MagicPath’s CEO Pietro Schirano put GPT-5.5 to the test by asking it to debug and rewrite a system post-launch. Where GPT-5.4 fell short, the new model delivered the same refactor his top engineer had spent days crafting—and it merged a frontend branch with hundreds of changes into the main line in about 20 minutes. Inside ChatGPT, GPT-5.5 Thinking speeds up tough problems with concise, structured answers. Early testers say GPT-5.5 Pro outperforms GPT-5.4 Pro on latency and complexity, especially in business, legal, education, and data science. The update shines on document-heavy tasks when paired with plugins, making coding, research and data analysis smoother. In scientific research, immunologist Derya Unutmaz used GPT-5.5 Pro to crunch a gene-expression dataset—62 samples, nearly 28,000 genes—and generate a detailed report in hours instead of months. The model handles multi-pass manuscript critiques, stress-tests arguments, proposes new analyses, and digests code, notes, even full PDFs. It feels less like a one-shot answer engine and more like a collaborative lab partner. Under the hood, delivering GPT-5.5 at GPT-5.4 latency meant reworking inference as a single system on NVIDIA GB200/GB300 NVL72 hardware. The team leaned on Codex to prototype benchmarks and sketch optimizations, while GPT-5.5 itself suggested key stack improvements. In other words, the model played a hands-on role in building the infrastructure that serves it.