Do people like this about Codex?
Something stirred around OpenAI's Codex in late March that is worth noting precisely because of how it was phrased. On March 22nd, a question surfaced inside OpenAI's ecosystem: do people actually *like* this about Codex? Not whether they use it. Not whether it ships clean code or reduces ticket time. Whether something about the experience generates genuine affection. Codex has had a strange arc — it arrived feeling like science fiction, became a foundational layer under GitHub Copilot and half a dozen other tools, and then quietly receded into infrastructure, the kind of technology people depend on without particularly thinking about. That makes this question more interesting than it looks. Companies typically ask about usage metrics and retention curves. They ask whether something is *liked* when they suspect the emotional relationship with a product is becoming strategically important — when they are trying to understand not just whether users stay, but why, and what that feeling might be worth.
If confirmed, here is what this means. OpenAI may be in the early stages of repositioning Codex — not technically, but experientially. The coding-tool market is crowded now in a way it simply was not when Codex launched, with Cursor, Copilot, Claude, and a growing list of challengers all competing for developer loyalty. Loyalty, crucially, is an emotional category. If OpenAI is actively investigating what generates affection around Codex, the second-order effect is probably a product direction that leans harder into whatever that quality turns out to be — interface choices, explanation style, the texture of how the tool communicates uncertainty. Developers who have built workflows around Codex should pay attention, because products optimized for affection tend to change in ways that feel good and occasionally break things you relied on.
Watch for any OpenAI product announcements or developer surveys touching on Codex experience specifically — and watch whether the language they use starts shifting from capability claims toward something softer and harder to benchmark.
<!-- SC_OFF --><div class="md"><p>I spent like 6 months making something manually in Flask, granted I was still learning to code, and then last week picked up a new project, in
<!-- SC_OFF --><div class="md"><p>If your only tool is a hammer, you tend to see every problem as a nail. Does anyone agree? I've found that Claude code is good for speed but when
<table> <tr><td> <a href="https://www.reddit.com/r/OpenAI/comments/1uegp90/codex_is_really_like_this_or_its_bugged_for_me/"> <img alt="Codex is really like this or it's bugged for
<!-- SC_OFF --><div class="md"><p>My developer friends (who were obsessed with Claude Code a month ago) are now all jumping ship to Codex, which has left me wondering:</p> <p>Is
<!-- SC_OFF --><div class="md"><p>The recent changes to Codex limits have significantly degraded the developer experience.</p> <p>Previously, Codex in VS Code felt fluid and
<!-- SC_OFF --><div class="md"><p>I gave my Codex agent a task that would normally take me at least 12-15 hours — multiple steps, logic handling, and some debugging involved.<br
<table> <tr><td> <a href="https://www.reddit.com/r/OpenAI/comments/1tca2va/did_anyone_here_moved_from_claude_to_codex/"> <img alt="Did anyone here moved from claude to codex
<!-- SC_OFF --><div class="md"><p>For myslef im using it a lot but it will produce so much garbage its a full time job it feels like just maintaining scope. I combined all the
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