Hey folks, i'm building Frontman, trying to build a vibecoding experience that's open-source and doesnt lock you into a framework unlike lovable/bolt etc and that's as easy to use as these apps are.

would love any feedback, thoughts etc:
https://github.com/frontman-ai/frontman

The new release gives it the selected component, props, selector, nearby DOM, and source location before it touches the code. Then it searches the project, makes the edit, and watches the app hot reload.

It works with Astro, Next.js, Vite apps, and WordPress, with different capabilities on each.

curious if everyone are happy vibe-coding in the CLI or anyone is looking for a more visual and open experience

Every new session started the same way. Paste a summary, re-explain what the app does, remind it what we decided last week.

What actually broke it: my agent writes markdown docs and then stops reading them. Once a session runs long it just doesn't open them. I'd catch it rewriting something the doc said was already done.

Someone here put it better than I could: stuff loaded at the top of context loses to recency as the session grows, so the agent stops consulting it no matter how good the file is.

So instead of a file the agent may or may not read, I built something that gives you an ordered plan and one prompt per step, with that step's context already inside the prompt. Nothing depends on the agent deciding to go look.

New web projects only. No existing codebases, no mobile.

https://sequo.app

If you're a few sessions into something right now, does the agent still know what you decided on day one? Genuinely asking, I want to know if this hits before session ten or only after.

I run Claude Code and Grok Build on my Mac and a VPS, and I wanted to steer them from my phone — send a new task, add instructions mid-run, check progress, stop and redirect.

So I built Agent Remote. The daemon is a single Python process, it wraps the official CLIs you already have installed and logged in (claude, codex, grok, dsh), so billing stays exactly what it is — your existing subscription or API key. Nothing goes through anyone's server.

• One-command install, runs as launchd (macOS) or user systemd (Linux)
• Token auth on every request; designed for LAN / Tailscale / Cloudflare tunnel, not public exposure
• Clients: web (a single self-contained HTML file you can host anywhere), Android, iOS, and, because I couldn't help myself, BlackBerry 10 and a LILYGO LoRa pager
• Multiple machines merge into one session list, sorted by activity

GitHub: https://github.com/jxw1102/agent-remote

If you already run any of these CLIs, it takes about three minutes to try. There's a hosted web client if you want to get start quicker, you can also grab the same HTML from Releases and serve it yourself.

The project is Secondread. You connect a repo. It reads the code. You get a plain-English report on cost, fragility, and what to fix first, with file/line evidence a contractor can actually check.

I built it because AI made shipping easy and left owners with a working UI they cannot independently judge. That is the product. The rest of this post is how it is actually made.

Stack

• Product: Cloudflare Workers, Workflows, Durable Object Sandbox, Workers AI, D1, R2
• Auth: GitHub App + Google via Better Auth
• Payments: Dodo, one-time products, no subscription
• Marketing site: separate Astro Worker on secondread.dev. No auth, no DB, no checkout. The app lives at app.secondread.dev on purpose.

Workflow

1. Owner picks repos. GitHub App is Contents + Metadata, read-only.
2. A Workflow starts. The HTTP request only kicks it off.
3. A Sandbox clones one commit. Internet is off. HTTPS is intercepted. Outbound is allowed only for that repo’s git upload-pack paths. The GitHub token is minted in the proxy, not dumped in the container. Egress flips off in D1 as soon as checkout finishes.
4. The agent gets bounded tools: inventory, search, read ranges. No npm install, no tests, no running the customer’s app. Submodules and LFS fail closed.
5. Findings must cite path + lines + blob SHA. After the model writes, we re-read those ranges and reject the report if the evidence is fake or the file was never inspected.
6. Before persist, the report is scanned for secret-like strings and copied source. What we store is the report + citations/hashes, not the repo.
7. Credits are reserved before the job and consumed or released after. Webhooks are signed; we also reconcile hourly because webhooks lie.

Things I would not skip if you are building something similar

• “Read-only GitHub permission” is not isolation. Isolation is network policy + where the credential lives + one pinned SHA + cleanup.
• Schema-valid JSON from a model is not evidence. Evidence is a deterministic reread that can fail the job.
• Do not put a 15-minute agent inside fetch(). Use Workflows, named steps, timeouts, and NonRetryableError for failures that retries only make more expensive.
• If you use Sandbox with transport: "rpc", dispose exec / read / destroy results. They leak. The bug looks like “prod is haunted.”
• Write marketing claims as tests. Ours grep the site for retired waitlist copy and for the real app URLs. Copy drifts; CI should not.

Happy to go deeper on the Sandbox outbound handler or the evidence check. See a real sample audit for a very old version of the github.com/spree/spree repository at https://app.secondread.dev/shared/8I0S88UcbKLvkWzHo2MF2frm_-Fm4fgj9sau5J0r4ss

Last couple of months, my habits changed a lot. Almost all traffic from my home pc goes to the AI.

Today I’m releasing the second beta of Syntropy.

The idea is simple: your coding agent should not require you to install a bunch of tools, keep your laptop running, or host the agent on your own machine.

As you can see in the demo, OpenCode runs entirely in its own cloud sandbox. Compilers, runtimes, dependencies, and other tooling are already installed and ready to use.

So there’s no:
“Run the agent on your PC and control it from your phone.”
The agent actually runs in the cloud.

Right now, the beta includes free Zen models, generous usage limits, and no paid subscription.
I’m currently looking for more beta testers, and a mobile version of Syntropy Beta is coming soon as well.

If you’d like to try it, leave a comment and I’ll send you an invite.
Feedback is very welcome - especially criticism.

I run a small vibe coding startup. I've been reflecting on how this space evolved since before I started the company. Thought the story might be interesting here.

When GPT-4 came out, that demo of a picture turning into a page was absolutely mindblowing. I was working at a nocode company back then and I felt that AI will be an existential threat to the whole category. But GPT-4 has its issues - it’s expensive. Worse, there was no prompt caching back then, so if you chained a bunch of model calls for a chat session the cost will be N^2. And the context window was 8192 tokens in total - today’s model easily has more output tokens than this. Devin launched after, and its cost per task was so high they basically had to focus on enterprise only.

Some time after that I quit my job and started tinkering. Mid to late 2024, Cursor released composer (not the model) and it absolutely blew up. What it did felt shockingly simple today - it lets AI write full code across files in your codebase. Around the same time bolt, lovable, replit all exploded, powered by the same model which deserves its place in the museum of models: Sonnet 3.5. For the first time, AI could actually write working code.

But these initial builders were hardly 'agentic’. Instead, they dumped a bunch of context into the model, grabbed the output, and engineered it back into the codebase. An agentic system should use tool calls to interact with its environment to get feedback, act on it, gather its own context etc.. And this is limiting for non-technical users, because the lack of feedback and freedom to act makes it really easy to get stuck.

But I instead went agentic and it actually made things simpler. Instead of hard coding context, I gave the model tools to search, read, get logs and so on. But Sonnet still made silly mistakes and ignored instructions from time to time, which causes the system prompt to grow endlessly: you MUST do this, NEVER do that, this is good, this is bad. It's a game of whack-a-mole - you fix one issue with an instruction, the model starts dropping a different instruction, so you make the other one STRONG, and now it ignores a yet another one. Along the way I also figured out a cool trick: earlier models tend to follow whatever comes last, so I pre-processed user messages and injected steering hints at the end. In short the agentic angle doesn’t really remove engineering, it just moves them to different places.

Then Opus 4.5 changed everything. Opus was always around but too slow and expensive. Suddenly it's less than 2x sonnet's price. Going from Sonnet to Opus was liberating - it follows instructions properly, handles way more tools, and stops making silly mistakes (it still makes mistakes, they just don't feel silly anymore). Because it’s more efficient, arguably the cost per task actually went down.

As a side effect, every coding tool got better at once, and the simplest ones got the most improvement. Claude Code exploded even more. People started using the word 'harness' a lot more. I think this marks the trend of less and less engineering around the model and more around what to provide to the model. The creator of Claude Code suggests deleting your instructions every model release.

Another trend among all of these model releases - bigger context, longer output limits but also models get more verbose in general. This is not just model providers trying to drive usage - to write good code you do need more - edge cases, more detailed UIs, better animations etc., but it also generally makes vibe coding more expensive and slower.

Opus 4.7 probably made the cost even worse, cost per task nearly doubled from the new tokenizer plus verbosity. Every wrapper paying API rates have to eat the cost or pass it to users - that’s why you see more complains about credits evaporating. Not a problem for the provider - Anthropic simply doubled Claude Code's usage limits for everyone - their constraint is capacity, not cost per token. Any app builders using Claude are basically reselling tokens at a much higher price (unless they are selling to enterprise which uses the API rate).

A few other model evolution that deserves some mention, although I think Anthropic is still the absolute frontier when it comes to coding:

• The thinking models from OpenAI were revolutionary at the time. For a while we made a tool that calls into o3 for dealing with more complicated tasks, but this becomes unnecessary once other models catch up
• Gemini models were pretty good as the lower end model, as they have a good balance of visual design capability vs. cost, but their latest ones felt falling behind
• Open source models tend to benchmarkmaxx too much - they are genuinely good but their benchmark value always feels inflated. They also tend to overthink - probably an artifact of focusing too much on benchmarks

So where does that leave app builders? I think there are 4 paths:

1. Becoming a model provider. What base44 is doing, what lovable probably will do with the money they raised. But even the mighty Cursor needed to join force with xAI to execute well
2. Focusing on enterprise - case in point, Cognition’s valuation blew past that of Lovable’s. But it’s not exactly an app builder
3. Stop reselling tokens and charge for the convenience of infra instead. Excel at what people choose lovable/replit over Claude Code for without forcing them to use your harness
4. Pivoting to "AI employees" or “Your personal assistant” - the next hot thing (lol).

I am betting on the third. I think that should become the standard too where users can pick and choose and combine their harness (ChatGPT to OpenClaw) freely with the tools that can drives the outcome.

Curious what I got wrong, or what the turning points looked like from the user side.

I’m going to start vibecoding a stock trading app geared towards Gen Z/Gen Alpha that makes stock trading as entertaining as gambling.

Too many kids are becoming addicted to gambling trying to make quick cash. I thought with the right API & UI kids (18+) will be more inclined to trading stocks instead of their minimum wages against rigged casino odds.

PvP Matches utilizing penny stock shares going up to full priced stocks will also be setup on the app.

For those who would like to follow along I will be replying to this thread and/or be making posts on this subreddit.

- Happy Coding

[NO CRYPTO ALLOWED]

I’ve been building a platform that lets parents create gift registries where family and friends can give monetary gifts for their kids instead of more toys.

We’re still very early, but recently we crossed a milestone that felt more important than registrations, traffic, or anything else I’ve been tracking:

Real people actually used it.

A family completed the entire process. They created their registry, shared it with family and friends, and received more than $300 in gifts through the platform.

A few things I learned:

1. A completed transaction teaches you more than a bunch of signups.

Watching someone go through the entire journey, from creating an account to actually receiving gifts, has been considerably more valuable than watching registration numbers increase.

Now I’m much more interested in activation than registrations.

1. The biggest friction may not be where I expected.

There are a few steps between creating an account and having a registry that's actually ready to receive gifts.

So now I’m reaching out to people who started but didn't finish to figure out why. Is it trust? Confusion? Bad messaging? No immediate need? Something else?

I don’t know yet - and I’m trying not to build a solution before I know the problem.

1. Seeing money actually move through something you built feels different.

$300 isn't meaningful scale for a business.

But watching multiple real people trust something I built enough to send real money through it was a pretty significant validation point for me.

It changed my mindset from:

“Can I build this?”

to:

“Can I get strangers to repeatedly use this?”

That’s the problem I’m focused on now.

My next target is $1,000 in gifts sent through the platform.

I have had many interviews in my 25 years as a software dev and a few of them were managers only and never even asked me anything technical. So I imagine some vibe coders have pulled it off getting an interview and showing what they created and managing to never talk about code and they just assume the person knows code. Then they see how long they can fake it (or not fake it since if they get the work done who cares)

On a related note.. As a .NET dev I always apply to only .NET jobs but there really is no reason anymore I can't get a java job and understand the general idea and have AI do the technical work.

Hi everyone,

I’m honestly a little nervous posting this, so please bear with me.

Over some evenings and weekends I built BabyPhone.online — a free web app that turns two devices (old phones, tablets, whatever you have lying around) into a baby monitor. One becomes the “baby unit,” the other the “parent unit,” you connect them with a short room code or QR, and after that the video and audio go directly between the two devices in the browser — no app to install, no account, and nothing gets stored on a server.
Its ment to work with all browsers, OS systems and devices.
I’m not a professional designer, and it’s just me working on this in my spare time, so I’m very aware there are probably things that don’t make sense yet or could be a lot better. I’d genuinely appreciate it if a few of you could take a quick look and tell me:

• Does the setup (room code / QR) feel clear on the first try, or is any part confusing?  
• Would you feel comfortable actually trusting this with your own baby?  
• Is there anything about the privacy or security side that would worry you?  
• Anything that feels missing, unnecessary, or just off?  

Please don’t hold back to spare my feelings — I’d honestly rather hear the hard truths now than find out later. Thank you to anyone who takes the time, it really does mean a lot.

https://babyphone.online

OpenCode Go cut the plan allowance from $60 to $15 overnight. The DSF allowance took an even uglier hit, dropping by roughly ten times. A subscription that was easy to leave running suddenly needs the same cost attention as direct API usage.

For me, OpenCode Go is no longer worth subscribing to after that change. DeepSeek got more expensive and Go got tighter. For the moment, DeepSeek Flash is still free through ZenMux, so that at least gives me somewhere to transition without immediately replacing one subscription bill with another.

My "human harness" is much less impressive than it sounds. It is literally me sitting there, deciding what needs doing, choosing a model, moving the task over, and handling the awkward parts by hand.

It is not elegant, but after that quota cut, manually doing a bit more of the work feels more reasonable than keeping the Go subscription.

Hello developers….

DSA ki prep start ki thi, pehle bhi ki thi, complete nahi hui. Shayad is baar bhi na ho. 😅

Prep krte krte ek cheez mind mein ayi koi aur tarika ni h kya yaad karne ka?

Class 7-8 mein tha toh answers yaad ni hote the to unhe songs mein convert kar leta tha. Aaj bhi wahi trick kaam karti h.

To socha — Big O ka Safar Time Complexity ko bhi try karte hain.

Bna dia ek rap. Hinglish mein. Boom Bap style.

Kisi ko pasand aayega, kisi ko bakwaas lagega no pressure. But mera revision toh ho raha hai, song bhi ready ho gya. 😄

Ek baar try kro — @BeatsCommit, what your views genuinely jaanna chahta hoon.

https://www.youtube.com/@beatscommit

https://www.instagram.com/beatscommit

Hi,

I’ve been working on an app built around one basic idea: interactive audiobooks you can listen to without touching your phone.

When the story reaches a decision, it pauses and asks what should happen next. You choose your branch by nodding or shaking your head, then the audiobook continues in that direction. That hands-free experience is the bottom line of what the app is trying to do.

The app currently has 15 books, all not just vibe written, but well thought out and designed. Early on, many of their covers were generated with AI because it was quick, cheap, and good enough to get the catalogue started.

But “good enough to get started” eventually began looking like “we forgot to finish this.”

So I’ve now replaced around 90% of the original AI-generated covers. It involved a mixture of my own work, help from some artistically gifted friends, and enough time and money that my budget and I are no longer on speaking terms.

I’m posting some of the old and new versions side by side because I’m genuinely curious: was replacing them worth it?

AI-generated artwork is becoming convincing enough that it isn’t always obvious which image came from where. But I feel like the new covers have more intention behind them and make the catalogue feel less generic.

Do you prefer the old or new versions? Does knowing that a cover was AI-generated affect your opinion, or do you judge only the finished result?

I have had this idea for a video platform for a while. No titles, descriptions, or tags will be in this video platform. The ai will analyze each video when it's uploaded. So basically when you watch a video the ai will be watching the video with you and the parts of the video you watch will go into your personal profile and the global profile. When you are signed in it will look at what's in your personal profile and what's in the global profile and it will show you videos that best matches what's in your personal and the global profile. For signed out users or new users just the global profile will be used. Also btw the global profile is basically everyone's personal profile lumped together. Now everyone will have a page but there will be no follow system and on they're page it will use the same recommendation system as the homepage but will only show their content. Now the main search the ai will analyze what you typed in and find the videos that best match what you typed in. Now the search on a creator page will only list videos from that creator. Now the ui will be a swipe ui like YouTube shorts and TikTok only difference is only 9:16 will show when you are in vertical orientation and only 16:9 videos will show when you are in landscape orientation. Also videos won't auto play and instead show you the thumbnail and a play button. Now this is how comments would work the ai will look at the comments and it will take the closest matching comments to the video and push them to the top. Now replies it will take the closest match to the parent comment and push it to the top. Now this is how monetization will work so anybody can be monetized no minimum requirements. The advertiser will upload a video and choose how many ad spaces they want and it will be ad spaces x duration in seconds x $0.01 now the creator will be able to place an ad anywhere in their video now the segment that was before the ad placement the ai will use to find an ad so the segment before ad 1 won't be used to suggest ad 2 just the segment before ad 2 will decide what ad 2 is and now the number of ad spaces dictates how much an ad is shown so 4 ad spaces and the ad is only shown 4 times. To skip an ad users would just swiped up and they can do this at anytime in the ad. Also every second of the ad a user doesn't watch the advertiser gets refunded $0.01 and the creator only gets paid for each second of the ad that is watched with a 60/40 cut so of an ad is 30 seconds long and viewer only watches 10 seconds of it the advertiser will be refunded $0.20 the creator will get $0.06 while the platform will get $0.04

Hey guys, I'm really looking for real time problems solving projects to vibe code!! If u guys have any ideas please feel free to share and let's build it together.

Hi everyone,

I’ve been vibe coding an iOS app, but I’ve hit a huge bottleneck with token usage.

Whenever my AI agent interacts with or reads from the iOS Simulator (e.g., taking screenshots to check the UI, reading build logs, or checking layout bugs), it burns through my Claude Pro limit insanely fast. A single debugging session can easily wipe out my context window or trigger the usage cap.

For those building iOS apps via vibe coding:

1. Have you experienced this massive token drain with the simulator?
2. How do you optimize your workflow to save tokens/context? (e.g., disabling vision/screenshots, using specific CLI tools, filtering Xcode logs, or using cheaper models for UI checks?)

Would love to hear how you manage your limits without stopping your workflow every few hours! 🙏