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Sam Altman's sprint to correct OpenAl's direction and fend off Google
Mint Hyderabad
|December 10, 2025
The CEO is prioritizing achieving mass popularity through ChatGPT versus moonshot projects like artificial general intelligence
When OpenAI CEO Sam Altman made the dramatic call for a “code red” last week to beat back a rising threat from Google, he put a notable priority at the top of his list of fixes.
The world’s most valuable startup should pause its side projects like its Sora video generator for eight weeks and focus on improving ChatGPT, its popular chatbot that kicked off the Al boom.
In so doing, Altman was making a major strategic course correction and taking sides in a broader philosophical divide inside the company—between its pursuit of popularity among everyday consumers and its quest for research greatness.
OpenAI was founded to pursue artificial general intelligence, broadly defined as being able to outthink humans at almost all tasks. But for the company to survive, Altman was suggesting, it may have to pause that quest and give the people what they want.
The move was striking in part because one criticism of Altman’s leadership has been his reluctance to put limits on what the company can accomplish.
And it was telling that he instructed employees to boost ChatGPT in a specific way: through “better use of user signals,” he wrote in his memo.
With that directive, Altman was calling for turning up the crank on a controversial source of training data—including signals based on one-click feedback from users, rather than evaluations from professionals of the chatbot’s responses. An internal shift to rely on that user feedback had helped make ChatGPT’s 4o model so sycophantic earlier this year that it has been accused of exacerbating severe mental-health issues for some users.
Now Altman thinks the company has mitigated the worst aspects of that approach, but is poised to capture the upside: It significantly boosted engagement, as measured by performance on internal dashboards tracking daily active users.
“It was not a small, statistically significant bump, but like a ‘wow’ bump,” said one person who worked on the model.
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