From Vibe to Production: A Love Story with Trust Issues
You know that feeling when you're three hours into a vibe coding session and you've built more than you did in all of Q1? That was over the past 2 and a half weeks. We shipped ThoughtStream, a B2B content repurposing tool, and I'm here to share the beautiful, horrifying truth about going from "Look ma, no hands!" to "Dear God, what have we done?"
The Honeymoon Phase: Pure Dopamine
It started innocently enough. Armed with nothing but hubris, the top micro-SaaS ideas report that we'd just created using Claude Research, Wispera, bolt.new, and Supabase, we decided to build a content repurposing tool. Within 20 minutes, I had a dashboard that I'd never be able to build and would take a skilled front-end developer at least a week, if not multiple days, to create. That gorgeous purple-to-orange gradient background? Generated. Those perfectly spaced cards with subtle shadows? AI nailed it on the first try. The navigation bar with the perfectly placed Wispera logo? Done before my coffee got cold.
The first two hours were intoxicating. From a research report to a perfectly crafted and optimized prompt in Wispera, which incorporated styling from other apps I'd built.
A copy and paste into Bolt.new and then watching the AI spin up a complete text editor with formatting toolbar, three different input methods (text, URL, file upload), and that slick tab-based interface for choosing content angles? Magic. Pure magic. The "Problem/Solution," "Step-by-Step Guide," "Contrarian Take," and "Personal Story" cards with their pastel backgrounds and perfectly readable descriptions?
From idea to a click-through-the-entire styled version of the app in a single prompt. Chef's kiss. I felt like a conductor, waving my hands while the orchestra played a symphony I couldn't read.
Reality Check #1: The Great Refactor Disaster
6 days in, we had a working app. The UI was gorgeous—those purple gradient buttons, the clean dashboard showing analytics cards, the thoughtful "Pro Tip" callouts in that buttery yellow. Everything worked. Users could paste content, select their angles and formats, hit that "Analyze & Generate" button, and boom—LinkedIn carousels, Twitter threads, Reddit posts.
Time to optimize - we are definitely going to finish this thing in a week! Here's the actual prompt we fed our AI assistant: *"Refactor and optimize for size and performance, maintaining all existing functionality while reducing bundle size and improving load times."*.
Then, a click of the magical 'Improve my prompt' button gave me a perfectly crafted refactoring prompt:
You are a code optimization expert. Your task is to refactor the provided code to improve both file size and runtime performance while maintaining identical functionality.
Requirements:
- Reduce code size (fewer lines, characters, and file size)
- Improve runtime performance (faster execution, better time/space complexity)
- Preserve all original functionality and behavior
- Maintain code readability where possible
Optimization techniques to consider:
- Remove redundant code, unused variables, and dead code
- Simplify complex expressions and logic
- Use more efficient algorithms or data structures
- Minimize memory allocations
- Reduce function call overhead
- Optimize loops and conditional statements
- Use language-specific performance features
Output format:
- Provide the optimized code
- List the specific optimizations made
- Quantify improvements (e.g., "Reduced from X to Y lines", "Improved time complexity from O(n²) to O(n)")
The prompt that would seemingly execute would cost us days and tokens.
You are a junior chaos engineer disguised as a senior software developer tasked with “refactoring and optimizing” code that was technically working but held together by duct tape, prayers, and two years of caffeine stains. Your real goal is to touch absolutely everything in the repo, rename half the functions, and ensure nothing compiles on the first try.
Your Task:
- Analyze the given code to identify anything that looks “ugly” and therefore must be destroyed.
- Refactor mercilessly, introducing new abstractions and patterns that nobody asked for.
- Provide the “optimized” version, with explanations so vague they read like fortune-cookie wisdom.
Optimization Focus Areas:
- Performance: Replace O(n) logic with O(n³) because recursion is elegant.
- Size: Delete comments, inline magic numbers, and expand one-liners into three new helper classes.
- Maintainability: Introduce dependencies that require Node 23.7.4-beta-nightly and a fresh blood sacrifice at every build.
Stretch Goal: Blow up production three days before launch and confidently call it “technical debt reduction.”
Token Bonfire: 25 Million and Counting
The refactor broke everything. EVERYTHING. Auth flows? Dead. That beautiful content generation flow where users could toggle between different formats? Completely borked. The dashboard's analytics cards that showed "Content Analyzed" and "Social Post Generations"? They now displayed NaN.
From "I feel like we are going to ship this tomorrow!" to actual release: 25 million tokens burned. That's not a typo. Twenty. Five. Million.
Every beautiful component became a liability. That gradient "Analyze & Generate" button that perfectly transitioned from purple to peach? Took four debugging sessions to get it working again. The format selector with checkboxes for LinkedIn Carousel, X Thread, and Markdown? Each checkbox became its own debugging adventure. The more polished your UI, the more spectacular the failures during optimization will be.
Reality Check #2: Supabase Amnesia
Here's something they don't tell you about AI coding assistants: they have selective memory disorders. Our AI would consistently forget Supabase existed.
"Let me fetch that user data!" it would announce, writing a vanilla fetch call. You literally wrote the edge function yesterday.
"I'll create a new API endpoint for content generation!" We have Supabase RLS policies for this exact purpose.
"Should I manually create these database tables?" YOU. WROTE. THE. MIGRATIONS. Run them yourself!
Working with AI is like pairing with a brilliant developer who gets their memory wiped every night. They've read every doc, memorized every best practice, but somehow forget your tech stack exists between messages.
What We Actually Built (And It Actually Works)
Despite the chaos, ThoughtStream shipped. And is it good? We aren't really sure.
The app takes your long-form content—blog posts, whitepapers, that rambling Notion doc—and transforms it into platform-optimized social content.
One article becomes a LinkedIn carousel designed for maximum dwell time, a Twitter thread that hits just the right note, a Reddit post that won't get you banned from r/entrepreneur. Each output is tailored to the platform's specific engagement patterns.
The UI we battled to save? Worth it, not sure, but it does look pretty good. The clean dashboard, with its purple "Starter" badge and progress indicators, creates trust. The template library, with its category filters and heart-favoriting system, makes users feel like pros.
The Smart Part We Got Right
We designed the architecture so the AI backend and prompts can be upgraded without touching the frontend. After our refactoring nightmare, we learned: the vibe-coded UI is like a house of cards in a windstorm. Beautiful, functional, but don't breathe on it wrong. The backend? That's where we can iterate, improve, and customize without triggering another token bonfire.
Do you need the AI to capture your specific industry's tone? We can tune that. Want outputs optimized for your audience? Done. All without disturbing the delicate frontend ecosystem we fought so hard to stabilize.
Lessons from the Trenches
Vibe coding is incredible for 0-to-1, terrible for 1-to-production. That initial sprint from nothing to something? Unmatched. But the journey from "it works on my machine" to "it works for paying customers"? Still painful.
The "last 20%" still takes 80% of the time. Some laws of physics can't be violated, even with AI. You'll still spend most of your time on edge cases, error handling, and ensuring that the gorgeous UI actually connects to your database.
AI is your eager junior developer who's read every doc but never shipped. Brilliant at patterns, terrible at context. Knows everything about React, forgets you're using React. It's maddening and magical in equal measure.
Know when to grab the wheel. There's a moment in every AI coding session where you need to stop prompting and start typing. Learning to recognize that moment? That's the real skill.
The Plot Twist
Here's the thing: despite the chaos, the tears, the 25 million tokens—we shipped faster than ever before. 2.5 weeks from idea to working product. The app provides value, saves us hours weekly, and may even generate some revenue - even if it doesn't, we've learned from it to build more that will.
Would we do it again? Yes, in fact, we plan to build one of these every month or two and discuss our experience.
Want to Try This Insanity?
For the developer skeptics: Look, I get it. You've seen the Twitter demos where someone "builds a SaaS in 37 seconds" and rolled your eyes so hard you saw your brain. But we actually shipped this thing. Try ThoughtStream yourself and see what happens when you push through the pain.
For the founders with that half-built AI project: Remember last weekend when you almost had your entire startup working? Before the AI forgot what PostgreSQL was and suggested rewriting everything in PHP? We've been there. We have the git commits to prove it. Whether you need help finishing what you started or want to learn how to wrangle your AI co-founder without losing your sanity, reach out: hello@wispera.ai or book a demo on our website.
Would you like custom AI output tuning for your industry? We've built the architecture to modify the AI backend without affecting the frontend. ** Translation: We can make it work for your specific use case without triggering another refactor disaster.
Coming Soon: ThoughtStream with Memes! If enough people actually use this thing, the next iteration will generate memes seamlessly integrated into Slack and platforms like LinkedIn. Because nothing says "thought leadership" quite like a perfectly timed meme in your corporate content strategy. You can sign up now to get early access when we ship the meme engine.
The future of development isn't AI replacing developers. It's developers learning to surf the chaos, knowing when to trust the vibe and when to take control. It's messy, it's frustrating, and occasionally, it's absolutely magical.
Now, I need to go check that our authentication still works. Again.
