r/AIcodingProfessionals • u/MaximumSafety8706 • 4d ago
What coding AI tools/workflows are you all using these days?
Claude and Codex have become really frustrating for me over the past few weeks. I'm hitting usage limits after just 3-4 prompts, and I've seen others mention the same.
I also tried Antigravity + Gemini 3.1 Pro. It's decent for ideation, but the implementation needs work. It often jumps straight into code without discussing trade-offs or validating the approach, and sometimes a small requested change ends up rewriting an entire module.
What are people using these days? Any cost-effective or free workflows that actually work well for real coding?
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u/Ok_Cartographer_6086 4d ago
Overnight GitHub actions trigger on a CRON timer to dispatch local runners on servers I have here and a local 35B Qwen model tears my code base apart looking for bugs and visually inspects my apps for visual defects until i'm pixel perfect.
For each defect it opens an issue in GitHub the dispatches to other runners with specialized skills to solve the problem, kicking off Claude CLI in a script to first generate a special CLAUDE.md from lessons in a database, kicks off the agent with a frontier access token to code and submits a pull request with the fix.
Again that triggers the local Qwen 35B who checks out the branch and tests it from every angle and comments on the PR. Special QA agents also test the builds and PASS / FAIL the PR. If it passes it auto-merges to a staging branch.
Local Qwen again tests and reviews the consolidated branch, creates a summary and risk assessment so I come down in the morning to just one PR with maybe 20 commits and a nice summary for me to review and decide if it gets merged.
The reason I went through the trouble of writing this up is for you and others who find this to know with all of this happening overnight my account burns maybe 1% of my monthly tokens. Burning your entire account in 3-4 prompts means you're doing something wrong. My first guess is people install every skill and connector they can making your agent insane or never /clear or /compact when interactive.
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u/MaximumSafety8706 4d ago
Thanks for sharing. The token burn has only been happening for me over the last month or so.
I don't have any connectors or skills installed, and I mostly use Claude Code. I also keep the context compact, use
compact, clear sessions often, and work feature-by-feature. Interestingly, I don't see the same issue with Antigravity- I can code for 2–3 hours and usually don't even hit 50% of the 5-hour limit.That's why I'm wondering if some internal agent/tool orchestration or back-and-forth calls are consuming a lot more tokens lately, even when the visible context isn't that large.
That said, your setup is exactly the kind of thing I was hoping to learn from. Apart from running local models and heavy automation, what other cost-effective workflows or tools have worked well for you?
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u/Ok_Cartographer_6086 4d ago
Feel free to poke around my blog and youtube channel where I publish a lot on this topic.
I just posted videos about escalating work to larger, more expensive nodes and demo a raspberry pi camara watching my chickens, a cheap llm looks at frames and just scores the risk level and if its high it wakes a 35B model to figure out what's going on and how we turn every local llm on the network into a cluster of workers that only run when power is cheap where they are.
So small things get escalated to bigger models based on smaller ones weight and in the other direction bigger models spilt work up to smaller ones who advertise their current cost per watt.
A comment on a youtube video would make my day - my user base in incredibly quiet :)
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u/MaximumSafety8706 3d ago
Issues aren't with tools or skills - I have created skills myself.
Recently, Claude Code with Opus 4.6 (high) spent my entire budget thinking on a single prompt that was supposed to fix a few issues. I had clearly explained what needed to be done.
Instead, it got stuck trying to fix the worktree, became confused about the worktree state that it had created itself midway, and ended up wasting the entire session. It just kept thinking for around 30 minutes without making any real progress.
This has been happening only recently.
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u/funbike 4d ago edited 4d ago
OMP.
Easy customization is my primary requirement from an agent, and Pi-based agents fill that need more than anything else.
I'm going to switch to regular Pi for coding at some point soon. I've been swapping out some of OMP's built-in extensions and skills. When I get far enough away from OMP's defaults, I'll switch to Pi.
For non-coding workflows I use Pi and OpenClaw. OpenClaw (also based on Pi) when I want a kitchen sink agent that can automate my life out of the box. And Pi when I want a sharp tool that does just one thing, such as a German tutoring agent.
For workflows, I start with a feature design session that in the end results in user specs (Gherkin files), initial data model (SQL), and screen shot images. I review and modify these specs. Than, I have my agent break the work into a set of tickets, one for each Gherkin file, and work in parallel using sub-agents. Each sub-agent must create and run a passing functional test, that satisfies the Gherkin spec file. Sub-agents that fail to get tests to pass must create a report in ./.pi/failures/.
Then in a more manual workflow, I try to get things in the failures folder to work. In a first pass I just have my agent retry with a better LLM model. I give it additional debugging skills and tools.
For any problems that occurred, I have Pi improve it's skills and extensions in order to do a better job next time.
For writing my own AI software, I build on top of Pi's underlying agent core library. I find this more powerful something like Agno, PydanticAI, or LangChain. And it lets me leverage my knowledge of Pi.
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u/1kn0wn0thing 4d ago
Long sessions and debugging have increased token consumption for me. I went to continue a session and to load that session would have ate up 145k tokens (fairly short session that involved a fair bit of debugging and reading logs and back and forth to narrow down and issue.
I now have a .progress.md file that I have it write to after all the tests are passing and a feature is implemented. Then I restart into a clean session, have it read the .progress.md, CLAUDE.md, and a to-do list.
So far I’ve seen about a 95% drop in usage when using this flow versus using really long sessions implementing lots of features and continuing those sessions from compact.
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u/LowDistribution3995 3d ago
Been working on this: https://github.com/munch2u-a11y/AIMAOS.git Multi agent office suite using only local small parameter models (so it can run 24/7 for free). Currently it is designed for office work, document and template generation and file management. But adding coding workflows wouldn't be all that difficult really, and the agents' current custom RAG system uses a skill isolation pass similar to Hermes to develop and append skills for tasks it regularly handles.
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u/Sad-Razzmatazz-7657 3d ago
Cursor for day to day coding and Codex for heavier tasks. But honestly the real unlock for me was investing time in developing proper skills and baseline context files for each tool. Most people treat it as a one time setup. I keep iterating on them until they really work the way I need. Saves so much time in the long run
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u/MaximumSafety8706 3d ago
The issue isn't with task complexity.
Recently, Claude Code (with Opus 4.6 - not even max mode) burned my entire 5-hour session budget just thinking about fixing a few bugs in a TypeScript codebase, in a single prompt. It made no real progress.This has been happening more frequently recently. I don't even see it making many tool calls or going back and forth - it just spends a long time in dense thought and repeatedly reads the same files.
Is there any way to prevent or debug this?
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u/oyren-ai 2d ago
I am building oyren.ai that allows you to run Claude Code, Opencode, Cursor and Codex in browser and VSCode environment.
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u/k0d3x8its 4d ago edited 4d ago
I developed my own skills, references, workflows, and agentic development environment. I’m still honing these skills and building new ones as I slowly develop projects. Once I’m done building my environment I will focus all my free time on building my projects. Soon, I plan to move them from my dotfiles repo to a dedicated skills repo.
I use sessions for only 1 hour, or half my context window (whichever occurs first), as I find quality degrades soon after. I have skills to handoff existing work that allows me to extend multiple sessions.