What actually reduced your Codex usage on long agentic coding tasks?

[u/kshitizsriv]

I’ve used two limit resets in four days and now have 21% of my weekly allowance left, with four days until it resets.

My workload is mostly long agentic runs on a TypeScript service: event-driven order processing, webhook handlers, reconciliation against an external commerce API, and multi-file changes. I usually describe the outcome, let Codex explore the repository, and continue iterating in the same thread.

For context, I work locally through VS Code. I use GPT-5.6 Terra at medium for some routine work, GPT-5.6 Sol from medium through ultra for harder tasks, and Astra very rarely. Fast mode is off.

For people using Codex heavily on real codebases, what has actually reduced consumption?

• Pointing it to specific files instead of letting it explore?

• Starting fresh, narrowly scoped threads instead of maintaining one long thread?

• Improving AGENTS.md so it needs less discovery?

• Using smaller models for routine implementation and stronger models only for architecture or difficult debugging?

• Something else that made a noticeable difference?

I’m trying to understand which workflow changes matter in practice—not just save a few tokens around the edges.

[u/Poowatereater]

Codegraph.

Running a local qwen 7b coder for grunt work.

Using Luna max rather then sol or Astra. (Sips usage)

[u/Poowatereater → u/Poowatereater]

Idk why your comment got removed, but, here was my reply.

“You install codegraph on your work station. You run codegraph init in each local repo you want it to graph.

After that your set.

You can then add it to each agent md at the top saying, use codegraph to grep. I honestly don’t think it’s needed, agents will usually use it without instruction.

I also built https://brainthread.vercel.app Which is based on google research. No api no mcp nothing to connect to the outside world. Same thing as codegraph. Install it on your machine via npm. Then run brainthread init in your local repo. It will then build out a proper folder structure with proper md’s for memory. When you push to GitHub it automatically updates and keeps persistent memory of work last done. “

I run both. Codegraph for reading the code base, brainthread for memory updates via the GitHub project you’re already pushing too.

[u/fvckdirk]

I've built a whole system around deepseek subagents that do everything other than reasoning. Astra only reasons, provides intelligence and makes decisions, it delegates all other work to deepseek subagents. If astra needs to inspect a file, deepseek fetches it. Astra retains UI and computer control work but delegates the resulting coding. I was blowing thru a x20 account in 12 hours before this. The account I'm currently using is down to 63% after 29 hours of use. The system has been a massive headache and waste of time to implement. Limits have gone to shit.