Human Typing Speed and Review Time Now the Biggest Bottleneck in Race to AGI, Says OpenAI Executive

OpenAI Reveals Why Human Reviews are Holding Back AI Productivity Growth

This issue highlights the growing limits of AI interaction. In the past, experts focused on computing power and model size. Today, those areas move fast. Human involvement now creates the biggest delay. According to Embiricos, this problem affects many industries using AI tools. He believes the next phase of growth needs a major shift. must work reliably on their own. They should require less checking and fewer corrections. When systems become dependable by default, productivity can rise sharply. Embriicos described this growth as gradual at first, then sudden. Early users of better automation may see clear gains soon. Larger companies may follow as trust in AI systems increases. This change could drive strong across sectors. However, he also warned against simple solutions. Every use case differs. Fully autonomous AI systems need careful design. Some tasks require more control. Others allow more freedom. The path to AGI will involve many steps, not one breakthrough. Moreover, this change affects the future of work. By the time AI automation reaches its peak, the human roles might have changed. The workers might be engaged only in planning, decision-making, and creative work. Routine typing and checking may become less common. For years, the focused on faster chips and bigger models. Embiricos adds a new perspective. Human typing speed now plays a central role. Progress depends on better system design and smoother human-machine interaction. The message is clear. Smarter AI alone is not enough. Reducing human friction may decide how fast AGI becomes real.

Human typing speed is slowing the race to AGI, says senior OpenAI executive

Early adopters could see sharp productivity gains as soon as next year, with broader automation paving the way for AGI. Big tech companies like Meta, Google, and OpenAI are racing to develop artificial general intelligence (AGI). While the targets for achieving that appear to be far higher than expected, senior executives at these companies have been quite vocal about it as the industry moves towards AI. A senior OpenAI executive recently stated that human limitations such as typing speed and the time required to review AI-generated work could be one of the most significant impediments to the arrival of AGI. Speaking on Lenny's Podcast as cited by Business Insider, Alexander Embiricos, who heads product development for OpenAI's coding agent Codex, said progress toward AGI is increasingly constrained not by models or computing power, but by how quickly humans can interact with and supervise AI systems. As AI agents become capable of handling larger volumes of complex work, the need for humans to constantly write prompts and manually validate outputs is emerging as a key bottleneck, he argued. Embiricos stated that while AI agents can already observe and assist with tasks such as coding, productivity gains are limited if humans must manually review every output. According to him, if we want to unlock the next stage of growth, systems must be redesigned so that agents become reliable by default, reducing the need for constant human intervention. He stated that this shift is critical for triggering hockey stick productivity growth, which happens when gains are gradual for a period of time before accelerating sharply. According to Embiricos, early adopters may see a boost in productivity as soon as next year, with larger organisations following suit as workflows become more automated. While he cautioned that there is no single solution for fully autonomous AI systems and that different use cases will necessitate tailored approaches, Embiricos predicted that AGI will emerge during the transition period between early productivity gains and widespread enterprise automation.