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Twitter’s Parag Agrawal returns with parallel web systems

Former Twitter CEO Parag Agrawal emerges with AI startup
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A daring wager on artificial intelligence, Parag Agrawal, the former CEO of Twitter who was fired following Elon Musk’s takeover, has returned to the IT industry. The goal of his new business, Parallel Web Systems Inc., is to create AI agents that can gather and analyze web data on their own.

Agrawal stated in a Friday LinkedIn post that Parallel’s first significant product, the Deep Research API, already powers “millions of research activities everyday” and occasionally surpasses top AI models, such as OpenAI’s GPT-5, as well as human researchers. According to Bloomberg, the business now employs 25 people and has raised $30 million in funding.

Twitter's Parag Agrawal returns with parallel web systems

From Twitter to an innovator in AI

After leaving Twitter, Agrawal, who had previously developed machine learning systems there and later served as its CEO from November 2021 to October 2022, said he went back to doing practical AI research by reading scholarly articles and coding once more. He was offered positions as a “fixer” at faltering tech companies, but he decided to focus on AI since he thought it will shape the internet’s future.

His original concept was a healthcare platform driven by AI, but he changed his mind when he realized that web usage would soon be dominated by AI agents.

Also read: Crypto and Fintech leaders urge Trump to ban bank data fees threatening innovation

The rise of AI agents

Speaking to Bloomberg, Agrawal predicted:

“There’ll be more agents on the internet than there are humans around. You will probably deploy 50 agents on your behalf to be on the internet… and that’s going to happen soon, like next year.”

Recent observations from Coinbase developers, who contended that self-governing AI agents would emerge as Ethereum’s most significant users, are in line with this view. Agents might start stablecoin transfers on their own with standards like EIP-3009, enabling use cases ranging from AI models making money off of digital content to self-driving automobiles paying for gas.

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