The Deployment Reality Check

Here's what no one tells you: Bolt.new makes it stupidly easy to build apps, but deploying them to production is where dreams go to die.

Your app works perfectly in the WebContainer. The AI spun up a beautiful interface, connected to Supabase, added auth flows, everything runs smooth on bolt.host. Then you try to deploy to Netlify or Vercel and suddenly nothing works.

The Classic Build Failure Cycle

Day 1: "Deploy to production" - sounds simple enough.
Day 2: TypeError: fetch failed - ok, probably a URL issue.
Day 3: ECONNREFUSED 127.0.0.1:3000 - wait, localhost doesn't exist in production?
Day 4: Fixed URLs, now getting Access to XMLHttpRequest blocked by CORS policy.
Day 5: Fixed CORS, but now process.env.SUPABASE_KEY is undefined.
Day 6: Environment variables set, but build fails with Module not found: Error: Can't resolve './components/SomeComponent' because the AI used inconsistent import paths.

Sound familiar? I've been through this cycle with every Bolt.new project I've tried to ship. The AI builds for the WebContainer environment, which has different assumptions than actual web servers.

The Core Problems

Development vs Production Environment

WebContainer vs Real Servers: Bolt.new's WebContainer runs Node.js in your browser. Real deployment platforms like Netlify and Vercel have different file systems, networking rules, and environment handling. What works locally doesn't translate directly.

AI-Generated Assumptions: The AI assumes certain npm packages are installed, makes API calls to localhost, and sometimes imports files with wrong case sensitivity. These work fine in development but explode in production builds on Linux servers.

Missing Production Configs: Bolt.new doesn't automatically generate production-ready configs. No production environment variables, no proper error boundaries, no CDN optimization. It builds for demo mode, not real user traffic.

Environment Variable Hell: The AI might hardcode database URLs or API endpoints that only exist in the WebContainer. Moving to production means reconfiguring every external service connection.

Real Deployment Errors (And How to Fix Them)

Q

Why does my build fail with "TypeError: fetch failed"?

A

This happens when your code tries to make API calls to localhost or relative URLs that don't exist in production.

Check your API calls

  • if you see fetch('/api/users') or fetch('http://localhost:3000/api'), that's your problem. Fix: Replace with absolute URLs to your deployed API or use environment variables. Change fetch('/api/users') to fetch(${process.env.NEXT_PUBLIC_API_URL}/api/users).
Q

Build succeeds but the deployed site is blank/white screen?

A

Usually means JavaScript errors that don't show in the build logs.

The most common cause is import path issues

  • the AI might import ./Component when the actual file is ./component (case sensitivity matters on Linux servers). Fix: Check browser console on the deployed site for errors. Look for "Module not found" errors and fix import paths. Also check if your index.html is pointing to the right JavaScript bundle.
Q

Environment variables work in Bolt.new but not in production?

A

Bolt.new's WebContainer automatically loads some environment variables that don't exist in real deployment environments. Common issues: missing database URLs, API keys, or authentication secrets. Fix: Set up environment variables in your deployment platform (Netlify, Vercel, etc.). For Next.js, make sure client-side variables start with NEXT_PUBLIC_. Don't forget to restart/redeploy after adding environment variables.

Q

Getting CORS errors that didn't happen in development?

A

WebContainer doesn't enforce CORS the same way real browsers do when hitting external APIs. Your deployed app runs from a different domain than your API, triggering CORS restrictions. Fix: Configure your API server to allow your production domain. For Supabase, add your deployment URL to allowed origins. For custom APIs, set the proper Access-Control-Allow-Origin headers.

Q

Database connections work locally but fail in production?

A

The AI might have configured your database connection for localhost or used connection strings that only work in WebContainer. Common error: ECONNREFUSED or connection timeout. Fix: Update database connection strings to use production database URLs. For Supabase, make sure you're using the API URL, not localhost. Check that your database allows connections from your deployment platform's IP ranges.

Q

Build fails with "Module not found" for components that definitely exist?

A

Case sensitivity and relative path issues. The AI sometimes creates imports like import Button from './Button' when the file is actually button.js or in a different directory structure. Fix: Check the exact filename and path. Linux servers (where most deployments run) are case-sensitive unlike the WebContainer. Use your IDE's auto-import feature or manually verify every import path.

The Nuclear Options (When Everything Else Fails)

Emergency Deployment Fixes

Sometimes your Bolt.new project is so thoroughly fucked that you need to take drastic measures. Here are the fixes of last resort when standard troubleshooting doesn't work.

Rebuild the Project from Scratch (But Smarter)

When the codebase is too tangled with WebContainer-specific assumptions, starting over is faster than debugging. But don't just copy-paste everything:

  1. Export and analyze: Download your Bolt.new project and identify what actually works vs. what's WebContainer magic.
  2. Separate concerns: Pull out the business logic, UI components, and API calls. The core functionality is usually sound - it's the integration layer that's broken.
  3. Use a production template: Start with Create Next App or Vite configured for your deployment platform.
  4. Port components one by one: Copy over your UI components first (they usually work fine), then add back the API integration with proper production URLs.

I've done this three times with complex Bolt.new projects. Takes 2-3 hours but saves days of debugging import paths and environment variables.

The Manual Deployment Escape Hatch

If Bolt.new's Netlify integration isn't working, fuck the automation. Deploy manually:

For Static Sites:

npm run build
## Upload the build/ or dist/ folder to Netlify manually
## Or use Netlify CLI: netlify deploy --prod --dir=build

For Next.js Apps:

npm run build && npm run export
## Deploy the out/ folder to any static hosting

For Node.js APIs:

## Push to GitHub
## Connect GitHub repo to [Railway](https://railway.app/), [Render](https://render.com/), or [Digital Ocean App Platform](https://www.digitalocean.com/products/app-platform)
## Much more reliable than trying to debug Bolt.new's deployment magic

Environment Variable Audit and Cleanup

Download your project and grep for every environment variable reference:

grep -r \"process.env\" . --include=\"*.js\" --include=\"*.ts\" --include=\"*.jsx\" --include=\"*.tsx\"
grep -r \"import.meta.env\" . --include=\"*.js\" --include=\"*.ts\"

Create a production .env file with proper values for each variable you find. Half the deployment issues come from missing or incorrectly named environment variables that worked by magic in the WebContainer.

The Dependency Hell Fix

Bolt.new sometimes installs npm packages that don't work in production builds. Check your package.json for weird dependencies:

npm ls --depth=0
## Look for packages you didn't explicitly ask for
## Remove anything that seems WebContainer-specific
npm uninstall <suspicious-package>

Common culprits: packages that assume Node.js APIs exist in the browser, or development-only packages that made it into production dependencies.

Database Migration Strategy

If your database setup is fucked, the cleanest approach:

  1. Export your data from Supabase (or whatever database Bolt.new set up)
  2. Create a fresh database in production with proper connection strings
  3. Recreate tables manually instead of relying on Bolt.new's auto-generated schemas
  4. Import your data into the clean database
  5. Update connection strings to point to the production database

Bolt.new's AI sometimes creates database schemas that work in development but have subtle issues in production (wrong indexes, missing constraints, etc.). A clean recreation fixes these.

The theme here: when Bolt.new's magic breaks, go back to standard web development practices. The AI built something that works, but it needs human intervention to make it production-ready.

Deployment Platform Reality Check

Platform

Bolt.new Integration

Real Success Rate

Common Issues

Time to Fix

Netlify

āœ… Built-in button

šŸ”„ 70% work first try

Environment variables, build commands

~2 hours

Vercel

āŒ Manual setup required

šŸ”„ 85% work first try

API routes, serverless functions

~1 hour

GitHub Pages

āŒ Export required

šŸ”¶ 50% work (static only)

No server-side rendering, no APIs

~4 hours

Railway

āŒ Manual deployment

āœ… 90% work once configured

Initial setup complexity

~3 hours

Render

āŒ GitHub integration

āœ… 85% work reliably

Slower cold starts

~2 hours

Production Deployment Resources

Related Tools & Recommendations

compare
Recommended

I Tested 4 AI Coding Tools So You Don't Have To

Here's what actually works and what broke my workflow

Cursor
/compare/cursor/github-copilot/claude-code/windsurf/codeium/comprehensive-ai-coding-assistant-comparison
100%
tool
Similar content

Fix Pulumi Deployment Failures - Complete Troubleshooting Guide

Master Pulumi deployment troubleshooting with this comprehensive guide. Learn systematic debugging, resolve common "resource creation failed" errors, and handle

Pulumi
/tool/pulumi/troubleshooting-guide
94%
howto
Similar content

Deploy Django with Docker Compose - Complete Production Guide

End the deployment nightmare: From broken containers to bulletproof production deployments that actually work

Django
/howto/deploy-django-docker-compose/complete-production-deployment-guide
89%
tool
Similar content

Arbitrum Production Debugging: Fix Gas & WASM Errors in Live Dapps

Real debugging for developers who've been burned by production failures

Arbitrum SDK
/tool/arbitrum-development-tools/production-debugging-guide
85%
tool
Similar content

TaxBit Enterprise Production Troubleshooting: Debug & Fix Issues

Real errors, working fixes, and why your monitoring needs to catch these before 3AM calls

TaxBit Enterprise
/tool/taxbit-enterprise/production-troubleshooting
83%
tool
Similar content

SvelteKit Deployment Troubleshooting: Fix Build & 500 Errors

When your perfectly working local app turns into a production disaster

SvelteKit
/tool/sveltekit/deployment-troubleshooting
81%
tool
Similar content

LM Studio Performance: Fix Crashes & Speed Up Local AI

Stop fighting memory crashes and thermal throttling. Here's how to make LM Studio actually work on real hardware.

LM Studio
/tool/lm-studio/performance-optimization
75%
tool
Similar content

Hardhat Ethereum Development: Debug, Test & Deploy Smart Contracts

Smart contract development finally got good - debugging, testing, and deployment tools that actually work

Hardhat
/tool/hardhat/overview
75%
compare
Recommended

Cursor vs Copilot vs Codeium vs Windsurf vs Amazon Q vs Claude Code: Enterprise Reality Check

I've Watched Dozens of Enterprise AI Tool Rollouts Crash and Burn. Here's What Actually Works.

Cursor
/compare/cursor/copilot/codeium/windsurf/amazon-q/claude/enterprise-adoption-analysis
71%
tool
Similar content

React Production Debugging: Fix App Crashes & White Screens

Five ways React apps crash in production that'll make you question your life choices.

React
/tool/react/debugging-production-issues
70%
tool
Similar content

Git Disaster Recovery & CVE-2025-48384 Security Alert Guide

Learn Git disaster recovery strategies and get immediate action steps for the critical CVE-2025-48384 security alert affecting Linux and macOS users.

Git
/tool/git/disaster-recovery-troubleshooting
70%
howto
Similar content

Mastering ML Model Deployment: From Jupyter to Production

Tired of "it works on my machine" but crashes with real users? Here's what actually works.

Docker
/howto/deploy-machine-learning-models-to-production/production-deployment-guide
70%
tool
Similar content

Claude AI: Anthropic's Costly but Effective Production Use

Explore Claude AI's real-world implementation, costs, and common issues. Learn from 18 months of deploying Anthropic's powerful AI in production systems.

Claude
/tool/claude/overview
70%
tool
Similar content

Node.js Production Deployment - How to Not Get Paged at 3AM

Optimize Node.js production deployment to prevent outages. Learn common pitfalls, PM2 clustering, troubleshooting FAQs, and effective monitoring for robust Node

Node.js
/tool/node.js/production-deployment
70%
tool
Similar content

BentoML Production Deployment: Secure & Reliable ML Model Serving

Deploy BentoML models to production reliably and securely. This guide addresses common ML deployment challenges, robust architecture, security best practices, a

BentoML
/tool/bentoml/production-deployment-guide
70%
news
Recommended

Claude AI Can Now Control Your Browser and It's Both Amazing and Terrifying

Anthropic just launched a Chrome extension that lets Claude click buttons, fill forms, and shop for you - August 27, 2025

anthropic
/news/2025-08-27/anthropic-claude-chrome-browser-extension
67%
news
Recommended

Hackers Are Using Claude AI to Write Phishing Emails and We Saw It Coming

Anthropic catches cybercriminals red-handed using their own AI to build better scams - August 27, 2025

anthropic
/news/2025-08-27/anthropic-claude-hackers-weaponize-ai
67%
news
Recommended

Anthropic Pulls the Classic "Opt-Out or We Own Your Data" Move

September 28 Deadline to Stop Claude From Reading Your Shit - August 28, 2025

NVIDIA AI Chips
/news/2025-08-28/anthropic-claude-data-policy-changes
67%
tool
Similar content

uv Docker Production: Best Practices, Troubleshooting & Deployment Guide

Master uv in production Docker. Learn best practices, troubleshoot common issues (permissions, lock files), and use a battle-tested Dockerfile template for robu

uv
/tool/uv/docker-production-guide
66%
tool
Similar content

Node.js Docker Containerization: Setup, Optimization & Production Guide

Master Node.js Docker containerization with this comprehensive guide. Learn why Docker matters, optimize your builds, and implement advanced patterns for robust

Node.js
/tool/node.js/docker-containerization
66%

Recommendations combine user behavior, content similarity, research intelligence, and SEO optimization