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Pragmatic Coders

Your vibe-coded app took off — now make it reliable

About

Pragmatic Coders runs a Vibe Coding Rescue service line for founders whose AI-built app got traction and needs to survive real users. Their stated focus is making vibe-coded apps reliable, scalable, and secure across four areas: code and performance optimization, security audit and hardening, software testing and QA, and UX improvements. The engagement opens with a free first consultation and a Code Assessment that scales with codebase size. They publish a 10+ year track record and cite that 8 of 10 founders who contact them choose to work with the team. Krakow-based with delivery across Europe and the US.

Services

First Consultation

Code Review

Free intro call with their AI systems consultant to scope what is broken and what is worth keeping.

Free

Code Assessment

Security Audit

Sized to your codebase. Quote-on-call. Covers Code & Performance Optimization, Security Audit & Hardening, Software Testing & QA, and UX/Design Improvement.

Custom quote

Vibe Tool Expertise

Tech Stack

react
node
supabase
ExpertProficientFamiliar

Problems This Agency Can Fix

Security Vulnerabilities
Critical

AI coding tools often generate code with exposed API keys, missing input validation, broken authentication, and insecure data handling. These vulnerabilities can lead to data breaches, unauthorized access, and compliance failures.

Broken Authentication
Critical

Authentication is one of the most common failure points in vibe-coded apps. AI tools frequently generate insecure auth flows, missing session validation, broken password resets, and improperly configured OAuth.

Database Issues
High Priority

AI-generated database schemas often lack proper indexes, have no Row Level Security, use inefficient query patterns, and create data integrity problems. These issues worsen as your app grows.

Code Quality Issues
Medium

AI-generated codebases frequently have duplicated logic, inconsistent patterns, missing error handling, no TypeScript strict mode, and poor separation of concerns. This makes maintenance and feature additions increasingly difficult.

API Integration Issues
Medium

AI tools often generate API integrations with missing error handling, no retry logic, hardcoded endpoints, and insecure credential storage. These integrations break silently and are difficult to debug.

Mobile Issues
Medium

AI-generated UIs often look great on desktop but break on mobile devices. Missing responsive breakpoints, oversized images, touch-unfriendly controls, and fixed-width layouts create poor mobile experiences.

SEO Issues
Medium

AI-generated apps often lack proper meta tags, structured data, semantic HTML, and server-side rendering. This makes them invisible to search engines and kills organic traffic potential.