DeepSeek’s Impact on Everyday Life
With the launch of DeepSeek’s R1 model and the ripple effects it has caused across the industry, conversations in tech circles—whether in office hallways, cafeterias, or virtual meetings—have been filled with uncertainty. Founders, investors, and customers alike are all asking: what does this mean for those building with AI today?
Amidst the noise, one thing is clear—there’s never been a better time for founders to build. The opportunities in AI are more abundant than ever. At Rippling, we’ve been closely observing how this shift is unfolding, and DeepSeek’s breakthrough is more than just a technological milestone—it’s a major step toward democratizing AI, making it more accessible for those looking to innovate.
Even the most cautious takes on DeepSeek’s impact paint an exciting picture. More AI models will emerge, and they won’t require massive budgets to develop or deploy. Instead of charging for the models themselves, companies will focus on monetizing innovative products that leverage AI—products that are lightweight enough to run on everyday devices, possibly even for free.
The landscape is shifting, and the barriers to building cutting-edge software are lower than ever. For founders, this is a defining moment. If you’re looking to build with AI, there’s no better time than now. At Rippling, we take care of the administrative burdens—payroll, HR, benefits, IT, and expenses—so you can focus on what truly matters: building the next big thing.
Still trying to make sense of what this week’s AI developments mean for you? Here are five reasons why we believe now is the ideal time for founders to start building with AI:
AI is becoming more accessible, fueling open-source innovation
The open-source AI community has been growing for years, with models like Meta’s Llama and Mistral AI leading the charge. DeepSeek has now accelerated this momentum, pushing AI innovation into an even more open and collaborative space. This shift creates an opportunity for founders who understand specific industry challenges to build transformative solutions using open-source models and shared advancements.
For builders, this is energizing. AI breakthroughs are no longer exclusive to companies with billion-dollar budgets. While capital remains important, vision, execution, and a scrappy, resourceful approach can take you just as far in developing meaningful AI products.
Lower development costs and the power of multi-model AI stacks
If DeepSeek’s claims hold up, even partially, they’ve managed to build a high-performing AI model at a fraction of the usual compute cost. This is more than a technical win—it’s a fundamental shift in AI development economics.
For founders, this means the ability to design AI solutions with a model-agnostic architecture, integrating multiple AI models into a single, adaptable stack. Rather than worrying about skyrocketing compute expenses, you can focus on applying deep industry knowledge, leveraging diverse data sources, and solving real-world business and consumer challenges.
Think about the steam engine revolution in the 1800s. As engines became more efficient and affordable, people didn’t use less coal—they found more ways to use it, leading to even greater consumption. This phenomenon, known as Jevons Paradox, applies to AI as well: as AI models become more efficient and accessible, we won’t see a decrease in usage—we’ll see an explosion of specialized AI applications.
Many investors and industry leaders are pointing to this very shift. We may be on the verge of an even bigger wave of AI-driven application innovation in 2025 and 2026. Now is the time to build.
Author
Ms. Neha Gahlan
Assistant Professor – NorthCap University