u/CaptMcMurphy

I’m trying to make my Codex workflow more efficient by routing tasks between models, reasoning levels, and speed settings.

Instead of using the strongest model by default, I’m currently thinking about this setup:

Task type	Model	Reasoning	Speed
Small, isolated changes	GPT-5.4 Mini	Low	Normal
File lookup / scope check	GPT-5.4 Mini	Low	Normal
Simple UI / text / config fixes	GPT-5.4 Mini	Low	Normal
Normal implementation work	GPT-5.3 Codex	Medium	Normal
Multi-file patches	GPT-5.3 Codex	Medium	Normal
State logic / data flow / integration work	GPT-5.3 Codex	Medium–High	Normal
Hard bugs after failed attempts	GPT-5.4 or GPT-5.5	High	Normal
Architecture / rescue / regression chains	GPT-5.4 or GPT-5.5	High	Normal

My rule of thumb:

• GPT-5.4 Mini = scout / small patches
• GPT-5.3 Codex = default builder
• GPT-5.4 / GPT-5.5 = rescue mode only
• Low reasoning for obvious tasks
• Medium reasoning for normal coding
• High reasoning only when deeper analysis is actually needed
• Normal speed by default, unless latency matters more than efficiency

The main idea:

If a project already has a detailed implementation plan, clear coding conventions, and something like an AGENTS.md file with guardrails, the model should not rethink the whole project every time.

It should execute the next clearly defined step with the smallest safe patch.

How are you routing Codex tasks between models, reasoning levels, and speed settings?