OpenAI Codex Review 2026 — Updated from Daily Use

## The real test: Daily production use When I wrote my initial review in May 2025, Codex felt promising but rough around the edges. The kinds of tasks it could handle reliably were limited, error handling was poor, and multi-turn conversations often derailed. Fast-forward to March 2026, and I'm using Codex as a core part of my development workflow both personally and at WorkOS. The difference isn't subtle—it's night and day. … ## What still frustrates me ### Model selection opacity You still can't choose which model handles your task. Codex picks internally based on task complexity, repository size, and probably other factors I'm not privy to. As someone who understands the trade-offs between different model sizes and capabilities, this lack of control is annoying. Sometimes I want to throw GPT-5.2 at a complex architectural decision—it's their heaviest thinking and reasoning model—and sometimes I just need Codex to generate a simple CRUD interface where a smaller, faster model would be fine.