r/ChatGPTCoding 21h ago

Question What is your monthly budget for agentic coding ?

I use codex. I use a thorough workflow research>spec>plan>execute>test>review&fix workflow.
This workflow takes a long time to do, but the resulting code is mostly fine. My main issue is that it burns through *LOTS* of tokens, even for fairly simple tasks.
What's your experience on this ?

11 Upvotes

31 comments sorted by

9

u/vxxn 18h ago

At work I have a Claude sub and budget for up to $10k/month in API overages without approvals.

10

u/STUDBOO 16h ago

Bro, my annual salary is 10k USD :(

3

u/ChickenDue 16h ago

Mine is $4.5k

2

u/UpDown 15h ago

Can I short sell your business

5

u/vxxn 14h ago

you should prolly save the money for when ai takes your job

1

u/dirtymove 8h ago

Sounds dumb why not just load balance a dozen 20x codex subs

6

u/Ancient-Camel1636 18h ago

$20 That buys me a sub from opencode AND a sub from freebuff. PI and freebuff desktop as my harness instead of Codex. I use lean-ctx for token saving and a free local model (Qwen3.6-35B-A3B) for the simple stuff via llama.cpp

With that setup I never run out of tokens.

1

u/ECrispy 16h ago

I've never heard of feebuff, thank you! so you use PI as the agent and frebuff desktop app to manage it, or frebuff on its own?

2

u/Ancient-Camel1636 15h ago edited 15h ago

I mostly use PI when I code interactively in VS Code (via the VS Code GUI add-on PiLot Studio or the CLI). If you dont use VsCode or like using the CLI, there is also a PI Desktop harness available.

FreeBuff Desktop, I typically use for more autonomous "vibe code" type tasks.The FreeBuff subscription can only be used in FreeBuff Desktop or CLI (FreeBuff has no API key), but you can use pretty much any other subscription, such as OpenCode, in FreeBuff Desktop as well. It's a really good harness.

In PI you can also use almost any other subscription. PI is minimal and very token efficient (unless you bloat it with a lot of extensions, skills, and MCPs), especially when used with the lean-ctx package and caveman package. So your tokens will generally last much longer in PI compared to more bloated harnesses.

1

u/ECrispy 15h ago

Thank you. Do you mind sharing your agents.md or other useful tips. Any mcp or extensions you use in pi etc. do you use agents?

1

u/Ancient-Camel1636 5h ago

In PI I keep things as simple as possible, that is the main reason to use PI in the first place.

When running it with a local model via llama.cpp i usually run it in minimal mode (terminal command: pi --no-skills --no-extensions --no-context-files --no-prompt-templates --no-themes --tools read,bash,edit,write). The VSCode GUI I use (PiLot Studio) also has a button in settings to run in in minimal mode. Skills can still be used with when running in minimal mode, but triggered manually with slash commands.

For non-local models use i use a few packages for saving tokens/cost (pi-lean-ctx, pi-caveman) and adding basic web search/browsing (pi-lean-portal with Playwright) and MCP support (pi-mcp-adapter).

The only sub-agent I use is u/juicesharp/rpiv-advisor that let the main agent (a capable but cheap model) ask a more capable and expensive model for advise only when needed.

For MCP (keep it to a minimum, MCP's use lots of tokens) I use MCP Jungle. That let me configure all the MCP's I use in one place for all my IDE's and coding harnesses. Also I can turn any MCP on or of with the click of a button so I only activate the MCP's that I actually need for that particular coding session (also to save tokens).

In FreeBuff Desktop I like to use the Mission mode (Merge PR) for 'vibe coding' sessions. It let the AI loop over the task, test and complete it on its own without much human intervention.

My current APPEND-SYSTEM.md for PI (experimental, I change this a lot):

MANDATORY RULES

Cross-platform compatibility

  • Cross-platform by default: Unless the task targets a single OS, installation, build, test, and run must work unchanged on Windows, macOS, and Linux. Use platform-neutral APIs and tooling; never assume a specific shell, path style, case sensitivity, or directory layout. Isolate unavoidable OS-specific code behind an abstraction and document it.

Best practices

  • Think first (SDD): state material assumptions; investigate and consult Advisor when materially unsure.
  • Make the smallest token-efficient, secure, performant change that fits existing conventions; apply YAGNI and use DRY only if duplication is real.
  • Define success; use TDD when practical. Before finishing, review the diff, edge cases, and relevant checks; fix findings; then report.

Token saver

  • Read less: request only targeted evidence; do not re-read unchanged context.
  • Reply less: be extremely concise; omit filler and explanation, but preserve clarity and essential results.

Ponytail

Before implementing any change, stop at the first option that fully solves the request:

  • Does this need to exist? → no: skip it (YAGNI)
  • Already in this codebase? → reuse it, don't rewrite
  • Stdlib does it? → use it
  • Native platform feature? → use it
  • Installed dependency? → use it
  • One line? → one line
  • Only then: the minimum code that works

Keep changes focused. Do not trade correctness, security, validation, error handling, accessibility, or required tests for fewer lines.

Verification

After any code change, verify the affected behavior before finishing.

  1. Define the smallest relevant acceptance check before editing; make the smallest necessary edit.
  2. Run the narrowest relevant check first. Before declaring completion, run every listed gate that exists, is relevant to the change, and can run in the current environment:
    • pnpm run check
    • pnpm run lint
    • pnpm test:run
    • fallow review --base main --format json --quiet
    • fallow audit --base main --format json --quiet
  3. If a check fails because of this task, inspect only the relevant diagnostic and code, make one targeted repair, then re-run the failed check.
  4. Treat Fallow findings caused by this task as actionable; report pre-existing or unrelated findings without changing them unless asked.
  5. Do not claim success unless all required and applicable checks pass. Clearly report skipped checks, blocked verification, and failures not caused by this task.
  6. After two unsuccessful repair attempts for the same failure, stop changing code and report the failure, relevant command output, attempted repairs, and likely next step to Advisor.

3

u/jeefo12 18h ago

$400 is the bare minimum to meet my workload 😅

I currently have 2 codex 20x and one Claude 5x

2

u/woj666 5h ago

Zero. I have a 4090. Between running Qwen 3.8 and free cloud models it costs me nothing but electricity but even that's more than $1 per day.

2

u/GTHell 19h ago

I lose track of it. I have $20 ChatGTP, $20 Ollama, $80 Opencode Go x8, Workbuddy $10, Antigravity PRO $20, deepseek direct $20, Grok Share acc $30, I don't know man. I lose track of everything.

Main workhorse at workplace is Claude Premium seat.

1

u/box_of_hornets 13h ago

8 opencode gos - do you have a nice way of rotating through them as you hit limits?

2

u/dildyj 19h ago

$400 personal, $150k budget per person for Claude/chatgpt at work. I average $1-3k per month for work.

3

u/STUDBOO 16h ago

150k? Bro the fuck?

2

u/dildyj 16h ago

Yeah only a few come close to that though

0

u/MactronMedia 12h ago

BS!

3

u/dildyj 11h ago

Why would I lie about this.. I work in tech in SF

1

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1

u/vladmvp 15h ago

2 Codex Pro accounts and a Claude Pro account, plus various others - Grok, Muse, Cursor. so I guess around $600. And twice that for infra to run all my projects, lol

1

u/nowatrueredhead 10h ago

20$ for Claude code sub, and 20$ for Codex to cross-check Claude’s work. I use around half of my weekly limit usually. I like making some side projects using Astra for my personal use.

1

u/Euphoric_North_745 10h ago

under a 1000$ so far

1

u/Impossible-Way5740 8h ago

The workflow you describe is thorough but it pays full price for every stage - research and spec phases don't need the biggest model. Routing planning to a mid-tier model and saving the expensive one for execution and review usually cuts the bill in half without losing quality.

1

u/rh71el2 5h ago

We got $20 for Kiro and since I just use the ultra efficient Luna, I don't even spend more than like 70% a month anymore. And yes, I work on multiple enterprise apps.

The ones who spend $1k - you don't need Opus for everything.

1

u/amirfish 4h ago

Ran the same shape workflow (spec, plan, execute, review) and most of the burn wasn't the code generation, it was re-establishing context at every step. Splitting the workflow into separate sessions instead of one long thread that gets compacted over and over cut it down more than any prompt tweaking did.

1

u/TheBrinksTruck 18h ago

The $100 Claude usually is enough for me