By StartupHub.ai –
Publication Date: 2026-04-24 21:05:00
Denis Yarats, Co-founder and CTO of Perplexity AI, a company known for its AI-powered search engine, recently shared insights into the capabilities of a new language model, tentatively referred to as GPT-5.5. In a short video, Yarats discusses how this advanced model, which he integrated into an internal tool for generating a GitHub pull request merge time dashboard, demonstrated significant improvements in precision and efficiency. The project, which he had been deferring due to its perceived complexity, was completed in under an hour thanks to the new model.
Introducing GPT-5.5: Precision and Efficiency
Yarats’ primary focus was the remarkable efficiency of GPT-5.5. He stated, “GPT-5.5 is very precise and very token-efficient.” This efficiency was not just an abstract concept but a tangible benefit observed in a real-world application. He elaborated on the development of an internal tool that analyzes GitHub pull request merge times. Previously, he anticipated this task would take days, but the integration of GPT-5.5 dramatically accelerated the process.
The full discussion can be found on OpenAI Youtube‘s YouTube channel.
The video showcases the interface of the generated dashboard, which displays metrics like median, P95, and average merge times, along with monthly trends and distribution charts. The tool utilized the GitHub CLI to collect a snapshot of repositories and merged pull requests,…