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I used to hate vibe coding. I believe I can write better code, design cleaner systems, and make more thoughtful architectural decisions on my own. For a long time, that was probably true. Over time, things changed. AI agents improved significantly. MCP servers, cloud capabilities, agent workflows, planned first executions, and long-horizon coding tools turned Webcoding from a gimmick into a practical way to build real systems.
At some point, I entered. Since then, I’ve been using cloud code and open code to build systems that I would normally consider too complex for rapid iteration. These include payment platforms, stablecoin wallets, book reading applications, and full-stack production-ready web systems. What surprised me was not just the speed, but the consistency of results once the right structure and tools were in place.
Most people encounter web coding is not writing code.
It’s choosing the right tech stack.
Frontend, backend, authentication, database, storage, email, payment and deployment all come with countless options. Without a clear stack, even strong AI coding agents struggle to make good decisions. When an agent is given a well-defined and opinionated tech stack, it can reliably develop an end-to-end application with very little friction.
That is the focus of this article.
I’ll go through my go-to tech stack for coding advanced applications. This is the stack I use again because it works. We’ll cover how the pieces fit together, what each tool is responsible for, and how to go from zero to a production-ready system. I’ll also share code sample hints and optional tools that help turn a working prototype into a production-ready system.
# My Tech Stack and Why This Stack Works
In this section, I’ll break down the exact tech stack used for webcoding and explain how these tools work together when building real applications.
Stack
- Next.js (AppRouter) -> Frontend and Layout
- Shad/UI -> UI components
- Server action + routes -> Backend logic and webhooks
- Soup base -> Database, Author, Storage
- Resend -> Transactional emails
- strip -> Payment and Subscriptions
- Vercel -> Deployment and Preview
This stack is intentionally simple. You can use the free tier of every platform listed here, which makes it ideal if you’re just starting out. You can deploy a complete application to Versal for free and integrated managed services at no cost.
Why does this stack scale without messing up?
Two next. JS primitives do most of the heavy lifting as the app grows:
- Server actions Handle form submissions and server-side conversions. They put the data closer to the UI and remove a lot of the boilerplate that usually appears early.
- Route handlers Handle webhooks, health checks, and custom endpoints. This gives you a clean place for external systems to talk to your app without polluting your UI logic.
Soup base With a security model that provides you with a database, authentication and storage that stays close to the data. If you enable row-level security early, permissions remain constant as the system grows and you avoid painful migrations later.
Resend Keeps transactional email simple and environment-friendly.
Strip checkout Coupled with webhooks, it gives you a reliable way to convert payments into real entitlements instead of scattered feature flags.
Vercel Keeps connecting preview and production deployments, so you’re testing in a real environment from day one.
This stack works well for web coding because it is feedback, predictable and easy to reason about the AI ​​coding agent. Once the boundaries are clear, the system is almost ready by itself.
# Plan from zero to paid MVP
This build plan is designed for webcoding with real tools. The purpose is to a First production ready skeletonthen add capacity in small steps without breaking earlier decisions. Each step maps directly to the stack you’re using, so the AI ​​coding agent can follow it to the end.
Phase 1: MVP Foundation
Create a complete product loop with minimal scope.
- Setup Next.js (AppRouter) project with Vercel Deployment
- Using the Dashboard Shell and Navigation Shad/UI
- Flow using authentication Soup base (Signup, Login, Reset)
- In a primary user-owned table Soupbase Postgres
- With the power of crowd screens Next. JS Server Actions
- Through preview deployments on every change Vercel
At the end of this phase, you already have a usable app running in production, even if the feature set is small.
Phase 2: Data Safety and Access Control
Lock user data before adding more features.
- Enable Row level protection On user-owned tables in SoupBase
- Define read and write policies based on ownership
- Use constant patterns like owner_add , create_at , update_at
- Validate access rules through real UI flow, not just SQL
This step prevents future rewrites and keeps security tied to how the app actually works.
Phase 3: Email and Storage
Add trust and file handling.
- Through transactional emails Resend (Welcome, Validate, Reset)
- Using private storage buckets Soap base storage
- Uploads that respect the same ownership rules as your database
- Signed URLs or controlled access based on user identity
This is where the product starts to feel complete rather than experimental.
Phase 4: Billing and Entitlement
Turn consumption into revenue.
- create Strip checkout Session and redirect users
- The handle Strip web hooks Next.js with route handlers
- Store subscription or purchase state in soup base
- Gate premium features based on stored entitlements
- Make the handling webhook idempotent using the processed event ID
By the end of this phase, you have a paid MVP that can scale without changing the core architecture.
# Cloud Code Starter Prompt
You can change “Bookshop + Reader MVP” with your idea using the same cloud code prompt.
Build a **Book Shop + Reader MVP** using this stack:
- Next.js App Router
- shadcn/ui
- Supabase (Postgres, Auth, Storage)
- Resend
- Stripe (Checkout + webhooks)
- Vercel
## Goal
Ship a production-ready Book Shop and Reader with paid access.
## Build
- Public pages: landing, pricing, book list
- Auth: sign up, sign in, reset password
- Protected app: reader dashboard
## Data
- `books`, `chapters`
- Row Level Security so users access only their own data
## Features
- CRUD via Server Actions
- Reader view with progress tracking
- Private storage for book assets
- Welcome email
- Stripe Checkout + webhook-based entitlements
## Output
- Clean app structure
- Minimal dependencies
- README with setup, env vars, migrations, Stripe, and Vercel steps
- Manual verification checklist per featureAll you need to do is switch cloud code Plan modepaste the hint, and change the idea or adjust the scope based on your needs.
Once you get started, Claude will first plan the system and then start construction step-by-step with no friction. It will also guide you through setting up the required services, creating accounts on third-party platforms, and generating API keys where needed.
This makes it easy to go from an idea to a working application without getting stuck on setup or decisions.
# Optional tools
These tools are not required to ship the first version, but they help you test, monitor, and harden as it grows into real use.
| category | Device options | What helps with that? | To add it |
|---|---|---|---|
| Unit test | Most of all | Fast tests for utility and server logic | Once the Core Crude works |
| Component test | React Testing Library | Capture UI regressions in shapes and states | After dashboard consolidation |
| End-to-end test | Playwright | Complete user flow: Signup → Create → Create Pay | Before adding more features |
| Error tracking | Sentry | Stack marks, health release, warning | As real users come |
| Inscriptions | Axis or logtail | Searchable application logs, webhook debugging | When webhooks and billing go live |
| Performance testing | Lighthouse (CI) | Grab slow pages and oversized bundles | Before the marketing launch |
| Schema and migration | Drizzle Kit or SQL Migration | The iterative schema changes | At this moment you have 2+ tables |
| Background jobs | ingest or trigger.dev | async tasks: emails, exports, cleanup | When workflows expand beyond requests |
| Rate limiting | Upstish Reads (or similar) | Protect authoring endpoints and webhooks | When the traffic becomes real |
| Product Analytics | PostThug (or similar) | Funnels, Activation, Feature Usage | When you know what you measure |
# Final thoughts
Advanced development and engineering tools are evolving rapidly. Most of them are now designed with AI integration in mind, offering good documentation, APIs, and MCP-style access so that AI agents can work directly with them and build software faster than ever before.
If you are a data scientist who has never touched web development, or a complete beginner who wants to build something real or launch a startup, I strongly recommend starting with this tech stack. It requires minimal setup and lets you deploy a working application immediately.
It took me about three months of testing and comparing tools before settling on this stack. Starting here will save you time.
If you want more flexibility later, you can separate things. For example, use Neon For the database, Clerk For validation, and keep everything the same. Spreading responsibilities across tools makes it easy to replace one part as your system grows without breaking the rest.
Easy, start the ship quickly, and only prepare when you need it.
Abid Ali Owan For centuries.@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in Technology Management and a Bachelor’s degree in Telecommunication Engineering. His vision is to create an AI product using graph neural networks for students with mental illness.