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Valon Makes Most New Hires Earn AI Access, Projects 75% Cut in Token Spending

The mortgage-servicing startup is treating role knowledge as a prerequisite for AI use after broad access produced expensive model use and work colleagues had to correct.

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Valon Makes Most New Hires Earn AI Access, Projects 75% Cut in Token Spending
Valon Makes Most New Hires Earn AI Access, Projects 75% Cut in Token Spending

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Valon is making most new hires earn the right to use AI. The mortgage-servicing startup says employees—including senior recruits in nearly every function—must first learn their roles well enough to spot incorrect model output. Managers decide when that threshold has been met. Engineers are the exception, because Valon requires peer review for all code before release. CEO and cofounder Andrew Wang introduced the policy after seeing employees choose the most expensive models for simple assignments, apparently because they assumed those systems were usually right. He also said experienced colleagues were spending time cleaning up poor AI-generated work from newer hires. Valon has about 320 employees, and Wang projects the restriction could reduce token spending by roughly 75% this year. That is a projection, not a reported result. The policy is also changing how new recruits get help. Wang says they are turning more often to experienced coworkers, which he believes is giving them a deeper understanding of the underlying work. The broader concern is visible in a September 2025 BetterUp survey conducted with Stanford’s Social Media Lab: 40% of 1,150 full-time U.S. desk workers said they had received AI-generated work from a colleague in the previous month, and dealing with each case took nearly two hours on average. The key question is whether Valon can preserve AI’s productivity benefits while making role knowledge a prerequisite for access—and whether its projected savings hold up in practice.

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Mortgage-servicing startup Valon is using delayed AI access as a training and cost-control mechanism: most hires, including senior employees, must first prove they can catch model errors. Engineers remain exempt because code gets peer-reviewed. CEO Andrew Wang projects about 75% lower token spending this year, but that is an estimate, not a realized result. The policy is also shifting recruits toward experienced...

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    Managers decide when hires earn AI access based on their ability to identify incorrect output.

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    The rule covers nearly every function; engineers are excluded because all code receives peer review before release.

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    Valon has roughly 320 employees, making the projected 75% token reduction material but company-specific.

Valon now requires most new hires, including senior recruits in nearly every business function, to learn their roles without AI. Managers must decide that a worker can identify incorrect AI output before granting access.

CEO and cofounder Andrew Wang introduced the policy after reviewing employee use of broadly available AI tools. Wang said workers had turned to the most expensive models for simple assignments because they believed the systems were usually correct; he also said experienced employees had to clean up poor AI-generated work from newer hires.

The restriction is a notable constraint for a company with roughly 320 employees that builds mortgage-servicing software powered by AI agents. It applies across nearly all functions rather than only to junior staff.

  • Most new hires begin without AI, including senior recruits.
  • Managers decide when a hire understands the role well enough to recognize erroneous output.
  • Engineers are exempt because Valon requires peer review of all code before release. Wang said finance and human-resources teams lack comparable safeguards.

Wang said the rule is already directing new recruits to more tenured colleagues for help instead of asking an AI system to solve problems. He said those conversations are giving recruits a deeper understanding of their work. The savings estimate and the learning benefit are both Wang’s assessments of the policy’s early effect.

A September 2025 BetterUp survey conducted with Stanford’s Social Media Lab found that 40% of 1,150 full-time U.S. desk workers had received AI-generated work from a colleague in the prior month. Respondents said dealing with each instance took nearly two hours on average.

Wang said some AI enthusiasts criticized the policy in comments on a LinkedIn post. He also said experienced Valon employees generally welcomed it because they had been correcting poor-quality work from newer hires. Wang’s response to critics was an invitation to offer a better way to ensure people learn the underlying work.

Sources

  1. businessinsider.comNew hires at this AI startup have to earn their AI privileges
  2. tekedia.comAI Startup Valon Tells New Hires To Learn Without AI Before Using It - Tekedia