01
Client input
AI-generated source code received
The client already had an application foundation generated largely with AI.
From AI-generated code to production-ready software.
We help businesses take an existing AI-generated application, validate what works, fix what fails, secure the codebase, test real workflows, and move the product safely from sandbox to production.
Starting point
An existing AI-generated codebase, already in the client’s hands.
The foundation existed, but the application still needed engineering validation before it could safely move toward production.
Our role
Techphant rebuilt only what the codebase actually needed.
We understood the existing codebase, repaired failures, completed missing workflows, improved security, tested the product, and moved it toward production readiness.
02
Stabilize
Run, validate, and repair blocking errors
We checked whether the app could build, start, connect, and perform basic functions.
03
Workflow testing
Test complete application flows
We tested real user journeys instead of checking isolated screens or APIs.
04
Fix gaps
Complete missing logic and fix bugs
AI agents helped analyse the codebase while developers validated every change.
05
Security review
Review code quality and vulnerabilities
The codebase was checked for security risks, dependency issues, and quality problems.
06
Sandbox
Move into sandbox and fix environment issues
The application was tested in a production-like sandbox environment.
07
Production
Release, monitor, and respond
After validation, the project moved into production with post-release observation.
Engineering loop
AI accelerated delivery. Human engineering review kept the product safe.
AI was part of the engineering loop, but it did not replace engineering judgement, static analysis, workflow testing, or the deployment tooling that carries a release to production.
AI Agent
Analyses code, traces dependencies, suggests fixes, and accelerates debugging.
- Claude Code
- GitHub Copilot
Static Analysis
Automated scanning for vulnerabilities, dependency risks, and code-quality issues.
- Snyk
- Qodana
- Dependabot
- CodeRabbit
Developer
Reviews logic, validates fixes, tests workflows, and makes engineering decisions.
- Code review
- Manual QA
Testing
Confirms the application behaves correctly before moving forward.
- Workflow tests
- Sandbox validation
Deployment
Reproducible infrastructure and automated pipelines carry the release to production.
- Terraform
- Docker
- CI/CD pipelines