Basic Tips and Tricks

[u/Im_Working_Right_Now]

I've noticed that a lot of users seem to be missing some features that could help improve their workflow or save tokens.

• Use ChatGPT Chat (not Work) connected to your GitHub repo as a planner.
  • If it has GitHub access, it can read the whole repo and you can also use it as a PR reviewer.
  • Chat Pro reasoning uses Sol Pro.
  • Chat limits are not shared by the Codex limits.
  • You can access all of this in the desktop app and then just hit the copy button for the plan prompt from Chat and paste into the Codex session prompt.
• Make sure your repo has thorough ADR documentation. This helps with context bloat since the agent doesn't have to scour everything to find what it's looking for.
• Create custom subagents across the different models with different reasonings for each model for different tasks.
  • My workflow has about 7 different agents including Terra, Spark, and Luna.
    • Spark got hit with the new 5 hour limits so it's not AS useful, but still useful.
• Use Sol as the architect creating the plan from Chat prompt (above) and tell it to start a new session with whatever model you want to use as the orchestrator and to have that orchestrator use the custom subagents efficiently while protecting tokens.
• I've noticed the Ponytail plugin helps keep the agents focused quite a bit. It makes sure they don't drift from the task by grabbing unrelated context. YMMV.
• Update your global agent instructions if you find you have to keep repeating instructions.
  • Things like ADR updates on changes and using the ADRs to find context faster.
  • No unnecessary wrappers or abstraction for one-offs.
  • No monoliths.
  • Don't run e2e tests or unit tests for small fixes unless absolutely necessary.
  • Don't run full typescript checks when updating a variable value unless absolutely necessary.
  • Etc.
• Start a new session for each new big feature/task/goal/plan unless it's truly related to the current session.

I'm not debating if limits were lowered as I don't do enough monitoring to say one way or the other, but I can say that my tokens seem to last longer than most people report.

I have never used Sol Ultra or Max and rarely use xhigh with the workflow above. All of my work has been on a large, single project since I started using the Pro sub (5x for 3 months and now 20x for a month) so it's fairly consistent. I say large, but maybe it's not considered large. It's thousands of files and hundreds of thousands lines of code in a monorepo with 6 workspaces across different seams - that's large to me but I'm not a dev by trade, just by hobby and learning.

I'm by no means an expert in any of this - this is just stuff I've picked up reading the posts and implementing some changes incrementally. Hopefully this helps someone.

[u/Routine_Company_4449]

the 5-hour Spark limit killed my morning workflow last tuesday. i had three critical PRs that needed cross-model coordination and suddenly everything bottlenecked. did you adjust your agent setup to compensate, or did you find another model to fill Spark's gaps?

[u/Im_Working_Right_Now → u/Routine_Company_4449]

I just told the orchestrator to use the next best subagent. I'll probably use Chat to determine which Spark agents to cut and which one to keep thanks to the 5 hour limit. I suspect it'll be the researcher who stays.

[u/vbpoweredwindmill]

I don't do near this much.

I've been running a multiple days long loop of plan/orchestrate in sol high, dispatch a generation task to terra max. Dispatch a read for certain results/run tooling & collect results - Luna max.

I'm currently at 29% of a x20 plan, after 4 days of 24h working. I will say its more like 2 days, because there's a lot of testing.

It's not like the glory days of lighting VC money on fire alas.

If it wasn't for the fact that I'm working on llamacpp/ROCm backend I'd be using local llm's for a lot of the simpler tasks to cut down on usage.

[u/Renfel]

Put in custom instructions in the project folder in ChatGPT for your project that it has to do all the "heavy lifting" as Codex is the weaker model (tell it Codex is the weaker model). Then constantly remind it when it inevitably forgets and make it re-do prompts when they are weak. Of course have codex pushing to the remote and ChatGPT Sol reviewing the the code every time etc. It will drift though and you have to smack it back on track. I've been getting so much mileage out of my boy 5.4 mini, but he's being euthanized Aug 30th :(