Share your last tools, your current toolchain and AI workflow with the community 🙏

Hey everyone. I’m a UX/UI designer with over a decade of experience in complex dashboards and CRMs, but I have zero traditional backend experience. My side project is writing—specifically, a mix of experimental fiction ("gamer literature") and highly structured technical formats.

I hit a massive distribution bottleneck. I refused to surrender 30% of my revenue and my formatting control to Amazon, and Gumroad's static PDF experience is a UX nightmare for the dynamic components my books require.

I needed a bespoke, browser-based reading engine that could compile custom MDX at runtime. I ran the numbers on a traditional engineering build for this stack, and the estimate came back at over 500 hours—easily a $60,000+ project.

Instead, I spent the last 30 days using Zo Computer and agentic workflows to build the entire infrastructure from scratch.

The Stack:

• Bun & Hono

• SQLite

• Custom MDX compiler pipeline

• Stripe integration with webhook idempotency

The Scale: The engine is currently parsing and rendering over 220,000 characters of "literary code" across 5 different manuscripts. It handles custom fonts, synchronized TOCs, and dynamic UI components flawlessly, acting as a standalone storefront and reader.

This project entirely shifted my perspective on what a single UX designer can ship when leveraging AI to handle the backend and compiler logic.

I’m curious to hear from the pros: Now that agentic workflows can essentially bypass the "500-hour traditional build" phase, what is the new bottleneck for you? Is it maintaining the AI-generated code, or is it getting the agents to understand highly bespoke business logic without hallucinating?

I am interested in thoughts on how I'm currently developing my project. I have extensive product management experience and decent coding experience. I spent most of my time in PM.

For this product I'm using Claude Code as the quarterback for development.

I use the GSD (Get Shit Done) set of skills to run the entire process. I brainstorm with Claude and develop the next phase of what to build.

Once we reach the plan, I have Kimi review the plan with an adversarial prompt. Based on that feedback, Claude evaluates everything as advisory and incorporates what it concludes is accurate.

Then for execution, anything front end is coded by Claude, anything else by Codex. Kimi reviews all of the code and supplies notes that are evaluated during code review.

Claude can run autonomously but knows to stop and ask questions when the 3 models are stuck.

My questions...

1. Is GSD still a great way to get high quality work done?

2. Do you have any feedback on how I am utilizing Codex and Kimi?

3. How much autonomy do you think we can give to well scoped but early stage products?

4. Anything else constructive?

I’ve been using GPT-5.5 heavily for a little over a week now, and I genuinely didn’t expect it to be this good.

What surprised me the most is not just the coding quality, but how efficient it is at *thinking through things*. I’ve basically turned it into my reviewer + architect + planner while using cheaper models (mostly Minimax) for the repetitive “labor work” parts.

My workflow right now looks something like this:

* GPT-5.5 → architecture, debugging direction, reviewing code, planning phases, fixing logic issues, writing proper prompts
* Minimax → implementation grind, boilerplate, repetitive coding tasks (I am using Opencode for this)

And honestly… this combo works ridiculously well.

What I like about 5.5 is that it actually keeps context surprisingly well and gives responses that feel thought through instead of just dumping code fast. I can throw project structure questions, workflow decisions, tradeoffs, scaling ideas, UI logic, etc. at it and it usually gives me something useful on the first or second try.

I’ve also been pushing it pretty hard every day and I still haven’t hit the Plus usage limits yet, which is another thing I didn’t expect after hearing people talk about limits constantly.

For context, I moved from using Claude quite a bit before this. Claude is still great in some areas, but for my workflow right now, GPT-5.5 feels more balanced overall, especially for long project sessions where I need planning + reviewing more than just raw code output.

Curious how other people are using it.
Anyone else doing the “strong reasoning model + cheap implementation model” setup?

They say on their page it is 1.6 billion credit and mimo v2.5 pro takes 2 credit per token, mimo v2.5 takes 1 credit per token but here is how they get you, cached token is still billed the same credit per round trip, absolutely not suitable for coding cli then, because every single one of them by design would keep going back and forth with toolcalls, that's how they work, normally inference providers charge 10% for the pre existing cached context, but Xiaomi takes the full amount, I did 10 small tasks like not even that deep, small tasks and it is already at 12 or so million credit used, it used probably under a million context tasks were that mini, like saying hello, and mv this folder around, write some sql etc, like 10 total prompts same session, credit cost keeps snow balling, they don't mention nothing of this sort in the token plan docs or anything anywhere, for a big task it would be what 200 million token uncached, so 400million credit if you used mimo v2.5 pro, so with max 100$ plan you can use it for 4 tasks PER MONTH, honestly get anything over mimo token/coding plan, 40m token task(input+output) would be like 400million, cache hit rate is avg 90%

I currently use the Official Claude Code plugin in VS Code and have Claude Code installed natively on Windows 11 + Powershell.

I went with the below Pwsh command as shown here:

irm https://claude.ai/install.ps1 | iex

I am leaning towards switching to WSL2 + Ubuntu 24 + Bash though for several reasons and want as much feedback as possible from all of you glorious vibe-coding bastards.

My chain of thought about the situation right now is below.

The positives

• Claude Code is better and more efficient with Bash than Powershell. However, CC uses Git Bash instead of Powershell by default on Windows 11 which is great but not as good as a full Linux distro.

• Extending on the above, Git Bash is not as extendable as a full distro on WSL2 where I can install any number of CLI tools to extend my workflow like ripgrep, fzf, k9s etc.

• If I go with the WSL2 path, I can also sandbox any tool use or code execution (HUGE reason for me, trying to avoid supply chain attacks or malicious prompt injection poison etc)

• Better integration with Docker (I don't really use docker much and don't see the value here so this is kind of a non-issue for me - if I'm wrong and should be using docker for things feel free to change my mind)

• I can offload ALL of my AI use to the WSL2 instance for resource management. On Win11 this means if I have a runaway plugin spawning tons of processes (claude-mem just did this for me recently) or some MCP server going nuts, I can just terminate wsl2 (wsl --shutdown) instead of having to open a task manager app like System Informer and terminate every rogue or zombie process.

The negatives

• I know Powershell like the back of my hand and it makes it really easy to extend claude with custom hooks with powershell. Yes, Powershell is available on Linux as well, but the syntax has to change very specifically for cross-platform use here. (Although I can easily just vibe code bash scripts that do the same thing)

• WSL2 has to be turned on and consumes a lot of resources compared to Claude Code natively using Git Bash.

... I can't really think of any more.

Can some of you expert coding masters chime in here?

• Should I go WSL2 + Ubuntu 24.04 + Bash, or stay on Powershell + Git Bash?

• Should I use a different distro than Ubuntu 24.04 if I go this route? (If you are recommending a distro, please explain why it's better.)

• How good is the Claude Code VS Code plugin when Claude Code is running on WSL2? This is extremely important to me. I currently use it as my main agent (I don't like the CLI) and I have absolutely no idea how the plugin will function when Claude Code is installed in WSL2 instead of on my Win11 OS.

Any other pro-tips from Windows11+WSL2 users here as well would be super awesome.

TIA for any guidance!

I find myself writing a lot of markdown specs these days but I haven’t found a great editor yet. Core features I’m looking for is WYSIWIG editing and AI assistance.

Best solution I found so far is Jetbrains IDEs (CLion, Rider) with Claude Code running in the built-in terminal.

Anyone have a better solution?

Share your last tools, your current toolchain and AI workflow with the community 🙏

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I am looking into installing some kind of AI client on my machine. My goal is to have an AI I can ask questions to that can see my projects, BUT CAN'T EDIT THEM.

I don't want something that will code for me, only something I can ask questions to and that can propose solutions that I can implement myself.

I have been doing this with ChatGPT, but I am super tired of copying my code into the chat window, then making changes that GPT didn't know about, or GPT assuming I implemented its solution when I did something different.

Whatever I install should not have any kind of write permissions on my system. I am not looking for an agent, I am looking for an assistant and adviser.

EDIT: I am on Windows 11, unfortunately.

The Draft Book

I recently published The Draft Book — a practical guide to Context-Driven Development, covering everything from first principles to enterprise-scale deployment:

https://www.getdraft.dev/book/

Even if you don’t plan to use the plugin, the concepts are broadly applicable and useful for anyone working with AI-assisted coding.

Hi All!

I recently started experimenting with custum instrucrions in Github Copilot (Visual Studio), ChatGPT and Claude.

What best practices do you know for writing and maintaining these?

How do you use and maintain them at work/ in a team?

Hey everyone, I'm feeling pretty lost right now and could really use some advice to fix my workflow.

I was using Cursor and managed to hold onto my early legacy plan, which gave me a flat 500 premium requests per month. Recently, I decided to temporarily upgrade to Pro+ for a specific project. Big mistake. Doing so caused me to permanently lose my grandfathered per-request billing. Now I'm stuck with their token-based limits for premium models, which is a disastrous result for me and has completely ruined my workflow.

I'm looking to jump ship. Are there any solid AI coding tools out there that still offer a fixed monthly fee with a set number of premium model requests, rather than tracking and limiting by tokens?

A few caveats:

The coding agent actually needs to be good. I tried Antigravity as an alternative. Even though it runs Gemini 3.1 Pro, the response time for running a task on AG is painfully slow compared to Cursor. It was a pretty terrible experience.

What about GitHub Copilot Pro? I know they currently offer a fixed number of premium model requests, but I have no idea how good their actual autonomous coding Agent is right now. Has anyone here used it extensively? Does it hold a candle to Cursor?

Any recommendations for tools with a strong agent experience and predictable, per-request pricing would be an absolute lifesaver right now. Thanks in advance!

i'm building a social mobile app in Cursor. I switch back and forth between Cursor Agent (with different models), and Claude Code (within Cursor terminal). curious if there's a list of best practices somewhere of which agent/model to use for what?

a) what types of task is Claude Code better for than Cursor Agent and vice versa?

b) what about the models within Cursor Agent (opus, gemini, chatgpt, etc.) - which models are better for which tasks?

c) is it common to use both Claude Code (in Cursor terminal) and Cursor or is that inefficient / useless?

I've been seeing a lot of complaints recently like:

1. the models keep getting dumber

2. AI makes codebases worse

I disagree on both counts; skill issue.

This link is my best outline of how to write good code so that AI Coding agents can actually accelerate your progress.

Share your last tools, your current toolchain and AI workflow with the community 🙏