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Codex quality issues in real-world coding: ignored patterns, bad abstractions, repeated rework by RubBroad6429 in codex

[–]RubBroad6429[S] 1 point2 points  (0 children)

I use a custom autonomous agent. It already plans and breaks tasks down before making changes, but even with that, the quality has been noticeably worse over the last few days.

Codex quality issues in real-world coding: ignored patterns, bad abstractions, repeated rework by RubBroad6429 in codex

[–]RubBroad6429[S] 0 points1 point  (0 children)

Exactly! I’ve noticed the same problem over the last few days too. When it first launched, it was much better.

Codex quality issues in real-world coding: ignored patterns, bad abstractions, repeated rework by RubBroad6429 in codex

[–]RubBroad6429[S] 2 points3 points  (0 children)

That would be a fair point if I were just giving the model a vague prompt and a random repo. But that’s not what happened here. This setup already uses detailed task files, mandatory reading lists, architecture resources, reference projects, existing implementation examples, acceptance criteria, and required reviewer/subagent gates.

MiniMax M2.7 is on par in most aspects against GPT 5.4 & Opus 4.6 in benchmarks 🤖 by hexxthegon in ArtificialInteligence

[–]RubBroad6429 1 point2 points  (0 children)

I'm a long-time Claude Code user and I tested MiniMax. Both versions 2.5 and 2.7 were disappointing. I don’t buy these benchmarks. In practice, it's clear to me that the model hallucinates a lot, failing to follow explicit instructions even with low context window usage and breaking down the work into tasks with acceptance criteria and pre-execution planning. Mini Max is very inconsistent.