Rocking Tech
Three steps from stuck to production-ready
About
Rocking Tech is a UK-based boutique that pioneered the Platform Rescue model: a structured ladder for founders whose vibe-coded prototype just met real users and broke. Their engagement runs in three phases. A free 30-minute Code Health Assessment determines whether the codebase is worth saving. The fixed-price Platform Discovery Sprint delivers a 15-20 page Code Health Scorecard and a production roadmap over three weeks. The optional Custom Platform Build then rebuilds on Laravel with fixed pricing across 8-16 weeks. The Sprint fee is credited toward the Build, so founders can validate the rescue plan before committing to the full rebuild. Known for no-nonsense communication, transparent fixed pricing, and rebuilds that take Bolt.new and Lovable exports from sub-second demo to a production-ready Laravel + React stack.
Services
Code Health Assessment
Free 30-minute call to determine whether your vibe-coded app is worth saving. Honest verdict, no pitch.
Platform Discovery Sprint
Three-week full codebase audit delivering a 15-20 page Code Health Scorecard and production roadmap. Fee credited toward the Custom Build if you proceed.
Custom Platform Build
Production rebuild on Laravel + React over 8-16 weeks. Fixed pricing. Discovery Sprint fee credited in full.
Vibe Tool Expertise
Tech Stack
Problems This Agency Can Fix
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.
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.
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.
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.
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.
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.
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.
AI-generated applications often suffer from unoptimized database queries, excessive re-renders, large bundle sizes, and missing caching. This leads to slow page loads, poor Core Web Vitals, and frustrated users.
AI-generated code often works locally but fails during deployment. Common issues include missing environment variables, incorrect build configurations, incompatible dependencies, and misconfigured hosting platforms.
AI-generated apps often hit walls when traffic or data volume increases. Missing caching, unoptimized queries, no CDN configuration, and monolithic architectures prevent apps from handling real-world load.