"This isn't just another coding assistant; it's built for the complex, long-running tasks that define real software engineering work. What Makes GPT-5-Codex Different The most significant change is how GPT-5-Codex adjusts its thinking time according to task complexity. For quick questions or simple fixes, it responds fast. However, for large refactorings or complex debugging sessions, it can work independently for hours, up to seven hours in testing, iterating on solutions until they are successful."
""GPT-5-Codex represents a significant leap forward in how AI can be applied to real-world software engineering. We've long anticipated that AI would evolve beyond simple code creation to tackle much more difficult problems and complex development tasks, and this release shows that it's truly happening," said Mitch Ashley, VP and Practice Lead of Software Lifecycle Engineering at The Futurum Group."
GPT-5-Codex adapts its reasoning time to match task complexity, responding quickly to small fixes while running autonomously for hours on complex refactorings and debugging. The model uses far fewer tokens for simple tasks and increases editing and testing effort for difficult work. Training focused on real-world engineering tasks enables building projects, adding features, debugging production issues, and performing thorough code reviews. Benchmarks show improved performance on complex refactoring tasks versus GPT-5. The model also emphasizes deeper code review capabilities by understanding project context, navigating codebases, checking dependencies, and running tests.
Read at DevOps.com
Unable to calculate read time
Collection
[
|
...
]