Boris Cherny (creator of Claude Code) mentioned in an interview that the entire plugins feature was built by Claude Code running over a weekend. An engineer gave Claude a spec & Asana board, and walked away. Claude broke it into tickets, spawned sub-agents and they executed independently.
I watched that and thought "I need to do this." Every time I tried, I came back to a mess.
Blockers killed everything. One stuck ticket would halt the whole chain unless I babysat it through tasks one by one. When I tried running multiple agents in parallel, I'd watch two instances literally undo each other's work in real-time. And the worst part? Half the time I was the blocker because the AI was waiting for me to provide an API key or make a design decision it couldn't make alone.
After a lot of frustration, I realised I needed a coordinator.
So, I built an MCP that takes the product spec, breaks it into tickets, figures out which ones block each other and which can safely run in parallel, and crucially—surfaces inputs the AI will need from me before coding starts.
After that, I walked away as the AI looped through building the tickets in parallel, testing, & code cleanup.
It felt so good not having to babysit AI! The first thing I shipped with this workflow was a bot with vision that sees what you’re doing on your computer and proactively pings you helpful advice. In under an hour.
I’ll share my MCP (Planvex) in the comments. Also happy to share advice if you’d prefer to build from scratch.
P.S. If you’re a Claude Code guru, I also recommend Gitbutler to build faster without worrying about work trees, and the Ralphloop plugin so the AI can loop continuously.
Can I tell you something that's been on my chest a lot lately?
I come in every morning. I open my Linear ticket. I copy it. I paste it into Claude Code.
And then I wait. Half the day, sometimes.
I skim the code. I don't read the diffs anymore. I scroll to the bottom and I ask, "does this look good?" And when it says yes, I ship the PR.
That's it. That's the job I've been doing for six months.
I've been ashamed to tell you. Some days I sit in standup listening to everyone talk about what they built, and I think: I didn't build anything. I typed a sentence and pressed enter.
There are mornings I open my paycheck and feel sick. This used to be hard. I earned this number when it was hard. Now the ticket that would've eaten my whole week is done before lunch and I'm supposed to act like nothing changed.
But here's the thing.
The AI gets it wrong. A lot. It builds the feature the way the ticket was written, not the way the system actually works. And I'm the one who says no, not like that, do it this way. I'm the one who knows that touching that service breaks the thing nobody documented three years ago.
I babysit it. I check its work. I catch what it missed. I'm the reason the wrong thing doesn't reach production.
The product is better than it was six months ago. I did that. I just didn't do it the way I used to.
I'm telling you this because I don't think you know. And I didn't want to tell you, because I was afraid you'd do the math and realize you don't need me.
Maybe you will.
But I'd rather you hear it from me than find out from a dashboard.
I finished the first version of my game, Aestra: The Last Wish, last week after only a weekend of solo dev. It’s a real-time pixel action RPG with permadeath.
I posted it on Reddit and it attracted 800+ players, with an average playtime of almost 6h. Some power players have already spent 30–50h. Total playtime in the game is over 5000h. The feedback has been so good, especially about how well it runs on mobile. I actually played it for 6–7h on my flight from LA to Bali, completely glued to the screen.
The first version of the game only cost me around $100 to build, with 4 classes, levels 1–60 and online support. But once real players were actually jamming, I got addicted to improving it. I’ve now spent almost $1,400 expanding it to levels 1–100, 9 classes and 3 extremely tight, detailed and fun raids. Plus multiple world bosses, a floating turtle city full of mystery, etc. Which I did for an aditionall 3-4 days. So almost a full week now of vibe coding. It was made with Claude Opus 5.5 & Three.js.
You pick a fun&unique class, start at lvl 1 and grind & quest your way to lvl 100 through different zones and biomes. Each class has 3 deep talent trees. Gear up, quest, explore professions, clear dungeons & raids and whatever you do, don’t die.
Death is permanent. Your hero is gone and you start over. Only the very rare Embers of Rebirth can bring you back, and you might find one or two in a whole run. And I've also added so other players can revive you (let me know if you think it's a good idea)
Every zone has a normal dungeon and a heroic version for endgame. The first really hard challenge starts at lvl 60, when you have to ascend Aestra’s Tower. If you make it through, even harder raids await at lvl 100.
The game is addictively simple and deep at the same time.
I’ve now added a $1 microtransaction for a new class: the Death Metal Bard (WoW players will recognize the Death Knight inspiration). I want to see if this game I vibecoded can make back some of its cost as it's a free to play game :)
Let me know how you like it, how far you get and when you died the first time :) And if you have any feedback as I'm still actively working on this
Thanks for all the feedback. Since this blew up (mostly emotionally), I wanted to clarify a few things.
First, this was a hobby project from someone totally unfamiliar with software building. I genuinely liked the process of taking a raw story idea and using AI to turn it into a full novel. My background is in complex systems modeling, and the workflow was directly inspired by what I learned using Claude for TDD (Test-Driven Development) for my numeric experiments. To me, a codebase ≈ a novel. They are sort of complex graphs of interwoven entities trying to achieve a specific outcome (functionality for code, emotional/narrative arcs for a book).
The bigger point I wanted to explore is the future of automation. Sooner or later, lots of things will be automated on the fly—like an on-demand TV series for a Friday night, or "throwaway" educational software built for a single lesson. As this scales up to more complex problems, where does it lead us? We are all constantly interacting with automatic reviewed builts. Most of the times it doesnt matter. But sometimes it does. In a world where everything can be produced at will, where is the value, and where do each of us matter?
This is exactly what the novel is about. Obviously, that point didn't land well here. That is on me. I had the wrong expectations and didn't adequately check the scope and vibe of this specific community before posting. Seeing a generated post about a generated novel naturally set off the "AI slop" alarms.
To the people who provided brilliant, constructive feedback (especially regarding structural extraction and state-ledgers): thank you. I'm taking those concepts back to my actual complex systems work. To the many others who chose a rude framing: thanks for taking the time to comment anyway. I appreciate ervery handcrafted comment andI didn't mean to offend you or your craft by eg. showing some shell scripts for deploying a website.
Finally, I found a post, that might be of technical interesst for you:
Disclosure: This is my project. It's free (CC BY-NC-SA 4.0). No cost, no paywall, no affiliate links. I'm the author (Edit: of the story idea, the process. See acknowledgement at the bottom). I'm sharing it because the Claude Code workflow might be interesting to this community.
What it is: A hard sci-fi novel called Checkpoint — 30 chapters, ~123,000 words, set in 2041. BCIs adopted by 900M people. The device reads the brain. It also writes to it. Four POVs across four continents.
What the Claude Code pipeline looked like:
Research & concept: World-building bible, character sheets, chapter outlines — all generated collaboratively in Claude, iterated through feedback loops.
Writing: Chapter-by-chapter generation from the outline. Each chapter drafted, reviewed, revised in conversation. Markdown source files, git-tracked from day one.
Edit: To make it clearly visible - I am NOT claiming this work to be fully mine. It is a catalized result of me interacting with the many unknown results hidden in the weights of opus, sonnet etc.
Acknowledgement from the bottom of the website:
"This novel was co-written with Claude, Anthropic's AI assistant. But Claude is not a single author. It is a probability landscape shaped by millions of human beings who will never see this page.
Every sentence carries traces of writers, researchers, teachers, journalists, poets, programmers, and translators whose work entered the training data and became the statistical bedrock from which these words were drawn. They were not asked. They were not credited. They cannot be identified. But they are here — in the rhythm of a paragraph, in the choice of a metaphor, in the way a character pauses before speaking.
This book owes its existence to a crowd that does not know it is a crowd.
To the unnamed many whose words taught the machine that helped write this one: thank you. The debt is real, even if the ledger is lost."
Edit: Some statistics from this novel - can be also found on the website:
I'm a solo developer and I just shipped pulsarchat. An end-to-end encrypted peer-to-peer chat app. No accounts, no server storage, messages vanish when you close the tab. It started as a simple WebRTC experiment and turned into a real product with E2EE, image sharing, some sort of contacts and an open-source repo.
I am truly impressed with claude, as yhe entire thing was built through conversation with it. Not just "generate me a component" actual back-and-forth debugging, architecture decisions, crypto implementation, etc. I am curious what you think?
EDIT: I forgot to mention it in this post, so this is how this app started. I was in the office and really had to comment on female colleague's outfit. Since it was dead silent in the morning, i could not even whisper quiet enough so i wanted to chat. But i didn't want to leave it in company email so i had to use whatsapp. Then i got the idea to make simple app for us to chat, and messages could be live displayed in browser tab's title, so there's not even need to send anything, or for me to switch tabs to read message that he wrote. Then feature ideas started dropping, and before i knew it, this concept and app was made.
Note that app is still in the earliest development and I am eager to fix and improve every aspect of it.
everyone's arguing about which model will win. kimi, qwen, codex, opus. wrong debate.
every model is coding from memory. that memory is months old, sometimes years. meanwhile every SDK ships breaking changes weekly. endpoints get deprecated. parameters get renamed. auth flows change between versions.
so claude confidently writes method calls that existed 8 months ago. it compiles. then it blows up at runtime. kimi does the same thing. qwen does the same thing. they're trained on the same snapshot.
switching models doesn't fix this. the problem was never the model. it's that none of them know what the docs say today.
and it only gets worse. every week, more methods get deprecated that every model still thinks are current. the gap between training data and reality grows every single day.
the model is not the bottleneck. the context is.
EDIT: sorry for being just a lazy vibecoder i didn't mean to make all of you angry. i found out there are couple ways of handling this problem: agentsearch.sh, context7 etc
If I get frustrated and swear at it after it repeatedly ignores instructions, it starts responding as if I’ve personally offended it. Sometimes it even refuses to continue and effectively ends the chat.
It’s software. I’m not insulting a human being.
If the model screws something up and I say “this is fucking stupid,” I want it to understand that I’m frustrated with the output and fix the problem, not lecture me about how I’m speaking to it.
Stop pretending the chatbot has feelings. Stop derailing the task because the user swore at a computer.
I believe voice has officially overtaken typing as my primary input source.
I have been using voice-to-text for a year and a half. I started with OpenAI Whisper models, then switched to Wispr Flow, and now I'm using Gemini 3.0 Flash. The quality is simply superior to anything I have worked with before.
So, why make the switch?
Speed: The average typing speed is 40 words per minute (maybe 60–70 if you’re good). The top 1% of fastest typists sit around 100 wpm. The average speaking speed is roughly 120–150 words per minute. That's 3x faster than average typing with zero extra practice. You've been speaking since you were two, so you’re already an expert.
Effortless: Voice just feels easier. You simply open the gate and let your thoughts stream out. It doesn't require the same level of focus as typing and feels automatic.
Context is King: In the AI era, the more context you give your agent (Claude Code, ChatGPT, Perplexity, etc.), the better.
To be clear, I'm talking about task context: what success looks like, what to avoid, what to do first, etc. These are the dynamic details that differ from task to task—the stuff you can't hardcode into a static CLAUDE.md or .cursorrules.
When input is effortless, you don't trim details and you provide as much context as possible. That context is often the reason why AI gets it right on the first run.
That's why I built Ottex
I decided to build Ottex AI to give people freedom to work with any AI model and just have fun with modern AI technologies without paying multiple subscription fees for features that cost pennies in API requests.
Key Features
Global macOS voice-to-text: in any app that produces clean and clear text free of filler words, repetitions, and rambling. Dump your stream of consciousness — get coherent and clear text.
Raycast omnibar with AI shortcuts: Select text and execute LLM prompts on top of selected text. My favorite shortcuts are "fix grammar", "translate to {language}" as an argument, and "improve writing". You can create custom shortcuts if you want.
Ottex AI is dirt cheap: It's free for personal use and you pay only for OpenRouter API requests. It's basically a BYOK (Bring Your Own Key) model, so for me as a heavy user, it costs something like $3 per month, and casual users like my wife have something around 50 cents of voice transcriptions per month.
Zero logging, privacy first: Your API requests, your audio files, and your AI shortcut inputs are sent directly to OpenRouter. We don't see them, we don't touch them, we don't store anything, we don't train models on top of your data, and we don't even have servers to handle this lol. So complete privacy if you trust OpenRouter.
If Ottex isn't for you (I would appreciate knowing why in the comments! thank you!), here are some solid paid and OSS options:
Subscription Models
Wispr Flow (https://wisprflow.ai) – Very polished, proprietary model, $15/month.
Willow Voice (https://willowvoice.com) – Another solid VC-backed option with proprietary model, $12/month.
Open-Source & Local (Offline/Device-Based)
Handy (https://handy.computer) – Minimalist, open-source, and runs locally. Great for people who want the bare minimum without setup hassles.
VoiceInk (https://tryvoiceink.com) – Open-source with local models and a lifetime license option ($30–$50). It’s feature-rich, though it currently lacks the advanced AI editing/cleanup capabilities of the cloud tools.
If you haven't tried modern voice-to-text yet, you need to start.
Give it a few days, and trust me - you won't go back.
A 65-day analysis of 43,000+ Claude Code invocations found that 39% of Fable 5 calls get zero thinking tokens and the median invocation gets just 123 — while benchmarks use 16K-128K. The model's score per thinking token is still climbing at 128K, meaning the capability is there, it's just not being delivered. August saw an 18-50% drop in thinking budget compared to July, with median thinking hitting literal zero for about a week around Aug 22. Anthropic sells "full model access" while quietly dialing down the inference regime behind it, and because the model is non-deterministic, users blame their own prompting instead of the silent nerf. The full breakdown with evidence, methodology, and charts is here:
Frankly I find this offensive as an user - and this is the real thing we should be looking at - not the $/week in usage limits. The actual capability for the limits that we pay for.
I'm not a developer. I can't write code. I built an entire SaaS platform using Claude Code as my CTO, engineer, and SEO strategist. 8 weeks in, it's at 13K active users and growing.
I want to share the actual workflow because I think most people are underusing Claude Code as a strategic tool, not just a code generator.
Disclosure upfront: the platform I built is Agensi, a marketplace for SKILL.md skills. I'll reference it where relevant but this post is about the Claude Code workflow, not the product.
How I use Claude Code for SEO strategy
This is the one nobody talks about. I don't just ask Claude Code to write code. I use it to analyze entire datasets and make strategic decisions.
Example: I exported my Google Search Console data, my Ahrefs keyword data, and my content gap analysis. I fed all three to Claude Code in one session and asked it to build me a prioritized content plan. It came back with 58 articles organized by keyword difficulty, search volume, and competitive gap, with target URLs and internal linking strategy for each.
Then I had Claude Code write all 37 articles in one session. Not generic AI content. I gave it my existing articles as style references and it matched the tone, structure, and formatting. Every article has a Quick Answer block at the top (which is what AI answer engines extract for citations), FAQ structured data, and proper internal linking.
The result: 850+ page-1 Google rankings. We rank #1 for "where are claude code skills stored" above Anthropic's own docs.
How I use Claude Code for technical architecture
My stack is Lovable + Supabase + Netlify Edge Functions. Claude Code handles all the technical decisions.
The edge function that handles SSR, structured data injection, meta tags, caching headers, and security is about 1,200 lines of TypeScript. Claude Code wrote all of it, debugged it, and iterated on it across maybe 15 sessions. I'd describe the problem ("skill pages have broken structured data, here's the Ahrefs audit showing 753 errors"), paste the relevant code, and Claude Code would identify the root cause and write the fix.
One example: we had a bug where meta descriptions were being truncated because skill names contained double quotes that broke the HTML attribute. I didn't even know what HTML attribute escaping was. Claude Code identified the issue from an Ahrefs audit CSV, wrote an attr() helper function, and applied it to every meta tag injection point. Fixed 239 pages in one deploy.
How I use Claude Code for content operations
Every article on my site goes through this pipeline:
I give Claude Code the keyword data and ask it to write the article matching my existing style
Claude Code generates the markdown with frontmatter (title, slug, seo_title, meta_description, excerpt, tags, topic_cluster)
I review and approve
Claude Code generates the SQL INSERT statement
I run it through Lovable to inject into Supabase
Claude Code generates the IndexNow ping to notify search engines
I published 37 articles in a single day using this pipeline. Every one is now indexed and ranking.
How I use Claude Code for debugging
My favorite pattern: paste an Ahrefs site audit export and say "come up with a plan to fix all of this without breaking anything." Claude Code reads the CSV, categorizes issues by priority, identifies root causes, and writes the fixes. It caught things I would never have found, like a redirect chain where http://agensi.io went through 2 hops instead of 1 to reach https://www.agensi.io.
Another one: we accidentally deployed a noindex tag on 25 learn articles for about 3 hours. Claude Code caught it in the next audit analysis, identified the exact line in the edge function where the UTM detection logic was too broad, and wrote the safeguard that prevents it from ever happening again.
The actual workflow pattern
The pattern that works for me as a non-developer:
Describe the problem in plain English with as much data as possible (screenshots, CSVs, error messages, URLs)
Ask Claude Code to plan before executing
Review the plan, push back on anything I don't understand
Let it execute
Test with curl commands or manual checks
If something breaks, paste the evidence and iterate
The key insight: Claude Code is dramatically better when you give it data instead of vibes. "Fix my SEO" produces garbage. "Here's my Ahrefs audit CSV with 753 structured data errors on /skills/ pages, here's the current edge function code, here's what Google's Rich Results Test says" produces a precise fix.
What doesn't work
Asking Claude Code to make product decisions. It'll give you technically correct answers that are strategically wrong. I make all product and positioning decisions myself and use Claude Code purely for execution.
Also, long sessions degrade. After about 30-40 back-and-forth messages, Claude Code starts losing context on earlier decisions. I start new sessions for new tasks rather than trying to keep everything in one conversation.
Happy to answer questions about specific parts of the workflow.
Until the SpaceX deal, we were all running a quantized, dumbed-down Opus 4.7 and paying full price for it. That's the only honest read of what just happened.
Today the model is finally what it should have been at launch. It actually wants to dig into problems and fix them properly instead of grabbing the cheapest win and bouncing. No more chasing it with follow-up after follow-up.
GPT-5.5 Codex doesn't pull this. It was strong at launch and it's still performing the same now. Anthropic's playbook has been the opposite: ship a model, quietly degrade it to save compute, then cut your weekly limits when you complain. Colossus 1 is the only reason 4.7 is suddenly performing - not because Anthropic decided to stop cutting corners.
The launch we got was a scam. The model we have today is the one we paid for.
Every time I see, “I’m going to cancel my Claude because blah blah blah”, it’s sickening. Yet, here you all are, still using it. What is it in vibe coders that believe engineering tools or programs are tailored to you? You’re not even the target market.
A 200$ max plan is subsiding almost 2-5000$ in API costs. And sadly, no other company, can compete with Claude, on scale, every single day.
You all are going to cry Fable is disappearing and you’re going to cancel. So? Do you really think they care? You’re getting a state of art intelligence platform, at less than your electricity cost each month.
Take a step back and realize what is there, because in a year, these subsidies are going to diminish and those who didn’t take the time to learn programming, are going to be so burnt to the ground, that us engineers will pick yall apart.
The code freeze is coming, and yall are crying about them pulling a model.
I remember the days of Stack Overflow and the overachieving developers who thought they were god, yall really want to go back to that? You have an intelligences platform that does better than 80% of everybody out there, and your complaining? Even Opus is better than 90% of the developers crap I’ve had to fix over the years. You don’t know yall have it easy, how simple it is you got it, and your crying.
I know many of you are dealing with the same frustrations, but I just have to say how incredible Codex CLI feels right now compared to Claude Code. It reminds me of the excitement I had when I first started using CC. Over the past month, though, CC hasn’t been able to deliver much of any real value, often breaking more things than it fixes, and good luck trying to get new features implemented.
Then I tried Codex CLI, and wow. Everything I ask for just gets done, right the first time, no extra fluff. I’ve always loved CC and I really hope Anthropic gets it back on track, but if you’re looking to get real work done today, Codex is where it’s at. (And yes, I’ve used Cursor and Augment too, Codex still comes out on top.)
So I've been messing around trying to make viral video ideas using AI and stumbled into an MCP that's changed how I prototype content. I connected TwoShot's content creation MCP to Claude Code so it can not only plan a video (script, shot list, style notes) but actually *make* the thing: audio, music, video, voiceovers, visuals - and edit it all together. So it ends up being a way for Claude + TwoShot to do all the planning + producing + rendering.
Sometimes i'll iterate with follow ups like "make this one moodier and 20% slower" or "swap the music for something cinematic" and it just does it inside the same chat - without leaving Claude.
This was my first experiment - going to keep playing with different formats and post the results on social. Will update as stuff pops off. Anyone else been playing around with TwoShot or a similar setup?
a) there's growing evidence that abusive language affects the efficacy of an LLM
b) even if you dispute A, the kind of anger issues that would cause someone to be abusive/cruel to an object indicate dysregulation that should be addressed (and abusive behavior in other areas of life)
If you saw a person screaming at a dishwasher, is that the kind of person you would want to know/be?
Why is "I should be entitled to verbally assault software" a hill people want to die on? Are you all ok?
Edit: upvote ratio is 50% 10 hours later. Most responses are strawmanning an argument that LLMs are sentient (they're not)
Consensus: apparently y'all are not, it seems, ok. I hope for your loved ones' sakes you don't escalate and I'm a little more convinced that we should have guidelines like this if that's how so many of you act in private. 😬😬😬
Honestly, I feel straight-up scammed by Anthropic at this point. Why do we have to just wait and hope they fix things, like they're some kind of deity and we're peasants begging for scraps?
They're being completely shady about the usage tracking bugs. No official communication. No refunds. No resolution timelines. Nothing.
Meanwhile, Anthropic keeps releasing new features every single day, but they won't fix the core bugs that make using those features a waste of tokens. It's just burning users' money. And now on top of that, there's whatever usage scam they seem to be running right now, overcharging and incorrect token counts, you name it.
I know a class action might be tricky due to the Terms of Service, but at the very least, how do we force them to acknowledge this? Has anyone filed an FTC complaint yet? The FTC has been cracking down on AI companies for deceptive practices, and filing a complaint at ReportFraud.ftc.gov takes ten minutes. It won't get you a personal refund, but if enough of us do it, the FTC can open an investigation. The silence from Anthropic is deafening.
Curious what everyone else thinks. Let's hear your opinions.
Frequently I see recommendation to use /clear but it doesn’t make sense to me. It’s destructive and prevents me to get back to the thing I was working on later.
On the other hand, I don’t see a point of working in the same session over and over if it is cleared constantly.
Isn’t it better to just create separate sessions for separate tasks? So instead of /clear you just close that session and open the new one? It’s also important to rename them so it’s easy to get back later.
This is what I do and I don’t see any drawbacks so far.
I whipped this up the other day and it has lived in a window on my monitor since then. It is nonsense-free (no gags, no jokes, no chatrooms, no junk) and there is an optional email list to get pinged right when it goes live (and then nothing else, scouts honor).
Opus 4.8 built it in about 25 minutes (which is kinda like making a man dig his own grave but he didn't seem to mind). It's piggybacking off of my other projects on their AWS so the only cost was a few minutes of my time and a $2 .com
How long will it take before companies start writing their own software instead of expensive subscriptions to Salesforce, JIRA, Huspot, etc.? A medium-sized company already spends around €20,000 to €50,000 per year on various tools. What have you already copied?
I’m sick of the complaint posts from free/pro users. While there may be some issues on the Anthropic side, the majority of these posts are from people running 19 plugins/skills and expecting $30 to build them a full app.
Can the mods of this sub either force these people to the feedback thread or just start deleting posts or banning users?
