Prompt2Prod.AI hardens AI-generated and vibe coded projects into production-ready software with senior engineering expertise.
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Get ListedPrompt2Prod.AI is a specialized engineering service that takes AI-generated code, vibe coded projects, and AI-built MVPs and transforms them into production-ready solutions. Founded by Sonaht Tech, the service addresses a growing pain point in the software industry: AI tools like Cursor, Copilot, and ChatGPT enable rapid prototyping but often produce code that is fragile, insecure, and unscalable. Prompt2Prod.AI positions itself as the bridge between fast AI-generated prototypes and robust, maintainable production systems.
The market for AI-assisted coding has exploded, with developers using large language models to generate entire codebases in hours. However, the output frequently lacks proper authentication, input validation, error handling, and architectural coherence. Prompt2Prod.AI targets this gap by offering a structured process: assessment, audit, hardening, and delivery. The service promises to preserve working functionality while fixing critical gaps, avoiding unnecessary rewrites.
What sets Prompt2Prod.AI apart is its focus on the specific failure modes of AI-generated code. The team uses the same AI tools their clients use, giving them pattern recognition for common issues like exposed secrets, N+1 queries, and missing authorization flows. This approach allows faster assessments and more targeted fixes than traditional code review services.
The service is aimed at startups, indie developers, and product teams who have built an AI-generated prototype or MVP and need to take it to production without starting from scratch. It also serves teams that have inherited AI-generated codebases that are difficult to maintain or scale.
Production Readiness Assessment – A comprehensive audit of the codebase covering security vulnerabilities, scalability bottlenecks, performance issues, and maintainability problems. The assessment produces a prioritized report with concrete findings and a remediation plan. This can be a standalone deliverable for teams that want to fix issues internally.
AI Code Hardening – Targeted fixes for the most common weaknesses in AI-generated code: missing authentication, broken authorization, exposed secrets, lack of input sanitization, and poor error handling. Each fix is documented and tested by a senior engineer.
Vibe Coded Project Rescue – A structured intervention for projects built rapidly with AI tools that have become unmaintainable. The service untangles the codebase, fixes bugs, adds test coverage, and restores architectural coherence. The goal is to hand back a codebase that the original team can confidently maintain.
Security Hardening – An OWASP-aligned security audit specifically designed for AI-generated code. The service checks for the top vulnerabilities that AI tools commonly introduce, including broken access control, cryptographic failures, injection flaws, and security misconfiguration. All critical findings are remediated with documented changes.
Performance Optimization – Profiling and optimization of AI-generated code to address slow APIs, N+1 database queries, bloated bundles, and inefficient infrastructure usage. The service identifies real bottlenecks and ships targeted optimizations that produce measurable improvements in speed and cost.
Architecture Review and Scalability – An evaluation of the codebase's structural integrity, including separation of concerns, module boundaries, and growth strategy. The service introduces sound architectural patterns without over-engineering, ensuring the system can scale with user demand.
Senior-Only Engineering – Every engagement is handled directly by an experienced engineer, not a junior team member or account manager. This ensures fast ramp-up, clear communication, and decisions driven by business outcomes rather than technical dogma.
The process begins with a simple outreach: a prospective client sends a message describing their project, what AI tools were used, and what problems they are facing. There are no lengthy forms or sales qualification calls. The team responds directly, typically within hours.
Next comes a focused 30 to 45 minute assessment call. The engineer asks direct questions about the codebase, the build process, the current pain points, and the production requirements. This call is not a generic script; it is tailored to understand the specific context of the project.
After the call, the team conducts a full codebase audit. They examine security, scalability, performance, and maintainability. The output is a production readiness report that lists every finding, its risk level, and a concrete plan for remediation. This report can be used as a standalone deliverable if the client prefers to fix issues with their own team.
Finally, the hardening phase begins. The team works through the findings systematically, closing security gaps, improving architecture, adding tests, and tuning performance. Regular progress updates keep the client informed. At the end, the client receives a fully documented handover, including what was changed and why.
Startup with an AI-Built MVP – A founder uses Cursor to build a prototype for a SaaS product. The prototype works for demo purposes but crashes under real user load. Prompt2Prod.AI assesses the codebase, identifies missing error handling and inefficient database queries, and hardens the system for production. The startup launches on time without a full rewrite.
Indie Developer with a Vibe Coded Project – A solo developer builds a side project using ChatGPT and Bolt. The project gains traction but becomes impossible to maintain. Bugs pile up, and every new feature breaks something. Prompt2Prod.AI untangles the code, adds test coverage, and restores maintainability. The developer can continue building with confidence.
Team Inheriting AI-Generated Code – A product team acquires a codebase that was largely generated by AI. The code works but has no documentation, no tests, and unclear architecture. The team is afraid to make changes. Prompt2Prod.AI audits the codebase, documents the architecture, and fixes the most critical security and scalability issues. The team gains a clear understanding and a safe path forward.
Enterprise Security Audit – A company uses AI tools internally to generate code for internal tools. The security team is concerned about vulnerabilities. Prompt2Prod.AI conducts an OWASP-aligned audit, identifies exposed secrets and missing authentication, and remediates all critical findings. The company gets a documented security baseline.
Performance Rescue – A web application built with AI tools works fine in development but slows to a crawl under real traffic. Prompt2Prod.AI profiles the system, identifies N+1 queries and inefficient API endpoints, and optimizes the code. The application becomes responsive and infrastructure costs decrease.
Prompt2Prod.AI does not publish fixed pricing on its website. Instead, pricing follows the scope of work. Most engagements begin with a clearly scoped production readiness assessment at a fixed price. After the assessment, hardening and recovery work is quoted against an agreed plan. This approach ensures clients know exactly what they are committing to before work begins.
The value proposition is strong for teams that have invested time in an AI-generated codebase but cannot afford a full rewrite. The cost of a targeted hardening engagement is typically far less than rebuilding from scratch, and the turnaround time is measured in days rather than months. For startups on tight deadlines, this can be the difference between launching on time and missing a market window.
Potential clients should request a readiness assessment to get a tailored quote. The service is best suited for projects that have working functionality but need professional hardening to go live.
Prompt2Prod.AI fills a genuine need in the AI-assisted development ecosystem. As more developers use AI tools to generate code, the gap between fast prototypes and production-ready systems will only widen. The service offers a practical, cost-effective solution: preserve what works, fix what doesn't, and avoid the expense and risk of a full rewrite.
The main strength is the team's deep understanding of AI-generated code patterns. They know where AI tools cut corners and how to fix those gaps efficiently. The senior-only model ensures quality and fast ramp-up. The process is transparent, with clear deliverables and no hidden surprises.
Areas for improvement include the lack of published pricing, which may deter some potential clients who prefer upfront transparency. Additionally, the service is currently focused on code hardening rather than ongoing development or maintenance, so clients will need to manage the codebase themselves after the engagement.
Overall, Prompt2Prod.AI is a valuable resource for any team that has built an AI-generated prototype and needs to take it to production. It is especially useful for startups, indie developers, and product teams on tight timelines. For those interested, learn more about their process or check their expertise areas.
