OpenAI’s latest release, GPT-5-Codex, is more than an upgrade. For developers, it feels like a new generation of AI coding assistance. Unlike previ...
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Ali Farhat on September 15, 2025
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This is a fantastic breakdown of GPT-5-Codex! Is GPT-5-Codex the turning point where AI becomes a true coding collaborator rather than just a helper?
Great Breakdown of Gpt-5 Codex
I wonder how well it handles niche languages. Codex was decent with Python and JS, but I got mixed results with Rust.
Good point. GPT-5-Codex has broader multi-language support, but performance still varies. It’s strongest in popular ecosystems (Python, JS, TypeScript, Java) while niche languages may need more testing.
Yes, just like I want to use Codex for a Laravel project from PHP, I have to do the testing myself because Codex itself does not use the internet. Even though we can set up the environment to connect to the internet, there are risks involved.
Exactly!! GPT-5-Codex won’t replace testing. It can speed up scaffolding and code generation for frameworks like Laravel, but every output should still go through your normal testing pipeline. That’s where the balance lies: use Codex to accelerate delivery, but rely on your own validation for quality and security.
The AI code review part sounds promising, but I’d still be cautious. Automated reviews can miss subtle logic issues. Do you think teams should trust it fully?
I wouldn’t replace human reviewers. The value is in filtering out repetitive issues (style, obvious bugs) so humans can focus on design and architecture. It’s about speed and consistency, not full replacement.
Thank you!
It seems that support for JetBrains is not there yet.
Has anyone tried this for real work already?
This article offers a great perspective. It not only discusses code but also how foundational large models empower various specialized fields.
Really interesting breakdown. I’ve been using Copilot for a while, but context limits have always been painful. Curious if GPT-5-Codex finally fixes that.
Yes, that’s one of the biggest upgrades. GPT-5-Codex can reason over entire repositories instead of just single files, which makes it much more usable for real-world projects.
In your opinion, how should we divide the portions in using codex in our development? Do we need to give directions to our team to use codex?
You don’t need to assign Codex as a fixed percentage of the work. The best approach is to define clear guardrails: let the team use GPT-5-Codex for repetitive tasks, reviews, and boilerplate, but keep design and architecture decisions human-led. That way, you get speed without losing control.
Thank you!
This is a great deep dive! I'm wondering how you see tools like this integrating with industry-specific data models, like BIM (Building Information Modeling) or other complex 3D datasets common in PropTech. Could GPT-5 Codex effectively generate the Python scripts needed for data extraction and analysis from such complex sources? That's a question we're often tackling at Spot2.mx.