It feels like 2009 all over again. When I first held an iPhone, I had a hunch that the way we interact with technology would change. Today, I have the same feeling about AI-native products. These aren’t just extensions of existing systems; they’re built from the ground up to leverage the full power of artificial intelligence.

AI-native products aren’t just software with AI tacked on; they’re designed from scratch with AI at their core. This might sound like a subtle distinction, but it’s a profound one. Because they have AI as their foundation, these products continuously learn and adapt.

Take Perplexity. This platform combines traditional search technologies with large language models (LLMs) to answer complex questions, citing human-created sources from the internet. Unlike traditional search engines that give you a list of links, it prompts you to ask follow-up questions. This turns the search process into an interactive and educational experience.

AI-native apps like Perplexity get better over time. They learn from every interaction, becoming more accurate and useful. They adapt to new data and user needs, making them feel more intuitive and human-like. This continuous improvement makes them indispensable for quick, precise information.

The user interface (UI) of AI-native products is another big advantage. They understand human language and interactions, making them user-friendly. Even non-technical users can navigate and benefit from them without a steep learning curve. This intuitive design broadens their accessibility.

AI-native products also boost efficiency. By automating tasks and rapidly processing large amounts of data, users get information faster and more accurately. Perplexity, for example, provides quick and precise answers, reducing the time spent searching for information. Immediate, reliable responses let users focus on more critical tasks.

Personalization is a key strength of AI-native products. They cater to individual needs by offering tailored solutions, enhancing user experience and satisfaction. Perplexity adjusts its responses based on user interactions, providing customized information that meets specific requirements and interests, making each interaction more relevant and valuable.

But there are challenges too. Developing and maintaining AI-native products is complex and costly. You need significant technical expertise and financial resources. The AI models and infrastructure required aren’t cheap.

AI-native products also need a continuous stream of high-quality data to function well. If the data quality drops or becomes outdated, the performance suffers. This is especially challenging in industries where data is scarce or heavily regulated.

As someone who has witnessed several technological revolutions firsthand, I am excited about the possibilities that AI-native products offer. They remind me of the early days of the internet and the iPhone—times full of potential and change. Now is the time to embrace this new wave of innovation and help shape it. Whether you’re a developer, an entrepreneur, or a user, we all have a chance to be part of this groundbreaking transformation.