Rising Bharat 2025: I don’t plan Perplexity for more than three months, says CEO Aravind Srinivas

Aravind Srinivas

The CEO of AI-power search engine Perplexity, Aravind Srinivas said he does not plan his company beyond a three-month window, underscoring the rapidly changing world of artificial intelligence (AI), underscoring the rapid changes blowing through the space.

“You have to be pretty flexible and fast moving, and so I don't actually plan the company for more than three months now, and this is not the best way to run any company, but in AI, it happens to be like a perfect strategy for us,” Srinivas said at the Rising Bharat Summit 2025 in New Delhi on April 9.

Perplexity CEO’s comment was in response to a question about the one piece of advice in the AI industry that he deliberately ignores.

Usually, companies have strategies and plans for a year or two, stick to them no matter what happens in the world. “I think that used to be a fine strategy when the world was moving a lot slower. It doesn't hold true anymore. Like everything changes pretty fast,” he added.

Also Read: Overwhelmed by job applications, Perplexity AI founder puts India hiring on hold

Therefore, if the notion is that something doesn't work well, then it is fine-tuned and worked upon. “(But) when something happens in reasoning, for example, if you assume agents don't work, and then agents start working, what do you do?” he explained.

Also Read: Perplexity AI's Srinivas backs Piyush Goyal over startups remark

Srinivas also highlighted the challenge of building AI-native products and the balance between generality and user specificity. “People try to work backwards from what the user wants and build for a specific demographic, that’s established advice. But with AI, it’s hard to bake in custom constraints without losing the magic of its generality,” he added.

Also Read: If you're not using AI to write code, you risk stagnation: Perplexity’s Aravind Srinivas

According to Srinivas, striking a balance between building a product that serves a particular set of users while keeping it horizontal and widely applicable is key, and part of why many struggle to build successful AI-native companies.

“It's so hard to actually build anything as a product builder, but you have to figure out the sweet spot of still being useful for a particular set of users,” he said.