How do you make sure people continue to learn in the age of AI?
At the AI startup Valon, a new policy requires most new hires to learn their jobs the old-fashioned way, i.e., without AI.
A few takeaways stand out:
1\ AI can create an “illusion of competence.”
If a new employee asks AI for the answer immediately, they may complete the task without developing the mental model needed to recognize when that answer is wrong.
2\ The policy targets critical thinking, not productivity.
Valon allows engineers to use AI because their code goes through peer review. For finance, HR, and other functions without equivalent safeguards, employees first have to demonstrate that they understand the work well enough to challenge AI.
3\ There’s a striking economic signal.
Annualized AI-token spending fell from roughly $15–20 million to $4–5 million. That’s an enormous reduction in cost, and the social consequence may be just as important.
4\ New employees are now forced to ask experienced colleagues for help.
That’s slower in the short term, but it can accelerate organizational learning and culture, something that disappears when every question gets routed directly to a chatbot.
5\ AI should amplify competence, not replace it.
What Valon is saying is: “First become competent without AI. Then use AI to become more productive.”
In other words, AI should become a force multiplier for competence, rather than a replacement for acquiring competence.
This is particularly relevant if you’re building an AI-heavy company or workflow.
There are really two different types of AI usage:
A) Amplification: “I understand the problem; AI helps me do it 10× faster.”
B) Substitution: “I don’t understand the problem; AI produces something that looks like an answer.”
The first creates leverage. The second can create dependency and organizational fragility.
OpenAI’s launch of Astra and Anthropic’s launch of Fable/Mythos 5.1 are useful markers of how quickly the frontier is moving: AI is increasingly capable of not just answering questions, but carrying out complex, multistep professional work.
The goal should be to use AI to raise the ceiling of what humans can learn and accomplish.
That’s how AI becomes more than a productivity tool.
It becomes a force for human potential.
Until next time,
Ram
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Ram Srinivasan
MIT Alum | Author, The Conscious Machine | Global Future of Work and AI Adoption Leader published in Business Insider, Fortune, Harvard Business Review, MIT Executive Viewpoints and more.
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Ram Srinivasan currently serves as an Innovation Strategist and Transformation Leader, authoring groundbreaking works including "The Conscious Machine" and the upcoming "The Substrate Shift."
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