Task

Pamyatay Pro addresses a practical task: Pamyatay-pro is an application with a backend on Express using a Postgres database and a frontend on Next.js and React. Various LLM APIs are actively used for generating information of different types, ranging from text to audio and video generation. The application is currently in development, being maintained and improved in terms of module relevance and functionality.

The project is part of commercial development and is actively being worked on. It is related to services: Marketing and corporate websites.

This case demonstrates the approach to tasks in the area of "Marketing and corporate websites": from task setting to delivery with a clear module structure.

Before starting, we fixed the readiness criteria: a clear first screen, predictable form errors, and the possibility of enhancements without rewriting half of the codebase.

Solution

A working prototype/product has been assembled with clear navigation and predictable behavior of forms and lists. A demo is available via a link on the page.

The scenarios are designed so that the main actions fit within one or two screens: fewer switches, fewer input errors. Navigation and field labels are aligned with familiar patterns — the user does not need to "learn the interface".

Special attention is given to loading states and empty lists: skeleton/spinner where data comes asynchronously, and clear empty-state texts instead of an empty table.

Architecture and stack

UI and client: react, react-hook-form, tailwindcss.

Server and data: express.

Infrastructure and utilities: prisma, bcrypt, cors, dotenv, jsonwebtoken, multer, openai, pg, next, swiper, zustand, eslint.

Language distribution in the repository: HTML (57.3%), TypeScript (35.2%), CSS (3.5%), JavaScript (2.7%), Shell (1.1%), MDX (0.2%), Dockerfile (0.1%).

Layers are separated so that the UI does not know transport details: API/storage adapters, domain types, presentation components. This simplifies backend replacement and targeted UX fixes.

Key features

• prisma — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• bcrypt — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• cors — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• dotenv — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• express — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• jsonwebtoken — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• multer — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• openai — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.

Additionally:

• Integration and use of prisma in product logic and interface.
• Integration and use of bcrypt in product logic and interface.
• Integration and use of cors in product logic and interface.

Result

The MVP already covers the key scenario; next — expanding reporting, tests, and monitoring.

The source code is open: https://github.com/astropsy999/pamyatay-pro — you can assess the module structure and commit style.

An interactive demo is available via the link above — you can check the UX without deploying locally.

What I would improve

The next step is observability (logs/metrics), regression auto-tests, and API documentation for integrators. For high-load scenarios — profiling bottlenecks and caching reference data.