OpenAI executive Andrew Ambrosino says that while AI models can now write code, judging what a large product should become, from weighing user feedback to ranking features, remains a difficult problem, according to a post from The Information.
OpenAI · AI and software product development
Writing code is getting easier. Deciding what to build is still the hard part.
OpenAI executive Andrew Ambrosino says AI models can now write code, but judging what a large product should become, from weighing user feedback to ranking features, remains a difficult problem.
Product development as a cycle
Each pass through the loop involves human judgment, not just production of working code.
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STEP 2
Reassess priorities
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STEP 3
Decide which features get time and resources
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STEP 4
Build and test, faster with AI
↺ The cycle then repeats with new feedback.
Where AI helps
Writing code
Speeding up building
Speeding up testing
Handling more of the implementation work
Where judgment stays human
Weighing competing user needs
Balancing business goals
Setting long-term direction
Ranking features and choosing what is worth building
Key takeaway
Maintaining a large product is still hard, even with AI-assisted coding.
What the remarks establish
OpenAI acknowledges that AI-assisted coding has not removed the difficulty of managing a product over time.
What is not confirmed
The full context of the remarks, the scope of the argument, any concrete examples, and any specific product decisions or roadmap.
Open question
Will AI eventually help with prioritization and feedback analysis, or will those decisions remain largely a human responsibility?
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