Product Requirements & Technical Architecture

We've asked what to build and why. Now we ask: how should we build it?

This is where engineering becomes a real advantage — with one warning: architecture should serve the product, not the other way around. A technically impressive system that solves the wrong problem is still a bad system.

Don't Jump From “I Have an Idea” to “Let's Create the Database”

The sequence I use:

Business problem → Customer → Desired outcome → Workflow → Product requirements → Technical requirements → Architecture → Implementation

The further down you go, the more technical the conversation. Jumping straight to the database is backwards. If the problem isn't validated yet, start with whether it's worth solving and don't build the wrong product first.

What Is a PRD?

PRD means Product Requirements Document. It describes what the product needs to accomplish. It isn't primarily a programming document. It connects business → product → engineering.

A good PRD answers: who is using it, what problem they solve, what they should be able to do, what the system should do, what constraints exist, and how success is measured.

Functional vs Non-Functional Requirements

Functional = what the system must do. Users can create accounts. Staff can record sales. Managers can view reports. Administrators can deactivate accounts.

Non-functional = how the system should perform: performance, security, availability, reliability, scalability, accessibility, maintainability.

Example: if a product is offline-first (like a POS that must work when the internet drops), “the core sales workflow remains usable without connectivity” is a non-functional requirement. That one sentence can decide the entire architecture — not because a stack is fashionable, but because the product requires it.

Not every requirement is equal. Tag them: critical / high / medium / low. That stops the team treating every request as equally urgent. Same idea as not adding every feature.

User Flows and Use Cases Beat “Build an E-Commerce App”

A user flow is how someone moves through the product: browse → cart → checkout → confirmation. A use case is an actor + goal + steps + exceptions (e.g. cashier records a sale; system checks stock; insufficient stock applies a business rule).

That level of thinking exposes requirements a feature list hides — and it shows which parts of the system a sale actually touches: records, inventory, payments, reports.

What Software Architecture Actually Means

Architecture is the structure of the system and how its major pieces relate. You don't start a building by choosing paint. You start with foundation, rooms, plumbing.

A typical web app:

User → Frontend / App → API → Backend → Database, Auth, Services (email, payments)

Each piece has a job. That's architecture — not a list of trendy tools.

Frontend, Backend, Database, APIs

Frontend is what users touch: screens, forms, navigation. React, Next.js, React Native, Flutter — the framework is a consequence of requirements, not the starting point.

Backend is business logic, permissions, data, APIs, jobs, integrations. FastAPI, Node, Django, Laravel — pick based on team skill, requirements, ecosystem, cost, and expected scale. Not Twitter.

Database: there is no universally “best” database. Ask what data model and access patterns the product needs. Financial transactions often want relational consistency (PostgreSQL). Offline-first sync is an architectural question, not a preference.

APIs let systems talk. The app shouldn't usually talk straight to the database. Request → API → backend authenticates, checks permissions, queries, responds. Don't trust the frontend alone to enforce critical authorization. A malicious client can skip client-side checks. Security-sensitive rules live on the server.

Authentication vs Authorization — and MVP Doesn't Mean Unsafe

Founders sometimes say: “It's only an MVP. We'll secure it later.” Some things can be simplified. Security fundamentals should not be casually deferred — passwords, access control, validation, HTTPS, secrets, backups, logging, handling sensitive data. MVP does not mean unsafe. That's one of the architecture mistakes that kill startups.

Don't Architect for 10 Million Users When You Have 20

The better question: what scale do we realistically expect, and which decisions would block us from getting there?

Middle path: today's validated requirements + a reasonable path toward tomorrow. Same idea as build for one customer before one million.

Monolith vs microservices

Microservices ≠ “advanced.” For an early startup, a modular monolith is often the right call: one app with users, sales, inventory, payments, reports — simple to deploy and understand. Microservices add networking, monitoring, and distributed-systems pain. Don't architect for prestige. Architect for the business.

Build vs buy

Payments, email, SMS, auth, analytics — usually don't build all of that. If it isn't strategically differentiating, integrate a provider. Build when it's core to your product. Buy when it's commodity and maintenance would eat the team.

Tradeoffs and decision records

There is rarely a perfect architecture. You trade speed vs flexibility, simplicity vs customization, cost vs performance. A good technical partner doesn't say “this is perfect.” They say: “Given our constraints, this is the best tradeoff.”

For significant choices, write a short Architecture Decision Record: what we chose, why it mattered, alternatives, reason, consequences. Better than “we use PostgreSQL because it's good.”

Explain Architecture in Business Language

Don't lead with “REST, JWT, Postgres, Redis, Docker, Kubernetes.” Say: We'll separate the customer-facing app from the core business system so we can protect data, control permissions, and change the UI without rebuilding everything underneath.

Technical: “Redis will cache frequently accessed data.” Founder: “We'll keep frequently requested information ready so the system stays fast as usage grows.” You don't hide the tech. You translate it.

If a founder says “I need an Uber-like app,” the weak answer is a stack. The stronger answer is: who, what problem, core workflow, critical requirements, constraints — then architecture. That's the difference between coding and being a technical partner.

Mistakes I See Constantly

• Choosing technology before understanding requirements
• Overengineering an MVP
• Ignoring non-functional requirements
• Treating security as optional
• Building every infrastructure piece from scratch
• Designing for millions of users when you have none
• Never writing down why a decision was made
• Explaining technical decisions only in technical language