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'Use AI, but don't surrender to it': Sridhar Vembu's message to engineers goes viral
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Moneycontrol•21-09-2026, 21:04
Sridhar Vembu's Viral X Post Sparks Debate on AI in Software Development
  • •Zoho founder Sridhar Vembu commented on a viral X post discussing the increasing reliance on AI tools in software development.
  • •The original post highlighted how AI is used for various stages, from writing code to resolving tickets, pushing developers to ship faster.
  • •Vembu advocates using AI as a productivity tool but warns against letting it replace human understanding and technical judgment.
  • •He stressed that engineers must remain deeply involved in understanding the systems they build, despite AI's efficiency benefits.
  • •The debate extended to whether startups and established companies should approach AI differently, with some arguing startups need speed and others predicting AI will reshape programming skills.

Key Questions Answered

Zoho founder Sridhar Vembu expressed concern that many technology teams are becoming excessively dependent on AI tools like Claude Code for every stage of software development. He warned that while AI is a powerful productivity tool, engineers must never cede their technical understanding and judgment to it, comparing the tech industry's rapid adoption to driving a fancy new car without knowing how to operate it.

The post sparked a widespread online debate about the role of AI in software engineering, with participants discussing whether startups and established corporations should adopt different approaches. While some argued that early-stage startups must prioritize speed and output over how code is built, others suggested that AI might eventually diminish the unique value of traditional programming skills.

Sridhar Vembu previously discussed a developer productivity paradox where massive global investments and increased volumes of AI-generated code have not necessarily resulted in proportional gains in overall engineering productivity. He noted that AI systems apply immense knowledge while lacking actual problem understanding, with much of the generated code solving incremental tasks rather than producing core value.