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Kilo Code engineers spend only 1% of time coding due to AI

Engineers at Kilo Code spend only 1% of their time coding due to AI agents handling most tasks, prompting concerns about automation safety and rising costs. As reliance on AI increases, tech companieโ€ฆ

AI coding agents are blowing through budgets โ€” Replit, Kilo Code, and Symbotic explain how they're managing it
VentureBeat โ€” 4 August 2026
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At Kilo Code, engineers are spending just 1% of their time reading or writing code, with the remainder of their work handled by AI coding agents. This significant shift raises important questions for development teams about which systems are safe to automate, who is responsible for correcting errors made by AI, and how to manage the rising costs of using these technologies. The trend highlights an ongoing transformation in the workplace as AI becomes increasingly integrated into enterprise workflows.

The current reliance on AI coding agents comes amid a growing demand for efficiency and innovation in software development. As businesses seek to enhance productivity, tech leaders from companies like Replit, Kilo Code, and Symbotic view this evolution as a natural progression. Emilie Schario, co-founder of Kilo Code, emphasized that engineers now engage with code primarily when troubleshooting, stating, "Unless something's really broken or debugging, 99% of the time engineers are not reading or writing code anymore." This shift underscores the changing landscape of software development in the age of artificial intelligence.

However, the increased use of AI agents also raises concerns about the financial implications of relying on these technologies. As development teams grapple with soaring token bills, they must assess whether the benefits of AI justify the costs. Jared Go, a distinguished engineer at Symbotic, noted that the focus should be on directing AI efforts to maximize efficiency. He stressed the importance of establishing clear criteria for AI tasks to ensure that the technology delivers value without excessive expenditure.

Looking ahead, the challenge for tech companies will be to strike a balance between leveraging AI capabilities and managing the associated costs. As AI continues to evolve, organizations must develop strategies to navigate the complexities of automation while ensuring that budgets do not spiral out of control. This balancing act will be crucial for sustaining innovation and maintaining competitive advantages in a rapidly changing digital landscape.

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"Unless something's really broken or debugging, 99% of the time engineers are not reading or writing code anymore."
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