There is no…: ChatGPT head on what you need to be successful at OpenAI
OpenAI
's head of
ChatGPT
says the one trait that determines success at the AI giant isn't technical prowess or prestigious credentials—it's the ability to build "from scratch" without following established blueprints.
Nick Turley
told tech podcast host
Lenny Rachitsky
that approaching problems without preconceived solutions is crucial because "there is no analogy for what we're building." Unlike traditional tech companies that can iterate on existing products like
or Google's offerings, OpenAI operates in uncharted territory where employees must create entirely new frameworks.
"You can learn from everywhere, but you have to do it from scratch,"
Turley
explained during Saturday's podcast. "That's why that trait tends to make someone effective at OpenAI, and it's something we test for" during the hiring process.
OpenAI prioritises rapid deployment over perfect products
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This from-scratch mentality extends to OpenAI's controversial
product release strategy
. Despite receiving criticism for launching features before they're fully polished, Turley defends the approach as essential for learning from real users.
"We get a lot of crap for the model chooser," he said, referring to ChatGPT's now-discontinued dropdown menu that allowed users to select between different AI models. However, he argues it's better to "ship out something raw even if it makes less sense" rather than wait for perfection.
The company's recent GPT-5 launch exemplifies this philosophy. Following
user feedback
, OpenAI replaced the confusing model picker with an automated "real-time router" that selects the most appropriate model for each request.
Building AI requires constant adaptation and user feedback
Turley's core argument centers on the unpredictable nature of
AI development
. "You won't know what to polish until after you ship," he explained, noting this is "uniquely true in an environment where the properties of your product are emergent."
This approach means OpenAI employees must comfortable with ambiguity and
rapid iteration
. Success requires abandoning traditional tech development playbooks and embracing the uncertainty that comes with pioneering artificial intelligence technol
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