By Steven Gottlieb 28 January 2025
Every platform revolution — DOS, Windows, the Internet — ushered in a corresponding wave of disruptive business applications. Each built from the ground up, natively tailored to each platform, each did so much more than introduce new features; they abstracted complexity and accelerated productivity in ways only imagine and fundamentally redefined how work got done.
- DOS brought us Lotus 1-2-3 and WordPerfect, where, before these apps, complex calculation and document creation were painstakingly manual, consuming hours or even days — to accomplish what today is considered the most basic of tasks.
- Windows introduced Microsoft Office and Outlook, merging essential apps like word processing, spreadsheets, and email into a unified suite, and effectively ending the era where users juggled disconnected apps from different vendors, creating fragmented workflows, data silos, and incompatible file types.
- The Internet brought us Salesforce and Google Workspace, integrating real-time collaboration, sales, and customer management into the core of business operations. While before the internet, working on files as a group was clumsy and universal access was limited.
There’s no doubt that it’s easy to use the most successful applications in history as examples. But it’s intentional. Because these apps were not just about technology. Rather, they created paradigms of working. They were more than tools. They abstracted old complexities with entirely new ways of thinking about how to solve complex problems.
They changed the world.
This, is what we call the “DNA of Disruption,” and the characteristics that the above technologies had are the following.
- They exploited the new platform: They were built specifically for each platform (DOS, Windows, Internet) and fully leveraged new capabilities without legacy constraints, allowing rapid innovation and cost-effective operation by avoiding outdated system dependencies.
- They abstracted complexity: These apps turned fragmented workflows into cohesive, user-friendly suites or workflows, enabling users to accomplish more with minimal training, which sped up adoption and reduced training costs.
- They were designed for everyone: Intuitive and accessible, these apps empowered users across all technical levels, leading to widespread adoption, minimizing workflow disruptions, and enhancing productivity across varied skill levels and company sized.
- They had disruptive financial models: With innovative pricing, flexible packaging, and scalable distribution, these apps lowered entry costs and drove enterprise-wide adoption through new go to market strategies.
Now, we find ourselves at the beginning of the AI platform revolution.
But where are these disruptive business applications?
Despite the significant advances in LLMs and massive investments in AI infrastructure, we’re still waiting for the disruptive business applications that helped define past platform shifts to materialize in the world of AI.
Today, AI tools function largely as chatbots or copilots, sitting alongside existing applications but not fully transforming workflows or unlocking AI’s potential for deep, actionable insights and recommendations across systems. Sure, they add a layer of intelligence, but they stop short of delivering the game-changing productivity gains we know AI can offer. And while the potential for AI to streamline this complexity and synthesize vast amounts of data is enormous, it remains locked behind a technical barrier only few can cross. Data is often siloed, formats are varied, and workflows require intricate configurations or custom scripting that demand a level of technical skill and time commitment beyond most users.
Enter TNE.