Chamath Palihapitiya: AI Coding Adoption Could Turn Engineers Into 'Slot Players'

Venture capitalist Chamath Palihapitiya has sharply criticized the increasingly massive adoption of artificial intelligence (AI)-based coding tools. In a post on X on Sunday (Sept. 20, 2026), he argued that the phenomenon could turn technical experts into mere button-pressing operators rather than solution creators.

Palihapitiya highlighted a work pattern he considers counterproductive. "People are working 12 to 13 hours a day just to press enter," he wrote. He described the situation as turning an entire generation of technical experts around the world into retirees sitting in front of casino slot machines. According to him, this is a form of brain rot similar to endlessly scrolling social media.

The criticism is not unfounded. Throughout 2026, a number of major technology companies reported a surge in AI use in software development. OpenAI President Greg Brockman revealed in May that AI tools had written 20% to 80% of developers' code in just one month. Alphabet's Google even reported that 75% of its new code was generated by AI and approved by engineers. Meanwhile, Uber CTO Praveen Neppalli Naga said in March that 95% of the company's engineers use AI tools every month, with AI coding agents producing about 1,800 code changes per week without human writing.

Palihapitiya does not reject automation, but he emphasized that the real value of automated software is not execution speed. "The value of automated software is not making software faster. It is understanding your intent and making software BETTER," he stressed. He mentioned the need for edge advantage, better design, and higher alpha. Without clear intent, companies will only accelerate bad code.

He proposed four pillars that companies should focus on: intention, governance, verification, and evidence. According to him, bottom-up tool adoption will only increase costs and accelerate slot-machine behavior. Therefore, he stressed the importance of leadership from CEOs, CFOs, and CIOs in guiding AI use strategically.

"We are turning an entire generation of technical experts around the world into the equivalent of retirees pressing buttons in front of casino slot machines. At its core, this is the brain rot of social media doomscrolling." — Chamath Palihapitiya

Palihapitiya's view aligns with notes from Boris Cherny, the engineer behind Anthropic's Claude Code. Last month, Cherny said that AI coding tools are getting better at handling routine bugs, but are actually creating more complex challenges related to system design, interface usability, and broader context. He highlighted the importance of adversarial code review and the /code-review feature to catch such issues.

For Indonesia, this warning is relevant given that the wave of AI coding adoption is also beginning to reach startups and technology companies in the country. Without a clear governance framework, Palihapitiya's concerns about declining quality and the loss of technical skills could become reality. Companies need to ensure that AI is used to strengthen reasoning and creativity, not merely to chase speed. Regulators are also urged to start thinking about verification and accountability standards in AI-based software development.

Going forward, the question is no longer whether AI will dominate code writing, but how organizations can integrate it without sacrificing quality and long-term competitiveness. Will companies choose shortcuts that accelerate bad code, or build a stronger foundation with clear intent and strict verification?