An AI-built web application still needs a technology stack that fits its purpose. The stack typically includes the front-end framework, backend services, database, authentication, hosting, and any external integrations the product requires. It can be tempting to select technologies because they are popular or because an AI assistant recommends them, but popularity alone does not determine suitability. A small internal dashboard has different needs from a high-traffic marketplace or a SaaS product with complex billing. Before choosing a stack, consider your team's experience, the data the application stores, the integrations it needs, and how you expect it to grow. An AI app builder such as Greta.sh can help you move from an initial idea to a tangible application concept, but the underlying technical choices still deserve careful review. Avoid adding services you do not need, and make sure the team understands how the application will be deployed, monitored, and updated. For applications with user accounts, review database permissions and server-side authorization rather than relying only on hiding interface elements. Document important decisions so future developers can understand the project. A good tech stack is not necessarily the most sophisticated one. It is the combination of technologies that allows you to build, operate, and maintain the application reliably.
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