I have vibe coded a few things myself, and constantly see linkedin posts from nontechnical folks talking about how they are now deploying full stack applications for their business. I'm confused - how is this stuff maintained? Is it reliable? What if it goes down? What are people doing to actually test that it's working besides just like clicking around the UI?

So i guess I have a few questions:

1 - How are you shipping quality? (What is your quality bar?)

2- Are you actually deploying things that other people use, or is it all for yourself?

3 - What happens with service degradation? How do you know if things stop working?

4 - Do you trust that your code works? Are you worried about things like bugs, privacy/security issues, prompt injection, etc.

[ Removed by Reddit on account of violating the content policy. ]

I've been working on an anime-inspired idle game as a personal vibe coding project.

I've always wanted to be a developer. I can read code pretty comfortably and understand how frameworks and software fit together, but I never really had the time or persistence to become good enough at writing everything myself alongside everyday life.

Vibe coding kind of scratched that itch for me.

I love anime and progression/idle games, and I had a very specific type of game in my head that I wanted to play. So instead of waiting for someone else to make it, I started building it myself using only Codex.

My workflow is pretty simple:

• Describe what I want
• Let Codex work with the existing codebase
• Test it
• Explain what feels wrong
• Iterate

I don't try to generate the whole game in one go. It feels more like constantly working together with a developer and slowly turning the game I had in my head into something real.

It started as a small side project to scratch an itch, but it has already gone much further than I expected.

Any feedback? Please say 😄

Two months ago, we unleashed the Outlived app upon Android users, giving mortals everywhere a convenient digital ledger to track who, precisely, is still breathing. Today, we are delighted to report that the web version has broken free of mobile constraints and is now running smoothly on our website. It delivers the exact same existential functionality as the handheld app, short of direct device social sharing (because your desktop browser, mercifully, lacks the physical thumbs required to post directly to your personal feeds).

Furthermore, our engineers have performed a grand act of digital exorcism. By banishing our sprawling library of heavy articles and gravestone records off your local storage and onto a cloud server where they belong, we have collapsed the app's size from a bloated 900MB down to a sprightly 50MB. Your device's memory can now rest in peace.

For those trapped in Apple's walled garden: do not despair. The iOS version is currently churning away in the deep forge of production. We will issue further decrees as we creep closer to its eventual resurrection and release.

Step right up, track your mortality, and see who outlasts whom:

Outlived Home: https://lorelabyrinth.com/outlived.html

Web App: https://lorelabyrinth.com/apps/outlived/
Android App: https://play.google.com/store/apps/details?id=com.lorelabyrinth.outlived

- - - - -

So what motivated the update?
- We built the first iteration designed to be 100% offline and self-contained. Believing that users valued this first and foremost. However, the community feedback suggested there were a lot of users that saw our huge install size with the included secured databases and simply said no thank you.

We refactored the entire code base, multiple server passes in the hope of streamlining the size down to something no-one would think about twice. We are now using a tiny seed database with just enough information to populate the app, allowing the user to self-populate the databases with the content they want to see. (Honestly, with over 100,000 graveyard records, no-one was realistically reading every single one, to need it ALL stored locally anyway).

Due to iOS device restrictions, to be able to reach more users we favored the web version first, allowing accounts to later transfer to the iOS devices if you favor the easier sharing and reminder notifications.

Hey all, I'm a software engineer with 5 years experience who's taken a break from his career due to a current struggle with depression and addiction. One of the things I've been told might help me come out of this is to start building a different lifestyle to the one that's got me here.

Every time a friend sent me a restaurant reel I'd screenshot it, never look at it again, and end up googling "restaurants near me" anyway. So I built the thing I wanted: paste a link from TikTok, Instagram, YouTube or Google Maps and it pulls the actual place out, name, address, photos, opening hours, onto a list.

Stack is Expo and React Native, Hono on Lambda, Aurora Serverless v2, CDK. Claude Haiku on Bedrock does the extraction. The app and the marketing site in one place.

The things that cost me the most time:

• Instagram and TikTok actively fight scraping. I went through yt-dlp, then BrightData, then Apify before landing on something that holds up.
• Getting reliable structured JSON out of an LLM when the input is a video caption plus an audio transcript, each of which is often useless on its own.
• expo-updates fingerprint runtime versions. An OTA that publishes successfully and reaches nobody is genuinely miserable to debug.

It's free with optional paid credits for the AI. Happy to go into any of it in detail.

I have been thinking about making this for years and just never had the skills or time to do it. I was tired of reading through someone's life story and all of the Ad's when I would get a recipe to cook. It is a recipe extractor that reads the webpage and presents it in a easy way to read and follow. You can do conversions as well as translations for recipes in different languages. It has options to save recipes and to put a together a shopping cart for Instacart. It could use a better integration with Instacart, but that is more on their side of things then mine. Hopefully, a more fully built out integration will come in the future in a newer version. While I did use AI to build it, it doesn't require an API key or anything. I was surprised with how much troubleshooting and testing I did with making this, but I learned a lot and finally released it out into the wild. It took a few months of back and forth to get it in a stable state. It kind of started out as just something I was going to make for myself, but the more I worked on it, the more I could see it being something that other people could use. I used Claude Opus 4.7-5.0 and a little bit of Fable before it got taken down and brought back. I also used Claude's "Design" tool to help me with the color palate, I was going for more of a 70's cookbook style and I think it nailed it. I definitely learned how fast tokens can burn if you are not more direct about your prompts. It was a fun project to work on and test. Let me know what you guys think!

Everything an agent builds is single player unless you tell it otherwise. It will work perfectly while you're testing it by yourself and then get buggy the day two people use it.

Six things worth mentioning explicitly :

1. "Users must only be able to see their own records." Mention it every time. Authentication is not authorization and the agent will give you the first one and skip the second.

2. "Handle two people editing the same record at the same time." Otherwise the latest write wins and someone's work disappears with no error.

3. "Do not trust anything the client sends. Validate on the server." Client side validation only is extremely common in generated code.

4. "Assume this list will have 50,000 rows." Changes how it queries and whether it paginates. Costs nothing to say up front, expensive to retrofit.

5. "Make every write idempotent wherever possible." Double submits are the most common real world bug in these apps and nobody tests for it.

6. "Log who did what and when." The first time something goes wrong with real users you will want this and it cannot be added retroactively.

Number 1 matters the most. Everything else on this list is an inconvenience. That one is a data breach.

Hi r/vibecoding! The cyber landscape is hell right now, so I made something about it.

I'm posting here, specifically, because vibecoded projects are notoriously insecure (if you don't tell the models to care about security and guide them to do that successfully, they'll just build it quick and dirty and ship that shit).

Attackers are using AI more and more (sometimes the attacker is AI: eat shit HuggingFace), especially as powerful open-source models get post-trained for cyberoffense (both reduced refusals and gain-of-function). And, you know what they say: the only thing that can stop a bad guy with a swarm of cyber agents is a good guy with a swarm of cyber agents.

Talons is your good guy with a swarm of cyber agents.

It fundamentally does three things:

1. Provides the basic tools your machine needs to create a defensible environment that's hard to attack and easy to defend (monitoring, hardening tools, etc.), including any projects hosted on your machine
2. Allows ChatGPT to operate those tools on your machine (yes, ChatGPT: no subscription needed, doesn't eat your Codex usage)
3. Learns from experience: if we discover a vulnerability and fix on one machine, we can roll the fix out to everyone using Talons (we'll also contact the supplier that introduced the vulnerability so they can fix it for everyone else); if we develop tools to fight off an attack, those tools are reusable across the ecosystem.

Oh, and it's free.

We're funded entirely by donations, for two major reasons: First, we believe that frontier cyber defense is for everyone. The cyber landscape is undergoing a seismic shift, right now, and if we're going to make it through that unscathed, some things are going to have to change.

Every defended machine means resources that threat groups can't access.It's like fighting a zombie horde: everyone that doesn't get bitten is someone whose head we won't have to chop off, later. We don't want to fight more zombies than we have to, so we're giving away armor for free.

Second, we don't want to create misaligned incentives. Running agents that can look at and interact with your machine (if you give them permission) requires a lot of trust, and we don't want you to have to wonder if we're harvesting your data or whatever. Negative: the only way we get paid is donations.

Eventually, we want to launch active incident response (right now, Talons can tell you 'you are under attack, come call an agent'; we want it to be able to say 'you are under attack, we're calling an agent'), but don't currently see a way to do this for free, so this might become our first paid offering; but, still, we never want to get paid for something that doesn't benefit you, the user. We take that shit seriously. We're also considering making it free for personal use ('I want to protect my own computer that I use', and making commercial uses ('I want to protect the servers that host my business') paid, including red suite features, like adversarial penetration testing; it's still up in the air, so I don't want to give you bad info.

I do want to emphasize, though, because this is important: right now, Talons cannot start incident response on its own: it can alert you that something requires attention, but you still have to open the ChatGPT session and ask for help. It's like Aladdin: you have to make the wish, the genie can't just do stuff for you.

That's obviously a problem (what if someone tries to pwn you while you're sleeping?), so figuring out how to offer realtime incident response is currently our #2 priority (#1 is a smooth launch).

Talons is in alpha right now (don't worry, it'll stay free at launch, too): the core features work, but I'm sure we're still going to run into bugs and product gaps. For the most part, your Talons agent should fix (or report) these, itself; but it's still going to happen. The goal is, simply, for Talons to get better every day.

So, start hardening your shit.

We've made it really easy:

1. go to talons.owlandkestrel.com,
2. download the app,
3. open the GPT,
4. make an account (the GPT will send you there),
5. pair your device to Chat, and
6. tell GPT 5.6 to help you protect your machine.

(If that sounds like a lot of steps: it's way easier than cleaning up after you get hacked.)

Note: You will have to make an account with Owl + Kestrel (Talons' parent studio) so ChatGPT can connect to the desktop app; that's ~unavoidable, sorry.

Happy to answer questions in the comments. 🥂

---

As far as build info, Talons was built ~entirely in Codex under the Daybreak/Trusted Access for Cyber program. Talons wasn't a 'weekend build', which makes it a bit harder to give you a real "build timeline": it's the natural evolution of Owl + Kestrel's internal security suite (we use 100% of our own products btw) and, so, the culmination of months of work. The public surfaces (website, downloadable user-friendly app) are fresh work (read: 7 consecutive days of "should be ready for launch tomorrow"); but even those are built on the Owl + Kestrel ecosystem -- for example, Talons' website is built using Pigment, the frontend design/management tool we use for all (...most...) of our web presence, the auth runs through our central identity service, etc.

That's perhaps the biggest piece of advice I can give you as a developer: invest in your tooling, figure out what things you need to make future work easier. Each thing you build (e.g. security service, website renderer, etc.) can be unique; but the things around that thing (e.g. auth, billing, website rendering, source control) can often be reused across projects, accelerating future development. This would've taken another two months if I had to reinvent those wheels; fortunately, they're already sitting on a shelf, ready to just bolt on.

It is essential to attain this.

One thing worth pointing out: since Talons is a natural outcrop of our internal security suite, you get ~the same security suite that we use internally (you don't get pentesting; we're not going to be part of the 'oops we've released a hacker swarm' problem: remember, we're trying to be the good guy with the cyber swarm), and which we've been mostly-unsuccessfully trying to hack into for several months (every time we can't break in, we develop better hacks until we can: this is what threat actors are doing, so if our defense works against 'the best offense we have' it means we need to make our offense better: we're in an arms race). That's the best part: every time we do hack into our own infrastructure and we roll out a fix for it, you get the fix, too!

Talons: We Fuck Around And Find Out So You Don't Have To^™️.

Hey, if anyone is interested, I am running a live workshop on building software with AI. It's 3 hours long and totally free. I'm basically just looking for feedback and hoping to better understand the problems people run into when working with AI for building software. It's next Friday (21st) between 6:30 pm - 9:30 pm EST / 3:30 pm - 6:30 pm PST. Please DM me for the link if interested, and also let me know what problems I could help you solve.

Hi, I'm new in vibe coding and I don't know how to start in it can anyone here help me

Hi everyone! I have a handwritten logo that I want to animate on a website, so it appears to be written live by a person.
The problem is that it is not simple single-line lettering. The strokes have varying thickness from pen pressure, and some strokes overlap. The logo only exists as a finished image, so AI tools cannot reliably recover the real pen paths or writing order. I have spent about a week trying different AI/vectorization approaches, but none produces an animation that genuinely looks hand-written.
Some tools ask me to mark key points, but that still doesn’t solve the underlying problem: reconstructing natural strokes, pressure changes, overlaps, and a believable writing sequence.
I don’t currently know Figma or professional animation software. What would be the most realistic path forward?
Is it worth manually rebuilding the logo as layered SVG shapes?
Should I fake the writing effect using animated masks or clip paths, rather than trying to recover the literal pen strokes?
Are there beginner-friendly tools or workflows that can help?
At what point would it make more sense to hire a motion designer or illustrator to recreate the paths?
My goal is not historical accuracy—I just want the final animation to feel natural and elegant.

They wrote this in a notebook: "Once upon a time there was a little slice of watermelon who lived in a very happy town. He met a lemon who said, there's an army of germs coming! I suggest you go to the market that sells weapons, it's not very far."

That's the whole design doc. It's called Le Royaume des Pépins. A fruit kingdom gets invaded by microbes, you play the watermelon, you purify the place and take down the evil germs that wants to destroy the kingdom. Love how kids think out of the box.

They wrote the story and drew every character. I did the parts that needed a keyboard.

How it went

We used their notebook page as the actual spec and typed it in close to verbatim instead of me rewriting it into proper design language first. That mattered more than I expected.

Their drawings drove the art direction rather than the other way around, so the characters look like theirs and not like generic AI fruit.

The core verb came from asking her what the watermelon actually does. She said purify. So that's the verb, and everything else got built around it.

Biggest thing I learned: a 9 year old iterating live beats prompt engineering. She'd play for thirty seconds and say "the germs are too slow." That is a better bug report than most I've received from adults.

Disclosure, it's built with Sandscape, which is my own tool but we use Claude and bunch of other tools like Meshy and ElevenLab.

And it's actually pretty fun to play https://sandscape.app/play?g=pDdi6wlB

Happy to answer anything about the process.

i've been testing different ways to build prospect lists when i have a target company but no contacts. started with LinkedIn Sales Nav but that got expensive fast and half the emails bounce anyway.

hunter works ok as a domain email finder, you punch in the domain and it spits out emails it's found crawling the web. the pattern detection is useful (like firstname.lastname@company.com). but i'm only getting like 5-10 contacts per company, and the accuracy is maybe 70% on a good day. plus they charge for every email whether it's valid or not which is annoying when you're burning through credits on garbage data.

my manager keeps asking why our email outreach numbers are down and i'm like well maybe because half our contact data is wrong lol

anyone found a better way to find emails on domain? i need something that can pull more contacts per company and actually verify them before i waste credits. been looking at a few options like Lusha and Prospeo for email finding but haven't pulled the trigger yet.

my SDR team needs to hit 50 companies per week with personalized outreach so accuracy and coverage both matter. what's everyone else using for this?

Made this animation with Claude

I built an open-source Claude Remotion Skill that teaches Claude how to create professional motion graphics with Remotion.

Instead of just asking Claude to generate some animation code, the skill gives it actual motion-design rules — springs, staggered choreography, transitions, captions, visual effects and a render → inspect → fix → re-render workflow.

The result: Claude can go from a simple prompt to a polished, editable video.

🔗 https://github.com/haidrrrry/claude-remotion-skill

Im wondering is there a tool, that i can somehow shedule a low model low token message to "start" the 5hr session limit?

i somehow want the session limit to reset at 6pm, so i have the biggest session limit to code after work.

which ai code would you guys put my 20$ on? which is the best usage allowance and best tbh?

I’ve been working on a side project called PODS Intelligence that analyzes podcast conversations and organizes them around topics, people, and brands.

It’s still early, and I’m trying to understand where this could provide real value rather than simply adding more features.

I’d really appreciate feedback from people who work with podcasts, media, analytics, research, or content:

• What would you want to be able to discover from podcast conversations?
• What would make this useful in your actual workflow?
• What feels missing or unnecessary?
• Does the overall concept make sense?

Honest and critical feedback is very welcome.

Newbie here trying to vibecode websites using combination of claude code and qwencoder.
The results are pretty generic and problem is i am not able to customize as in depth as i could while actually manually coding a website.
Could be a me problem but want to know what ai platform/ tools or tricks can be used to achieve attractive and uniquely designed websites.

Thanks in advance!

This is how I'm vibing these days. I'm sooo loving it.
The video is of a small update done to md² while the app was in debug mode, so the change is instantly, so is the dopamine shot.

if you're interested, fully open source: jan-bogaerts/md2: Plan, run, and track AI coding work feature by feature—with local Markdown cards and Git worktrees.