AI Agents Are Making Tech Workers Stay Awake Longer

SAN FRANCISCO — Autonomous artificial intelligence agents were built to execute multi-step tasks independently, yet executives and researchers in the technology sector say they often demand continuous human monitoring, prompt refinement, and real-time oversight. The result is an unexpected workplace paradox: automated systems are extending work hours and intensifying output expectations for engineers and founders rather than reducing human labor.

Lucy Guo, a venture capitalist and tech founder, described the shift as an “always-on” operational requirement. She said workers must adapt to the speed and runtime of autonomous systems during a recent interview on the *Fortune Daily Show*.

“I think AI is making people work harder actually because you have to be awake for your agents to be running,” said Guo, who co-founded the data infrastructure company Scale AI. Managing continuous AI agent workloads recently led her to complete a 26-hour unbroken workday because she “refused to go to sleep.”

The pattern also emerged in an eight-month study by researchers at the University of California, Berkeley. The researchers tracked 200 employees at a U.S. technology company and found that AI integration changed work patterns without formal instructions from management. Employees increased their output pace, broadened the scope of their projects, and moved work into off-hours instead of simply spending less time on tasks.

Early AI coding assistants and generative models have produced clear speed gains in basic code completion. The UC Berkeley findings also raised questions about work quality and output inflation in software development, as companies and workers absorbed higher project volumes that offset time saved with expanded workloads.

Guo’s background in the AI sector began during the infrastructure wave that preceded the current generative AI boom. In 2016, she co-founded Scale AI alongside Alexandr Wang. The startup became a cornerstone of the AI development ecosystem by supplying human-labeled data sets used to train large language models for major technology platforms, including Meta, OpenAI, and enterprise software providers.

Guo left Scale AI in 2018 while retaining an equity stake in the enterprise. As Scale AI’s valuation rose with industry demand for training data pipelines, that equity position made her a billionaire.

She later established Backend Capital, a venture firm focused on early-stage investments in software engineers and technical founders. Through the firm, Guo backed an early-stage startup that was later acquired by Anthropic, the AI research safety company that created the Claude large language model family. The acquisition made Guo a significant shareholder in the AI platform.

In 2022, Guo launched Passes, a web3 and creator monetization platform where she currently serves as chief executive officer. Passes gives digital creators tools to monetize content and engage direct audiences through subscription tiers and exclusive interactions.

Technical evaluation and human talent, Guo said, remain fundamental to company performance despite the heavy reliance on automated systems across her portfolio and operations. She studied computer science at Carnegie Mellon University for two years; the university is one of the country’s top-ranked programs for computer science and artificial intelligence.

“The people in a company make the company,” Guo said. She explained that baseline technical literacy helps founders and investors recruit engineers with complementary skill sets capable of building scalable systems.

Guo previously held the distinction of being the world’s youngest self-made female billionaire. Last year, that title shifted to Luana Lopes Lara, co-founder of Kalshi, the federally regulated prediction market platform.

Guo brushed off the change in financial rankings. “I think it’s a really good sign when this title is taken away because that means that, like, women are winning,” she said.