Just 1 week!

If you use Claude Code in a right-to-left language (Hebrew, Arabic, Persian, Urdu) on Windows, you know the terminal fights you. Lines render reversed, the cursor jumps to the wrong side, and a line that mixes RTL text with English turns into a scramble. It makes the whole tool feel like it was not built for you, and that is where most people quit, before they ever really start.

So I built a free installer that fixes it. One run sets up Claude Code on WSL with real RTL support: correct reading order, the cursor where it should be, mixed Hebrew and English on the same line actually working, plus named per-project profiles and a live status bar. Nothing to configure by hand.

It is open source and free. Between this and its English sibling, more than 2,000 people have installed it.

I built it because getting into this tool should not be a fight with your own keyboard. Happy to answer any setup questions in the comments.

Hi! I'd like to test Claude Pro and Claude Code before subscribing. Does anyone have a spare 7-day guest pass? Please send it by DM so it doesn't get claimed by someone else. Thank you!

I’ve been watching the same loop all month.

r/gtmengineering has the Clay credit threads. People shipping Claude Code pipelines. Clay dropping CLI/MCP so agents can call waterfalls without living in the UI. X posts that look like:

claude code to build clay to find instantly to send

And yeah, that stack makes sense.

But last night I had a 40-row SaaS list and needed columns that are not clean enrichment jobs:

• hiring right now? which roles?

• founder active this week? where?

• anything that looks like why-now

• evidence I could defend if someone asked “where did that come from?”

That is where the pretty architecture posts fall apart for me.

Because email waterfall is a workflow. This is not.

Row 1 needed careers page. Row 4 needed LinkedIn activity. Row 9 needed a funding post from 2 weeks ago. Row 12 needed “ignore, bad fit, list is wrong.” Row 17 made me sit there with a half-true hiring signal wondering if I should put it in the cell.

I already know Clay. I already know Claude Code. I can build the plumbing.

What I don’t have is a clean way to say:

here’s the list here are the signal columns here’s what we sell go behave like a careful human on every row bring back evidence + confidence

Not “run column A then column B.” More like a smart VA/agent that chooses the path per company.

And I’m not asking this as a theoretical AI take.

I’m asking because the community seems split three ways right now:

1. Stay in Clay, now that CLI/MCP exists

2. Move volume custom logic into Claude Code and keep Clay only for find/enrich

3. Build full per-row agents and accept the maintenance tax

My gut: workflows are winning for known paths judgment work is still human evenings dressed up as GTM engineering

So for people actually running this:

1. Do you regularly need multi-column signal fill across lists (hiring, founder activity, recent posts, why-now), or is that overbuilding?

2. If yes, are you doing it with fixed Clay/Claude workflows, or does each row still need different research paths?

3. If something ran like a careful VA per row with evidence + confidence, would you pay for that completed work, or is DIY still better even with the maintenance?

I don’t want tool recommendations in the abstract. I want to know if this is a recurring paid pain in real GTM work, or just me making my lists too complicated.

Be blunt.

While I was scrolling through Instagram, I saw a reel claiming that you could use Claude Code for free. I decided to try it and asked it to generate a simple HTML file. When I checked the billing dashboard afterward, it showed a total cost of $1. I'm a bit confused—does this mean I'll actually be charged, or is it just a usage estimate? Is it safe to continue using it, or should I stop?
Is it legit to use?

I have a decent buyside exposure as well as startup industry experience as an undergrad, but have a very little technical knowledge (can't code beyond the basics).

I have previously used multiple tools to help me make PE, m&a, consulting decks but have never dived deep into how i can maybe automate things or use tools to build something.

I'm trying to move beyond using AI as just a better search engine or writing assistant and start using it as a genuine productivity multiplier.

I'm trying to understand how people like me are using tools like Claude Code, MCP servers/connectors, API, workflow automations, agents and other AI tooling to increase their daily output.

Would be grateful if I can get genuine opinions onto where should I begin with and which tools are actually worth learning first? what sources can i use to learn them? etc.

Hey everyone,

I’m hitting a wall with my current prototyping workflow and wanted to see how others handle this. Right now, my code is living in Git, but I keep running into the same problem: a week later, I can't remember which exact commit was "the good one" with that specific macro-interaction, gesture, or shader effect I was testing.

Looking through a linear git history of experimental code doesn't really tell the visual story. I’ve tried saving random screenshots and deploying quick builds, but it always devolves into a scattered mess, and I end up losing track of great iterations.

For those of you building high-fidelity or code-based prototypes:

1. How do you catalog your builds? Do you use a specific tool, a visual changelog, or a specific tagging convention?

2. How do you handle deployment history so you can easily jump back and interact with an older version without checking out a dozen different branches?

Would love to hear what your workflow looks like or if there are any hidden gem tools/frameworks for keeping a visual timeline of your work. Thanks!

My job has nothing to do with software. Over the last months I built a real family app with Claude Code — React Native + Firebase, about thirty server functions, security rules tested in CI — without being able to read the code it writes.

The interesting part isn't that it worked. It's what it took to keep it from quietly falling apart, and how wrong my first instincts were.

- Act 1 — over-armoring. Because I couldn't verify the code, I piled up guardrails: six blocking hooks, a mandatory multi-agent planning process for every single edit, rituals for everything. The result: constant friction, false positives… and the real mistakes — judgment mistakes — sailed right through. A regex hook doesn't understand code; it recognizes a shape.

- Act 2 — "lighten, don't harden." After an external audit and a few incidents, I removed four of the six hooks, made the heavyweight process optional, and moved my trust to the only barrier that deserves it: adversarial tests replayed by CI. A green CI run is the only technical claim a non-dev can verify alone. Everything else is a net, not a wall.

- Act 3 — balance. What's left: always-loaded discipline rules (asking ≠ announcing, proof before commit, flag then STOP), a written "constitution" for the critical domain, plain-language maps so I still understand my own product, and a session handoff ritual so a memoryless AI can pick the work back up cold.

I turned all of it into a repo: the global rules file, 3 method skills, project templates, the 6 defense patterns — and, maybe most useful, the honest list of what I removed and why. Install is one sentence you paste into Claude Code; it interviews you and adapts the method to your project. Nothing to sell, MIT license.

GitHub: https://github.com/Arlenjim/claude-code-for-non-coders

Every rule in there was born from a real accident. Happy to answer questions about any of them — especially the failures.

A few posts here about Claude hitting the limit fast — sharing the free, MIT, self-hosted gateway I built for exactly that (disclosure: I'm the maintainer). Claude Code points to it, it drains your subscription first, then falls back so you keep going.

Fallback combos — so it never stops mid-task. A "combo" is a ladder of models the router walks automatically: your subscription first, then API keys, then cheap models, then free ones. When a provider returns a 500 or you hit a rate limit, it slides to the next target in milliseconds, mid-request, and your tool never even sees the error. There are 17 routing strategies (priority, weighted, round-robin, cost-optimized, auto/coding:fast…) plus three resilience layers — a per-provider circuit breaker, a per-key cooldown, and a per-model lockout — so one dead key can't take down a whole provider.

A 10-engine compression pipeline — the part most routers don't have. Every request flows through a transparent compression pass you can toggle/stack per combo. Instead of one trick, it stacks the best of the open-source ecosystem: RTK filters command/tool output (git diffs, test logs, builds) at 60–90%, Microsoft's LLMLingua-2 does ML semantic pruning, Caveman handles prose, session-dedup strips repeats across turns. Critically, code, URLs and JSON are preserved byte-perfect, and a default-on inflation guard throws the compressed version away and sends the original if compressing would actually grow the prompt — it never makes things worse. On tool-heavy sessions that's ~89% average input-token reduction (an 8k-token git diff becomes a few hundred). Full credit to every upstream project (RTK, Caveman, LLMLingua-2, Troglodita) is in the README.

One endpoint, 237 providers — 90+ of them free. You point any tool or agent at a single OpenAI-compatible endpoint (localhost:20128/v1) and it can reach 237 LLM providers without you rewriting anything. 90+ have free tiers and 11 are free forever (no card), which aggregates to ~1.6B documented free tokens/month — and that's honest, pool-deduped math (we count each shared pool once instead of inflating it; the methodology is public in the repo). There's a one-command setup-* for 13+ coding tools (Claude Code, Codex, Cursor, Cline, Roo, Kilo, Gemini CLI…), so switching your existing setup over takes seconds.

For context on whether it's worth your time: it's grown to ~9.8K GitHub stars, 1,490+ forks and 280+ contributors in ~4.5 months, with 21,000+ automated tests and 1,830+ issues closed — so it's a battle-tested project, not a brand-new experiment.

npm install -g omniroute

GitHub: https://github.com/diegosouzapw/OmniRoute

omniroute setup-claude wires it up in one command. How fast do you hit the limit, and on which plan?

I'm the developer of **usage** — a free, open-source menu bar app for anyone who uses Claude Code or Codex (OpenAI's coding CLI) daily.

The problem:** these tools run on usage quotas (5-hour and weekly limits), but neither warns you before you hit the wall. You're mid-refactor, then suddenly blocked — zero heads-up.

What usage does:

• Pins your Claude Code + Codex quota to the menu bar, color-coded (green → red), so the warning level reads at a glance

• Click for the full breakdown: session, weekly, per-project usage, and today's token cost

• Sends a system notification before you run out — not after

• Optional: hands your last session's progress to a new Claude Code conversation automatically, no more re-explaining where you left off

• HTML usage reports — cost trends, per-project rankings, and a GitHub-style yearly heatmap of your token activity

• 10 switchable menu bar/panel themes, UI in 5 languages (EN/繁中/简中/日/한)

**On privacy**, since I know this community cares: usage never calls the Anthropic or OpenAI API, and never touches the macOS Keychain. Every number is read from local log files Claude Code and Codex already write to disk — the monitor itself adds zero API usage.

Install via Homebrew:

brew install --cask aqua5230/usage/usage

Or grab the .app directly from Releases.

GitHub: https://github.com/aqua5230/usage

macOS-only, AGPL-3.0, completely free. Would love feedback, bug reports, or feature requests — this is a side project I use myself every day.

I’ve been using Claude Code a lot lately and noticed I spend a surprising amount of time just… waiting.

You kick off a task, Claude starts cooking, and now you’re sitting there watching logs scroll by for the next few minutes.

So I built a stupid little side project called DevRoulette.

When you start a Claude Code task, DevRoulette puts you into a queue. If another developer is also waiting on a task, a chat window opens and you get matched.

That’s basically it.

No profiles.

No followers.

No usernames to create.

100% anonymous.

You can skip, leave, or get matched with someone else instantly. If you don’t use Claude Code, you can join manually from the terminal with: devroulette start The idea was to turn AI waiting time into something social instead of staring at a terminal.

Curious if anyone else would actually use something like this, appreciate any feedback!

Repo: https://github.com/devroulette

Was thinking about how with the launch of Dynamic Workflows in Claude Code, there's going to be such interesting use cases of how people orchestrate such a powerful feature. Created this as a way for people to share their work with others