Tech companies, large and small, depend on software moats to remain competitive. These software defensive barriers are necessary to prevent rival companies from replicating proprietary data and product differentiators that often keep paying customers locked into the SaaS platform. Rami Beracha is a former Wall Street Corporate attorney who successfully transitioned to the venture capital world back in the 90s. Currently, he is a venture capitalist who specializes in advancing decentralized AI technologies to build a decentralized digital economy.
Like many executives, Beracha keeps a keen eye on advances in AI. Our modern economy is heavily based on SaaS (Software as a Service) as a foundation for profitable business models (Google, Salesforce, Adobe, Facebook). But he envisions a future in which AI has destroyed the moats and defensibility of hundreds of software companies that once designed unique software solutions, because those solutions are now easily developed in-house using AI.
This trend has given rise to companies that combine both hardware and AI in their software solutions, making hardware (rather than the software) a more sustainable differentiator.
A Critical Trend for Startups to Consider
Rami Beracha is a thought leader in product development and go-to-market strategies for businesses at every stage of the startup journey. He has been instrumental in the success of over 90 M&As and 25 IPOs, many of which focused on deep tech and systems intelligence. Beracha has witnessed a shift from software to hardware as a business model differentiator. These restructured business models are built using AI, effectively removing most barriers to software coding and platform development.
Beracha knows the dominant industry for startups has typically been software and data-related ventures. But more recently, he has witnessed the AI subsector grow massively, accounting for nearly 20% of all software/data startups. With the move toward AI-developed software, there is more competition and less need for human personnel.
Software features are no longer a dependable moat, as AI is driving a decline in “per-seat” SaaS pricing, the traditional model of charging per user. Now, AI agents that replace human personnel mean the end user buys fewer licenses, a trend that has already begun to drastically lower profit margins for SaaS vendors.
The Future of AI in Software Development
“Between 2017 and 2024, the number of AI tech companies experienced significant growth. The tech industry now represents a substantial portion of the total U.S. Gross Domestic Product, contributing trillions to the economy.”
Software defensibility is critical to startups because it provides assurance that the product can maintain a competitive advantage over rivals. It is an economic moat that prevents the product from being easily replicated, supported by proprietary technology, network effects, and high-end user switching costs. But Rami Beracha believes that the future of software development is in peril, with AI doubling software production compared with the human workforce.
As AI continues to commoditize software feature development, the future of software defensibility will lie in creating products with real-time context that make them harder to replace. At the same time, new product development with hardware features will give these products a true competitive advantage. The combination of custom hardware and proprietary software creates a product that is difficult to replicate.
The Rise of Hardware AI Startups
To offset the role of AI-produced software, Beracha believes a stronger hardware moat can benefit both the end user, with a superior user experience, and the developer, with higher switching costs. While the tech industry has traditionally been software-driven, Rami sees a new era of hardware-focused startups that are taking center stage. AI hardware industry giants include NVIDIA, AMD (USA), Apple (USA), and Anduril, all of which are among the world’s most dominant manufacturers of advanced AI hardware.
The tech industry has shifted from a long period in which software drove product development back to a hardware-focused era, similar to the early days of the microcomputer’s invention. The rise of hardware AI startups includes a fast and furious launch of neural processing units (NPUs) and AI accelerator companies, creating products that reduce data center power consumption and latency.
Soon, AI will all but eliminate or reduce software defensibility. Due to the sheer scale of generative AI output, the industry’s focus on hardware sufficiency will launch top-tier hardware startups into the stratosphere. In the future, the marriage of software and hardware will set the standard for the defensibility of powerful IT systems.
