that product and business which caused us to question things. This spark led to an epiphany that it was time for a better way of doing things and led to the birth of the idea of DevRev.

With the Book of DevRev, we aim to not only talk about some of our lessons learned, and tips for success, but also to create a platform for others to share their experiences. The world is a diverse place and we would be remiss to ever believe we were all knowing. With this, we aim to set knowledge free, learn from one another, and enable everyone to build better products and companies!

Let’s grow together –

—Steven Poitras (aka SP, aka The Dude)

We commence our exploration at the very core of genesis, representing the inception and creation of business. We delve into the profound influence of evolution, an unwavering force that not only shapes the natural world but also leaves its mark on the realms of business and technology.

Businesses, tracing their origins from the early days of tangible trade to the contemporary landscape dominated by software companies, have encountered distinctive challenges and undergone transformative journeys. Throughout our voyage, we underscore the critical importance of adaptability, especially in light of the dramatic shift in consumer expectations.

Our scrutiny extends to the evolution of systems, encompassing the integration of ERP and CRM systems, as well as the rapid technological advancements that have unfolded. Central to our exploration is the fundamental query: How have these systems evolved to align with the evolving needs of modern enterprises?

Lastly, we immerse ourselves in the genesis of the AI revolution, a technological marvel that has reshaped our world. Large language models and generative transformers have ushered in a paradigm shift in our interactions with technology and information, challenging conventional search methods and unlocking new realms of creative potential.

Evolution

“It is not the strongest of the species that survive, nor the most intelligent, but the one most responsive to change.” - Charles Darwin

Within the natural world, the concept of evolution stands as one of the most profound and influential forces. It is the unyielding current that has propelled life from its humble origins as minuscule molecules to the rich diversity of complex living organisms we behold today. These same forces hold true with the evolution of customer needs, technology, products and businesses alike. In this exploration, we delve into the heart of evolution and how this has impacted business, their supporting systems and finally the impact of AI.

Business

The evolution of businesses has been a dynamic journey, starting with the production and trade of tangible goods and services. As businesses aimed for profitability and scalability, the emphasis on efficiency became paramount. In parallel, the landscape of businesses has transformed, particularly with the proliferation of software companies, leading to distinctive challenges, processes, and needs compared to traditional enterprises. While many businesses have attempted to retrofit their models to existing systems, this approach often presents challenges, as experienced by our prior company.

If we just look at the proliferation of and evolution of software companies since the introduction of the mainframe to the dot-com boom to the cloud era and now the GenAI era; the sheer number, scale and impact of these companies has dwarfed many others. In some analysis the software and digital portion of the technology total addressable market (TAM) has massively increased from a mere 25% in 1995 to over 75% as of late. This digitization is a fundamental shift, which, in most accounts, will continue to expand.

In the world today and the future, everyone company is a “software company”, even if they deliver tangible goods

Consumers

Similar to how businesses have impacted the world as we know it, the products they’ve produced have brought about a shift in the way consumers use, engage and purchase products. This intertwined dance of products and customers continually drives innovation and is constantly changing the expectations of the consumer.

Moreover, consumer expectations have shifted significantly. The balance of power has tilted from vendors to consumers, who now have an abundance of choices (optionality). To attract and retain customers, businesses must reconsider their approaches, raising questions about the relevance and efficiency of traditional methods in this rapidly changing environment. Consumers today are more informed, empowered, and connected than ever before. The digital age has given rise to an era of online shopping, personalized experiences, and instant access to information, profoundly influencing their behavior. This shift has prompted businesses to focus on enhancing user experiences, offering seamless digital interactions, and leveraging data-driven insights to meet the evolving needs of the modern consumer.

Systems

The implementation of structured processes and methodologies has significantly enhanced operational efficiency within businesses. The advent of computers further accelerated this efficiency, and the subsequent integration of enterprise resource planning (ERP) systems, encompassing functions such as finance, manufacturing, supply chain, inventory management, and procurement, played a pivotal role in optimizing overall business operations. Shortly after, the adoption of customer relationship management (CRM) software emerged as a means to effectively monitor customer engagement, marketing campaigns, and business opportunities. Additionally, the development of customer support systems became essential for addressing issues that arose after customer acquisition.

Considering the rapid evolution of technology in recent years, as well as over the past decade, it becomes evident that numerous facets of the industry have undergone profound transformations. These include shifts in programming languages, evolving methodologies, architectural advancements, interfaces (e.g., social, mobile) and changing user expectations.

In light of these substantial technological advancements, a pertinent question arises: How have these software products evolved, given that many of them have been in existence for more than 15 years?

Human and Business Interaction

The landscape of human and business interaction has undergone a profound transformation throughout the years. From the early days of exclusive in-person encounters to the era of carrier pigeons and telegrams, followed by the revolutionary advent of the internet, and culminating in the perpetually connected world of today, the metamorphosis has been relentless and will undoubtedly persist.

This journey has left no aspect untouched, revolutionizing how individuals collaborate, how to engage and interact with customers.

• The dynamics of collaboration among individuals.
• The strategies employed for engaging customers.
• The manner in which customers interact with businesses.
• The approaches taken in providing customer support.
• And a myriad of other dimensions.

To illustrate this, consider the bygone era before the internet’s ascent, when customer outreach predominantly relied on conventional methods such as physical mail, billboards, or radio advertisements. In stark contrast, the digital realm now reigns supreme with the advent of the internet and social media platforms.

Likewise, the means by which businesses interact with and support their customers have undergone remarkable evolution as well. Initially, interactions primarily took place in person or through telephone conversations. With the advent of the internet, email emerged as a powerful alternative. Fast forward to the present, and chat interfaces and social media have gained prominence, gradually eclipsing traditional methods.

In the realm of internal collaboration, the impact of COVID-19 has reshaped the way people work. Traditionally, work and collaboration thrived on physical proximity. However, in the wake of the pandemic and the ensuing paradigm shift toward “remote work,” collaboration dynamics have shifted from a co-located model to a decentralized one. This transition leverages an arsenal of collaboration tools, including messaging platforms and video conferencing, to bridge the physical gap. It’s crucial to recognize that rather than debating the merits of these two approaches, the key lesson lies in embracing both local and remote work paradigms to drive efficiency.

The AI Revolution

The emergence of Artificial Intelligence (AI) technologies, such as large language models (LLM), generative pre-trained transformers (GPT), and vector databases, has transformed the technological landscape. While AI had its skeptics a mere five years ago, it is now undeniable that AI is a game-changer, just like the internet and cloud were revolutionary.

AI has not only changed our perception of technology but also revolutionized how we conduct tasks. For instance, AI-powered models can access and process vast amounts of information from the internet to answer queries, potentially rendering traditional search methods obsolete.

Furthermore, AI’s influence extends to content creation, with AI-generated content becoming increasingly prevalent. This shift has the potential to alter the value of content, especially as AI could replace traditional search engines that index generated content. Businesses may need to adapt their content strategies to influence AI models and shape the information presented to users.

Lastly, AI has also impacted creativity, offering tools that change the way people envision, design, and iterate. These innovations empower individuals to create complex and detailed content independently. In fact, Midjourney was used to generate a great deal of the abstract images used throughout this book.

We have transitioned from a phase where AI was associated with apocalyptic scenarios to an era where AI enhances our lives, improves efficiency, and reshapes the way we interact with technology and information.

Throughout our relentless exploration of how we could have evolved and approached things from a different perspective, we’ve acquired deep and meaningful understanding. This isn’t just theoretical pondering; it represents the invaluable wisdom we’ve gleaned through our encounters with real-world challenges, are encountering in the present and future alike.

In this section, we dive into the nitty-gritty details and unveil the lessons we’ve learned. We’ve witnessed the stark disconnect between dynamic businesses and their stagnant support systems. And we’ve asked the pivotal question: Why persist with an outdated approach when modern enterprises demand agility?

Our journey continues with the pitfalls of organizations, where we’ve encountered the hurdles of silos, knowledge gaps, and the quest for unity. It’s a journey from the humble beginnings of startups to the complexities of established businesses.

Join us as we share the insights and discoveries that have led us to a new way of thinking about the intricate relationship between business and technology. This is a practical guide, offering invaluable lessons for leaders, innovators, and anyone navigating the ever-evolving landscape of modern enterprise.

The Impedance Mismatch Between Business Evolution and Systems

As businesses have evolved, embracing new paradigms and navigating a rapidly changing landscape, a clear and significant discrepancy has emerged. While businesses have adapted, innovated, and expanded, the systems supporting them have often remained stagnant, unable to keep pace with evolving needs. When you think about the changes just in technology alone, the systems developed even a few years ago will face dramatic challenges or the need for re-platforming or re-writing to fully embrace current technology. For example, some legacy systems still rely on older relational structures, and the shift to a vector database would be a massive undertaking. Similarly, the way systems were built has dramatically evolved including the languages, the interfaces (e.g., APIs and webhooks), and ways things were built (e.g., monolithic vs microservice archtiecture) which can be very limiting when it comes to embracing the latest and greatest.

This incongruity between the dynamic nature of business and the static nature of their supporting systems has raised a critical question: Why persist with an approach that no longer aligns with the demands of modern enterprises? This question has led to a resounding realization that a fundamental shift is imperative.

Challenges related to visibility, efficiency, and effectiveness have underscored the limitations of traditional methods. Consequently, a growing imperative for a new, adaptive solution has emerged to bridge the widening gap between the ever-evolving business landscape and the systems that underpin their operations.

Silos and Organizational Evolution

Allow me to commence with a brief narrative…

In the year 2011, when I embarked on my journey with Nutanix, the landscape was far from auspicious. Our venture lacked a shipping product, customer base, and the product itself was a work in progress. We operated from a single room on Technology Dr. in San Jose, CA, encapsulating those formative “early days” familiar to all startups.

As our product gained traction and viability, we expanded our purview to include dedicated Ops/IT teams, ensuring the stability of our operations. The initial model of our engineering team supporting customers proved unsustainable, prompting the establishment of a dedicated support team, complete with a ticketing system. In parallel, we listened keenly to our early customers, using their insights to evolve our product into something we could confidently promote and sell. Consequently, we welcomed marketing and sales teams into the fold, along with the introduction of then essential tools like Salesforce CRM and Marketo.

In those initial stages, proximity facilitated seamless collaboration and communicmake ration; questions were addressed with a mere shout or a short walk. However, as our business burgeoned, fissures in knowledge sharing and the rise of organizational silos became increasingly evident. Each team cultivated its own system and workspace, with sales on one end of the building and marketing on the other. Over time, these divisions solidified, unintentionally erecting barriers to effective collaboration.

As Nutanix continued to grow, the issue intensified, with these silos becoming even more entrenched. Allocating additional resources, while a common response, failed to address the root problem, and individual productivity remained elusive.

Regrettably, it’s a common tendency for leaders to hoard knowledge, viewing these silos as a form of leverage. However, this mindset, while it may serve their immediate interests, ultimately undermines the greater good of the company. Conversations with numerous individuals and businesses confirmed that this issue wasn’t unique to our organization; it plagued companies of all sizes.

The Inevitable Proliferation of Silos

When contemplating the structure of a company, one inevitably encounters the inclination to build these silos. In most businesses, departments such as Engineering, Support, Sales, Marketing, IT, HR, Finance, and Accounting function as distinct entities, each essential for the company’s success. For optimal efficiency, these units must operate harmoniously; any discord can manifest as inefficiency or, in extreme cases, jeopardize the company’s viability.

Whether by design or circumstance, companies frequently gravitate toward silo creation. As they expand, new departments and leaders often introduce their own systems of record, each demanding its autonomous domain.

The visual below illustrates a typical scenario, where disparate teams operate within their silos, often without shared accounts or integrated systems. This fragmentation leads to duplication, inconsistency, and a lack of coordination, as each team interprets information differently.

The Hidden Costs of Silos

Generally, a series of consequences and impacts tend to arise:

• Coordination Dilemmas and Inefficiency:
  • Frequently, each department operates with its individual plans and roadmap, often in isolation.
  • This lack of coordination can result in misaligned efforts and even gross duplication of work.
  • Operating within silos also leads to inconsistency across departments.
• Knowledge Barriers and Gaps:
  • Some may regard knowledge and information as leverage, but this often breeds internal politics, detrimental to business.
  • Users are typically confined to their respective systems, lacking access to others.
  • For instance, an Engineer might have access to their work system like JIRA or DevRev but not to support systems like ZenDesk or SFDC Service Cloud.
  • This leads to fragmented context and a lack of the “big picture.”
• Subpar Employee Experience:
  • Silos can foster a competitive rather than collaborative environment.
  • Discovering that one’s work has been duplicated elsewhere can be demoralizing.
  • Due to the absence of full context and the constant need to relay information between teams, this often results in “work suck.”
• Dismal Customer Experience:
  • Few things are as frustrating as encountering a problem, speaking to a support representative, and then a salesperson who’s unaware of the support agent’s actions.
  • This frequently leads to inconsistent messaging, portraying a negative image of internal coordination and execution capability to the customer.

But perhaps you’re thinking, “That’s not my problem…” Are you entirely sure?

Let’s consider this from the perspectives of various personas:

Product Manager:

• How would your approach evolve if you had a holistic view encompassing customer requests, product usage, bug tracking, and revenue potential?
• Imagine gaining a comprehensive understanding of your customers, including their support interactions, engagements, and product usage.
• Consider the possibilities of identifying and prioritizing high-impact items based on their revenue implications.

Support Engineer:

• How would your approach change if you knew about potential opportunities or deals with the customer?
• Imagine not having to engage in the tedious task of copying and pasting between engineering issues and your tickets.
• What if you could effortlessly track the status of escalations and have that status automatically reflected in the ticket?

Sales Representative:

• What if you had full visibility and could easily monitor the challenges your customers face, receiving notifications when issues arise?
• What if you could prioritize certain fixes based on deal size?
• Imagine having immediate insight into matters that your customers care about or being promptly notified about new developments from the engineering team.

Customer Success:

• What if there were a unified platform providing clear visibility into your customer’s tickets, opportunities, and relevant engineering issues?
• How would a more coordinated approach impact your customer’s overall experience?
• What if you could prioritize work based upon risk to churn and growth opportunities?
• If a system existed for sharing context, how much manual coordination effort could it save you?

Finance:

• What’s the cost of context-switching and inefficiency within your department?
• If you could save 30 minutes of wasted work daily, what would the opportunity cost savings amount to?
• Consider the cost of an individual being 20% less productive and then extrapolate that to a company-wide scale.

Human Resources (HR):

• How does inefficiency or lack of knowledge affect employee morale?
• Does the manual inefficiency negatively impact their well-being?
• What if you could empower them to be more productive? How would that boost morale?

Whether we embrace it or not, silos cast an impact on everyone within the business, either directly or indirectly. They genuinely influence productivity, experience, efficiency, and, ultimately, the bottom line. So, have you ever considered the true cost of inefficiency for your business?

Unifying Your Product Perspective

When we embark on the journey of managing a product portfolio, numerous critical questions demand our attention. How should we perceive our product lineup? What products are currently at our disposal, and what unique capabilities do they bring to the table? And, perhaps most importantly, how do we make informed decisions about product investments, divestments, or discontinuations?

How we contemplate our products and structure them within our organizational framework constitutes a foundational prerequisite for addressing these intricate inquiries. Without a well-defined and meticulously structured product hierarchy, the fog of uncertainty obscures our vision, leaving us without the clarity needed for effective decision-making.

Commence with the Why

First and foremost, why is this matter of such importance?

Drawing from our past experiences, we encountered formidable visibility challenges stemming from an inability to correlate revenue, costs, and defects with precise granular facets of our products. While we could enact a semblance of this analysis at a crude level, the absence of a mechanism to delineate distinct ROI for each feature imposed significant constraints.

Conversations with fellow founders and leaders in established companies unveiled a shared predicament. While organizations could oversee operations at a macro level, the conundrum of deciphering which features to amplify, curtail, or discontinue in the context of substantial engineering teams remained perplexing. Optimization became paramount, considering the judicious allocation of time, financial resources, and opportunity costs.

Return on investment (ROI) has perennially taken center stage in departments like sales and marketing. For instance, envision a sales representative, with a designated cost structure encompassing base salary, commissions, and travel and entertainment expenses. By quantifying the generated pipeline and revenue, one can effortlessly appraise the ROI for that representative. It bewildered us that analogous objective assessments or granular ROI evaluations weren’t commonplace when it came to products.

One of the fundamental tenets underlying the development of the DevRev platform centered on the insistence that everything must be intrinsically linked to a product and/or customer. But why, you might wonder? The answer is unequivocal: Clarity. By establishing these interconnections, we gain the capacity to address a multitude of probing questions, including but not limited to:

• Which features constitute the primary revenue drivers?
• What features are customers actually using?
• What was the development cost associated with a specific feature?
• Which capabilities exhibit the highest defect rates?
• Which features are experiencing accelerated adoption rates?
• What ROI did a particular feature yield?

The Product Lifecycle

In the realm of modern businesses, a distinct pattern emerges, emphasizing specific areas of focus throughout the lifespan of a product or service.

We’ve broken down this journey into four fundamental quadrants:

• Build
  • Focuses on the ideation, creation, and evolution of products or services.
• Operate
  • Focuses on the operation, monitoring and incident management of products or services.
• Support
  • Focuses on the support and troubleshooting with customers, collaboration with them, and a collaborated effort to minimize churn.
• Grow
  • Focuses on the expansion of product adoption including new customer adoption, nurture, awareness and retaining.

The diagram below offers a visual representation of these quadrants and the link back to product:

This comprehensive lifecycle serves as a cornerstone for any organization aiming to retain competitiveness within its industry. It encompasses the multifarious stages a product traverses, commencing from initial design and development, progressing through evolution, and concluding with eventual decline or obsolescence. In this article, we will embark on a high-level exploration of these distinct phases. Subsequent in-depth discussions for each quadrant will follow in dedicated posts.

Note: While primarily applicable to products and services, these quadrants equally pertain to a company and its personnel.

Artificial Intelligence (AI)

In the age of artificial intelligence (AI), change is the only constant. AI’s profound impact on our world, akin to the internet’s transformation, demands our attention. With AI’s undeniable presence, those who resist its embrace risk falling behind.

However, integrating AI into existing systems is no simple feat, especially for products born before the AI revolution. Re-platforming is imperative, but it comes with formidable challenges, including the critical role of context in AI effectiveness, the need for swift adaptation, extensive system redesign, and internal dynamics.

This exploration delves into the pivotal role of context in AI, emphasizes the importance of context for unlocking AI’s potential, and underscores the significance of knowledge graphs. These versatile tools go beyond item similarity, helping us organize and cluster events over time, make informed decisions, and navigate the complexities of our data-driven world. Join us as we navigate the evolving AI landscape, reshaping industries and redefining technology’s role in our lives.

AI will eat the world

“Change is the law of life. And those who look only to the past or present are certain to miss the future.” - John F. Kennedy

Inevitably, AI is becoming an indomitable force, reshaping the very foundations of our world. Much like the advent of the internet, its impact is profound, and those who hesitate to embrace it risk falling behind.

To illustrate this transformation, consider that nearly all the images within this work were crafted with the assistance of AI. This isn’t conjecture; AI is an undeniable reality.

The Imperative for Re-platforming

For systems and products conceived prior to the AI revolution, a fundamental re-architecture is imperative to unlock its full potential.

While every vendor may harbor the potential for AI integration, the journey may be riddled with challenges, some surmountable, and others insurmountable. In navigating these waters, it’s wise to apply a litmus test, for often, marketing promises diverge from stark realities.

Here are some formidable challenges they may encounter:

• Limited context impedes their results (you can’t fix what you don’t know; this is paramount).
• Inability to pivot swiftly (turning a tanker is vastly different from steering a small boat).
• Extensive redesign of user interfaces and backend systems (the extent varies but is essential).
• Encounters with internal politics and conflicts (in larger organizations, everyone seeks a slice of the pie).

Context is Key

In the realm of AI, models are only as effective as the context they possess (e.g., training data, fine-tuning data, and embeddings). For instance, both Chat GPT 3.5 and 4.0 were trained on publicly available internet data as of September 2021. Still, they lack knowledge of the current state. AutoGPT and similar innovations aim to bridge this gap by providing the ability to acquire additional context, yet…

That’s not the key, the key is in the data that you have that the models don’t have access to.

The greater the context you can furnish through embeddings or fine-tuning, the more powerful AI becomes in your hands.

The Significance of Knowledge Graphs

Knowledge graphs stand as invaluable tools that facilitate the organization and association of items based on various dimensions. Their utility extends beyond merely establishing item similarity; they excel at the localization and clustering of events over time as well. These can be used to reduce the potential of hallucinations, enhance model viability with fine-tuning and leverage things like reinforcement learning from human feedback (RLHF). The true power of AI is attainable when you can correctly bias it, else you are at fate of training sets.

Knowledge graphs serve a multifaceted purpose, offering the following key advantages:

• Dimensional Clustering: Knowledge graphs enable the grouping of items or entities by considering multiple dimensions simultaneously. This sophisticated clustering ability aids in the identification of intricate relationships and patterns that might otherwise remain concealed.
• Enhanced Similarity Analysis: By incorporating a wide range of attributes and connections, knowledge graphs allow for a comprehensive examination of item similarity. This goes beyond basic comparisons, as it takes into account nuanced relationships and contextual information.
• Temporal Event Clustering: Knowledge graphs are not confined to static data. They excel at clustering events over time, providing a dynamic perspective on how various occurrences are interconnected. This is particularly valuable in fields where temporal analysis is essential, such as historical research, financial markets, and epidemiology.
• Contextual Insights: With knowledge graphs, items are situated within a broader context, fostering a deeper understanding of their significance and relevance. This contextualization can lead to richer insights and more informed decision-making.
• Discovering Hidden Associations: Knowledge graphs have the capacity to unveil hidden associations and dependencies among items. This can be instrumental in fields like network security, fraud detection, and recommendation systems.
• Navigational Efficiency: Knowledge graphs offer efficient navigation through complex datasets. Users can traverse relationships between entities, making it easier to explore and extract valuable information from large, interconnected datasets.
• Machine Learning and AI: Knowledge graphs play a pivotal role in machine learning and artificial intelligence applications. They provide structured data that can be leveraged for training models, improving predictions, and enhancing the understanding of complex systems.

In summary, knowledge graphs are not limited to a single use case or dimension; they are versatile tools capable of uncovering insights, clustering entities, and navigating through intricate datasets. Their ability to capture the essence of relationships and events, both spatially and temporally, makes them indispensable in a wide range of applications across various industries.

“The journey of a thousand miles begins with one step.” - Lao Tzu

The Idea

In the prior sections, we went through some of the challenges ourselves and others had faced as well as the revelations we learned from them. These learnings are the precurser or spark that lead to the beginnings of something we believe to be revolutionary.

These items can be boiled down to the following key motivators:

• The disconnect between systems and the needs of businesses in the modern era
• The challenges of silos and inefficiencies they represent
• The inconsistent view of how product is thought about and structured
• The eventual revolution of how AI will change the world as we knew it

The above items brewing together and increasing over time like a perfect storm until the clarity emerged.

We sought to re-imagine what people building, supporting, operating, and growing products needed. Could we be everything to everyone? No. But for the 80% we will do our best to fix things.

Here’s what we imagined:

• A single platform replacing the core functionality of some systems, augmenting others
• A platform built fully embracing and designed for AI
• A platform that related everything back to product and customer
• Integrated with systems to gather events/context (e.g., monitoring alerts, git events, etc.)
• A modern browser interface
• Fully integratable with APIs (benefits for both headed and headless modes)

The Tenants

Convergence

We felt the pain of engineering not having access to the support system and context from customer discussions. We felt the pain of product management not having all the context to define and prioritize clearly. We felt the pain of sales reps not having clarity on their customers’ tickets, engineering roadmaps, and the status of items relevant to them. We felt the pain of support not having access to information like customer details and the status of pipeline opportunities. Lastly, we felt the pain of having to ‘ask’ for access or context instead of natively having it in the context of the work.

Why not just give everyone access to everything? Cost All of these have per-seat licensing, so it was not fiscally possible.

Why not just build a ton of integrations to replicate all data everywhere? Opportunity Cost. Integrations take time and each of these would have to be done point-to-point which doesn’t scale and/or work when things change.

We pondered if this was just isolated to us, however, after many discussions with our peers and established corporations; we found it is something that is rampant across many organizations, big and small alike.

Perturbed by this inefficiency and understanding the impact this had on ourselves and others alike, we had enough and knew there had to be a better way, hence the beginnings of what led to DevRev.

We dreamed to enable people to move from the legacy siloed model:

To a converged model where everyone could operate in unison on the shared context:

Platform-first Thinking

From the inception of our journey, we held a steadfast commitment to extensibility and the future integration of third-party add-ons. This significantly influenced how we approached the design of our services and the manner in which we established interfaces between various elements.

At the heart of DevRev lies a comprehensive platform, housing all the essential components required to construct a robust enterprise system. While we do provide a user-friendly interface through our application, which abstracts many of these underlying APIs; our platform’s versatility shines when utilized in a headless fashion or as part of a hybrid solution. Much like how cloud services (IaaS, PaaS) furnish the building blocks for running diverse workloads, our platform empowers users to develop applications atop its foundation.

During our initial stages, we pondered the foundational building blocks essential for our platform, characterized by the following diagram:

Built for AI

With all of the buzz around ChatGPT, LLMs, and AI, everyone is hopping on the bandwagon with “support.” But how much of this is fluff vs. reality?

When we initially thought about the company, AI was a foundational focus for the product. This is why we chose devrev.ai when we registered our domain in 2020 (far before this recent hype).

We aren’t just now hopping on the bandwagon; we’ve been preparing for it.

Domain Name: devrev.ai
Registry Domain ID: 982682_nic_ai
Registry WHOIS Server: whois.nic.ai
Creation Date: 2020-06-07T22:25:10.749Z

At its core, DevRev was built to converge the events, products and people (customers, partners and employees) focused around building, operating, supporting, and growing of products. Through the linkage between these objects, we were able to build a powerful knowledge graph that is used to drive every piece of the system.

With the ability to triangulate across these vertices, we can do some really amazing things and provide much more understanding and insight. This is applicable to not only correlation, or clustering (similarity), but brings the power of AI to things like analytics, trend analysis, and prioritization, as well as many more.

By converging things and having a common context, all teams are using; the goal is to enable them to operate as a much more cohesive unit with much higher efficiency and satisfaction.

The following figure (I know, it’s a lot) shows a real-world example of how we can correlate between product, people (contributors, customers), support, build, opportunities, docs, and a whole plethora of other objects:

Ok, but why should I care?

When it comes to making decisions or gathering insight, the more context you have the better the decision you can make. Just think about this in real-world scenarios…

When you buy a car do you just consider the features of the car? No, you consider the features, your finances, practicality, terms, what the spouse will say, etc. When you purchase a product, you consider the need, cost, runway, future needs, etc.

Now, say you want to prioritize which work you should focus on and deliver in the next sprint. You’d need information about other items in-flight, staff workload, customer impact of items, dependent opportunities, and a lot of additional data.

With DevRev, we have the full context and can use that to feed into the models. With the other point systems, you’d need to consolidate somewhere manually or lose valuable context which the models need.

Would you trust something making decisions without full context?

How we embrace

Coming from Nutanix, we saw a lot of customers looking to move from monolithic systems to those of a more scalable, converged nature.

Because we knew AI would be a crucial part of the system, this impacted how we designed our platform. Affecting things like our service design, delivery architecture, change tracking, object model, analytics and almost everything we’ve done in the system; even the way we designed our interface and UX was built to embrace this.

What are some examples of how we architected things differently?

• We built a badass knowledge graph
  • This is at the core of the DevRev platform and is used by every piece of the system
  • We have defined links between objects which allows us to keep track of various relationships between objects
  • Given this, we are able to easily create graphs of relationships (edges) between objects (nodes)
  • This allows us to triangulate and correlate between items (can also be used in vector DB scenarios)
  • Using this constructed vector DB we can easily cluster objects across various dimensions (we use this to cluster similar events into an incident, for example)
  • We can also triangulate between a customer, product, ticket, issue, and developer allowing us to feed “events” between objects that may be relevant
• We used a flexible document DB instead of traditional relational systems
  • Using this structure, we have a ton of flexibility in the document structure, the ability to annotate and extend
  • Relational systems can be very rigid and can quickly get messy with a ton of constraints, especially if you haven’t built a ton of abstractions into the data model
  • This was key enabler for the next point (customization)
• We built customization in from the start
  • We knew extensibility would be key for any platform
  • Given the simplicity of customization, we can easily extend our object model with new annotations or context that can be used and fed into models
  • This means, that a customer or vendor, can easily extend our object model with new data on objects which can be used by models, new object types, or with the output of a model
• We built multi-tenancy into the object
  • Rather than physically segmenting tenant data, we built tenancy into the objects using specific attributes which act as partitions
  • This allows us to create macro partitions (e.g., customer) or extremely granular partitions (e.g., user level)
  • This gives us a ton of flexibility as all data is in one place and the granularity can range from macro to micro
• We designed our services for the cloud
  • Being built in the “era of cloud” we had a lot of very nice tools available to us (e.g. K8s, Lambda, edge computing, WASM, etc.)
  • We fully embraced these methodologies allowing us to create a set of very flexible [micro, function, edge]-based services
  • This allows us to rapidly scale resourcing (e.g. scale-up/down) and iterate quickly
  • Also, by leveraging edge logic and WASM (client-side), we can do some really amazing things (more to come here)
• We are built to iterate quickly
  • AI evolves faster than we can imagine; being able to iterate quickly is quintessential to ensure customers get the value of this evolution
  • Given the granularity of our services, teams can operate with much more autonomy and speed
  • We were also built during the CI/CD era, meaning we have fully continuous integration and delivery. As an example, we deploy hundreds of changes daily
  • With monolithic systems, changing things can be complicated as you need to build things at a much more macro level
  • Also, some vendors who didn’t grow up in the “as a service” era will need to change processes to embrace CI/CD (some may have)
  • A good ask here is how frequently changes are deployed
  • When something new comes out, we can react and enable rapidly; others may be slower to enable, leading to a gap between when something is “available” and “really available”

Most of the available items and concepts we had weren’t even ideas when a majority of the other vendors were created. Having gone through a great deal of platform re-architecture, it is a nightmare (if it works).

This means that those vendors can’t simply “bolt-on” AI, or if they do I would question the efficiency of this.

The “Trinity” (product, people, work)

When examining the realm of business, one encounters several pivotal elements:

• Products (the offerings that companies create and deliver)
• People (encompassing both customers and employees)
• Work (the activities revolving around product development, customer support, and operational tasks)

The existence of companies hinges upon the products they offer to their customers. The presence of customers is essential, for without them, a product lacks viability, and consequently, a company’s existence is jeopardized. Conversely, the absence of a product would leave a company bereft of its customer base.

Work serves as the driving force behind engaging and nurturing customers, providing them with support, and continuously evolving the product. Neglecting the work required to support customers can lead to attrition and churn. Furthermore, failing to invest effort in acquiring, engaging, and nurturing customers hinders a product’s and company’s growth. Lastly, the importance of laboring to build and enhance products cannot be overstated, as it prevents a misalignment between the evolving demands of consumers and the product’s capabilities.

To succeed, businesses must integrate product, people, and work. This synergy ensures products meet customer needs and adapt to future demands, fostering success.

Security

In the realm of security and privacy, they often find themselves relegated to an afterthought rather than integral components of the original product concept. Our past experiences at other organizations underscored the formidable challenges posed by attempting to retrofit elements like role-based access control (RBAC) onto semi-mature platforms. The stark reality is that the longer such considerations are delayed, the more daunting they become, sometimes reaching a point where implementation appears elusive.

Armed with the wisdom from these experiences, we were resolute in our conviction that security must be elevated to the status of a first-class citizen in our development philosophy. Vital facets such as identity, authentication (AuthN), authorization (AuthZ), compliance, and platform security demanded the same level of attention as any other service or component.

Our approach involved a symbiotic design process, orchestrating our authorization platform and object model in unison. This synergistic approach proved immensely potent. Within our object model, we meticulously laid the groundwork, ensuring we possessed the requisite keys to partition and segment data effectively. This profound understanding of the structure empowered us to fashion granular and precise authorization mechanisms. By dedicating upfront effort to this aspect, we’ve endowed our system with authorization capabilities that some mature companies can only envision, including support for role-based access control (RBAC), attribute-based access control (ABAC), policy-based access control (PBAC), field-level security, lease-based access, conditional policies, and more.

From a compliance perspective, our rigorous efforts encompassed adherence to regulations such as SOC2 and ISO-27001. These considerations exerted influence over various facets of our architecture, notably shaping our approach to edge security through our web-application firewall (WAF) and our handling of configuration management.

Even within our internal operations, we wholeheartedly embraced the zero-trust model, recognizing that the human factor often serves as the most susceptible threat vector.

DevRev on DevRev

While it may sound idealistic and somewhat disconnected from reality, we firmly believe that as builders of a product, we should experience its challenges more intensely than anyone else. We are committed to leaving no stone unturned to thoroughly evaluate every aspect of what we deliver to our external customers. In our journey as a product provider, we have fully immersed ourselves in every stage: building, operating, supporting, and growing our product, using our own creation.

However, within this commitment lies a paradox, which also presents an opportunity. We find ourselves in a situation reminiscent of inception, where we are building the very product we use to build our product. We consciously chose not to take shortcuts; instead, we invested the necessary time and effort to develop, implement, and continually refine our tools, ensuring a rigorous and efficient approach to product development.

Through these experiences, we believe it has allowed us to push out a much better product with the right motivations. However, we are not all customers, and not all customers are alike. So while we will continue to run the building, operating, supporting, and growing of our product on our product, we will continually listen to our customers, collaborate with them and partner with them to build something better together.

The Future

“The greatest danger for most of us is not that our aim is too high and we miss it, but that it is too low and we reach it.” - Michelangelo

In the evolving landscape of technology and human progress, it is our vision and dreams that propel us forward. We must continually strive to elevate our aspirations, to reach for the stars rather than settling for the ordinary. Our journey doesn’t end with the status quo; it thrives on pushing boundaries, imagining the impossible, and pioneering new horizons.

As we look to the future, let us remember that our potential knows no bounds. We are the architects of our destiny, and it is our audacious dreams and unwavering commitment to progress that will lead us to new frontiers. So, let us raise our ambitions, challenge the norm, and together, push the bar higher than ever before, for it is in aiming for the extraordinary that we truly find greatness.