A few people asked after launch how this actually got built, so here's the real picture.
7 months, solo, zero coding background before I started. Backend runs on Cloudflare Workers with automated AI evals and vector-based memory search. Live on 4 platforms: iOS, iPad, Mac, web.
Around 32,000 automated tests across the stack before anything ships. I write the scenario spec, what it's testing and why it matters. AI generates the test case and a gold reference reply from that spec. Nothing ships unreviewed.
Happy to answer anything about the process, the stack, or vibe coding in general.
Genuinely asking, not trying to dunk on anyone building fast. when the AI generated codebase behind a launch needs a real feature added six months in, or a security fix under pressure, what usually happens. is maintainability something builders are thinking about early, or is the priority almost entirely getting to launch day and figuring the rest out later
there's a version of this where it's totally fine, the product gets traction and someone eventually brings in a real engineer to clean things up. and there's a version where the technical debt is deep enough that it needs a full rebuild anyway. curious where people think most vibe coded products actually land on that spectrum
Hello everyone, Sumit here from the Himalayas. I hope everyone is having a relaxed weekend. My workflow with vibe coding has settled pretty well as I get more and more time out of desk while Claude Code builds the software. I wanted to offer any assistance to fellow founders. I have been vibe coding full-time for a little over 4 weeks. Wrote about it here. Please share your tools, or workflow and in particular what is not working for you. What is frustrating you in building software with vibe coding?
disclaimer: I'm not an engineer. i do growth and marketing.
when people talk about vibe coding they usually mean shipping a product. an app, a saas, a tool with real users. that's the version that gets posted. but it's not where things actually changed for me.
Every time I vibe code there is always this huge lift that I constantly have to go through. Authentication, billing, password resets, emails, signup, waitlist, landing page and when it s all said done and the app is ready then comes the marketing, the blogging, the social media automation, the product hunt launch etc etc etc . So much repetitive crap that I have to do just to get a simple app up and running. How do you guys handle all this?
Since I am a coder and a hammer sees everything as a nail, I decided to create all this code as a template so I can jump into building an app right away. There is actually a lot more than what I mentioned above e.g customer support, chat, roadmap for building in public, email flows and more coming.
First off, I am a history major, so I don't really have any knowledge or background in LLMs or what you guys call an AI Agent. But I have always been interested in the field and have lots of free time this summer.
I am, though, very good at using AI chatbots, like chatgpt, or Gemini, becasue I relied on them a lot while writing papers. This time, I wanted to use them for programming instead. I wasn't sure which AI coding tool to use for someone like me, so I simply picked a random one. Now, jumping to my question(please check the image I attached below):
I ve been tracking my own workflow lately while chatting around with ChatGPT and Gemini, and I noticed a painful pattern: I had the whole picture in my mind, but I constantly forget some edge cases or tiny technical constraints on my first try.
I hit send, wait 30 seconds, realise the AI guessed wrong, tweak it, and retry. It s an absolute token-waster and a massive productivity killer.
I'm trying to prototype a lightweight extension to intercept these "blind spots" in real-time right inside the input box before hitting send. But I'm curious about how you lot deal with this:
Been building Consile almost entirely with Lovable, and the thing I've found matters most isn't the AI generating code fast, it's having a real, repeatable process for verifying what it generates before it ships. Things like actually reproducing security findings against live endpoints instead of trusting a policy read, or independently confirming a claimed fix rather than taking "done" at face value.
Curious what others here have landed on. Do you have an actual verification process, or is it more ad hoc? What's caught you off guard that a quick glance wouldn't have?
