Lovable's Alexandre Pesant reports that GPT-5.5 delivers a 31% increase in intent understanding during planning and 22% fewer context-forgetting moments, translating directly to higher first-attempt success rates on large, multi-step feature builds.
The context retention improvement is the number worth focusing on. Losing track of intent mid-build is the core failure mode in AI-assisted development, and a 22% reduction in that failure is not a minor tuning gain. It changes what kinds of projects are actually viable to attempt in a single session.
The full video details how Pesant's team at Lovable stress-tested GPT-5.5 against complex build scenarios. If you care about where AI coding tools actually break down and what makes this model different from its predecessors at the architecture level, the specifics are in the source material at openai.com.
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