Quick tip on how to get the current model served by codex:
RUST_LOG='codex_api::sse::responses=trace' codex exec --sandbox read-only --model gpt-5.3-codex 'ping' 2>&1 | grep -m1 'SSE event: {"type":"response.created"' | sed 's/^.*SSE event: //' | jq -r '.response.model'Before running this command, I need to enter a trusted directory first.
Agentboard and iOS Codex Access
There are quite a few projects that are designed to help access agentic CLI tools, such as codex, from an iOS device. I have researched several of them, and the best is Agentboard. It uses Tailscale to seamlessly visit a home computer or a server via just a web browser on the phone, and connect into any live codex sessions there. So far, Agentboard offers the best experience of connecting to a codex session from my phone, and is much better than other alternatives, such as happy.engineering, tgterm, or directly using Openclaw with Telegram.
A Language for Agents
A Language for Agents, by Armin Ronacher, is an excellent (but long) essay about the future of programming languages in an agentic world.
Though it lobbied for a new language only for agents, it also made a strong case for using Rust and TypeScript (and perhaps also Go) as “the agent’s language,” but not nearly as much for Python, which is not strongly typed.
In my personal opinion, we can just settle for TypeScript and Rust as the programming languages of choice going forward when starting greenfield projects, and only use Python for machine learning. To reduce the cognitive load, we shouldn’t be learning programming languages beyond TypeScript (as the first language) and Rust (as the advanced, performance-oriented alternative) for general-purpose programming, and perhaps Python for its ecosystem in machine learning.