The Pros and Cons of Making Your Product Dynamic - Prioritizing Flexibility, Budget, and Time
When to build configurable systems vs. hardcode it. Real examples of when I got this right, and when I over-engineered.
When to build configurable systems vs. hardcode it. Real examples of when I got this right, and when I over-engineered.

I have a problem: I want to make everything configurable.
Payment gateway? Don't hardcode it — build an abstraction layer so we can swap providers. Discount rules? Make them admin-configurable. Email templates? Obviously dynamic.
This instinct has saved me countless times. It's also burned me badly when I over-engineered systems that never needed to change.
Here's what I've learned about when to build dynamic vs. when to just hardcode it.
1. When the business changes faster than you can deploy
I built an e-commerce platform where the marketing team needed to create new promotions weekly — buy-one-get-one, tiered discounts, flash sales, bundle deals.
If every promotion required a code change, we'd need:
Instead, we built a rules engine. Marketing could create promotions through an admin panel. Time from idea to live: 30 minutes instead of 3 days.
ROI calculation: If you need 50 promotions/year and each hardcoded change costs $500 in dev time, that's $25K/year. A rules engine that costs $40K to build pays for itself in under 2 years — and gets faster every year after.
2. When you have multiple clients/tenants
For a multi-tenant platform, hardcoding means maintaining separate codebases or config files for each client. That doesn't scale.
We built a system where each tenant could configure:
One codebase, 12+ clients, each with different configurations.
3. When regulations vary by market
Selling in UAE vs. EU vs. US? Tax rules, data retention, consent requirements — all different.
Hardcoding market-specific logic creates a maintenance nightmare. A config-driven approach lets you add markets without code changes.
1. Building for hypothetical flexibility
Early in my career, I built a "flexible" user role system with dynamic permissions, custom role creation, and hierarchical inheritance.
The client used three roles: Admin, Manager, User. For three years. They never created a custom role.
I spent 3 weeks building a system that a simple hardcoded enum would have handled in 2 hours.
Lesson: Build for the requirements you have, not the requirements you imagine.
2. When the dynamic system becomes harder than code changes
I've seen admin panels so complex that business users were afraid to touch them. "What if I break something?"
If your dynamic system requires training sessions and documentation, you've just moved complexity from code to config. Sometimes that's worth it. Often it's not.
3. Performance overhead
Dynamic systems have runtime costs:
For a high-frequency system doing 150+ operations/second, a rules engine that adds 50ms latency per request is a problem. Sometimes hardcoded logic is just faster.
I ask three questions:
1. How often will this actually change?
Be honest. Not "how often might it change" but "in the last year, how many times did we need to change this?"
2. Who needs to make the change?
3. What's the cost of getting it wrong?
If you hardcode and it needs to change: you deploy code. Cost = dev time + deploy risk.
If you build dynamic but it never changes: you paid for complexity you don't use. Cost = initial dev time + ongoing maintenance.
I'd rather pay the "hardcode tax" of occasional deploys than maintain a dynamic system nobody uses.
Not everything needs an admin UI. Sometimes a config file or environment variable is enough:
# Instead of this (hardcoded)
DISCOUNT_PERCENTAGE = 10
# Do this (configurable, but simple)
DISCOUNT_PERCENTAGE = env("DISCOUNT_PCT", default=10)
This gives you flexibility without building a whole admin panel. You can change it without redeploying (depending on your setup), but you don't have the overhead of a dynamic system.
Dynamic systems trade initial development time for ongoing operational speed.
The math only works if:
If all three aren't true, hardcode it and move on. You can always refactor later when you have real data on how often things actually change.
Bottom line: My instinct is still to make things configurable. But I've learned to ask "will this actually change?" before building abstractions. The best code is often the simplest code that solves today's problem.