You can reach a production deployment without a developer writing the code, but launching a dependable production app without any engineering review is risky. Production introduces security, privacy, data integrity, monitoring, recovery, and maintenance requirements that a working prototype may not reveal.
Use an AI coding agent to plan and implement the product in small, testable stages. Define user roles, permissions, data retention, failure behavior, and service-level expectations. Require automated tests, source control, separate environments, secure secret handling, backups, logging, rate limits, and a rollback process. Review third-party services and their pricing before making them part of the architecture.
Verdent can help non-technical builders clarify requirements, dispatch implementation tasks, isolate changes, and review results. Those controls reduce risk but do not certify an application for production. Arrange independent review of authentication, payments, sensitive data, infrastructure, and legal obligations.
The practical answer depends on consequence. A low-risk internal tool may be reasonable with careful testing; a healthcare, financial, or high-volume customer system requires deeper expertise. AI can reduce the amount of developer labor, but someone must still own engineering decisions and incident response.
