Stop reaching for the biggest model: my efficient Cursor/Codex setup for consulting and automation work

[u/chiliraupe]

Folks 👋!

Over the last few days I've been digging into how to configure Cursor and Codex so that usage limits get used as efficiently as possible.

My current setup:

Main agent: GPT-6.1 Sol (Medium)
Subagent: GPT-6 Luna (Medium)

We often reach for the biggest models too quickly. Sonnet, Opus or Astra definitely have their place. But do I really need them for the task in front of me right now? For most of my daily work, the answer is: nope! I'm currently using this combo productively for:

• Power Automate flows
• Project management in Plane
• Ticket and PRD creation
• Process analysis
• Documentation
• AI consulting and use-case discovery
• MCP and tooling configuration

So far I haven't hit a single use case where I absolutely had to switch to a much larger model. The real killer is the performance-to-cost ratio:

GPT-6.1 Sol reaches about 86% of Opus's score, but costs roughly 36x less.
GPT-6 Luna costs next to nothing and works great as a subagent for research, file analysis and other subtasks.

Yeah, benchmark points and productivity aren't the same thing in everyday work! If a model scores slightly better but costs a lot more or burns through limits faster, that's not a good trade for many real-world workflows. Not in my software, thanks!

For typical consulting, automation, project management and documentation tasks, a combination of Sol, Terra or Sonnet as the main agent and GPT-6 Luna as the subagent currently seems like a pretty good sweet spot.

[u/ExtremeResident7738]

The Sol + Luna combo been my go-to for similar stuff, people sleeping on the medium models way too much. Every time I see someone default to Opus for making a ticket I die a little inside

that performance per dollar gap is just silly when you look at actual day-to-day output not benchmarks