How I Learned to Stop Controlling Systems and Start Reacting to Reality

Why adopting an event-first mindset actually simplifies system design instead of complicating it

Nov 10, 2025

I used to build systems the “simple” way.

Direct API calls between services. Commands flowing from one component to another.

Everything explicitly connected and controlled. User Service tells Order Service to create an order. Order Service tells Inventory Service to reserve items. Inventory Service tells Payment Service to process the charge.

Clean, linear, easy to understand.

Then I watched those same systems become increasingly brittle.

Every business change required coordinated updates across multiple services.

A simple request like “send a welcome email when users make their first purchase” turned into an architectural overhaul involving four different teams. We spent more time managing dependencies than building value.

That’s when I discovered something counterintuitive: adopting an event-first mindset actually simplifies system design.

The complexity we were experiencing wasn’t from business requirements—it was from fighting against how business processes actually work.

When an event occurs in the real world, multiple things can happen simultaneously and independently. A customer makes a purchase, which should:

Update inventory counts
Trigger shipping processes
Send confirmation emails
Update analytics dashboards
Apply loyalty point rewards
Generate financial reports

In command-based systems, the ordering service has to know about and orchestrate all of these consequences. This creates tight coupling between systems that shouldn’t need to know about each other.

In the real world, these reactions happen naturally and independently. The event “customer made a purchase” simply occurred, and different systems react according to their own responsibilities.

Traditional systems are like having to physically flip every light switch in a building, while event-driven systems are like motion sensors that react to what actually happens.

The difference between commands and events isn’t just technical—it’s philosophical.

Commands: “System A tells System B what to do” Events: “Something happened, and systems react appropriately”

Commands represent control: One system decides what should happen next Events represent facts: Something occurred, and the consequences emerge naturally

In contrast, a command-based model requires the user to physically flip a light switch to turn on the light. This works fine for simple scenarios, but becomes unwieldy as complexity grows.

When an event occurs, it determines which processors or functions will use it, promoting decoupling. No single system needs to understand all the consequences of business events.

Instead of building tightly coupled command chains, I started building reactive systems around business events:

Treat Events as Immutable Facts

An event represents a fact: something happened, it is immutable, and it alters our domain model.

The mindset shift: Events aren’t instructions about what should happen next. They’re historical records of what already occurred.

Examples:

Not: CreateOrder (command)
Instead: OrderWasCreated (event)
Not: SendWelcomeEmail (command)
Instead: UserRegistered (event that triggers email sending)

Build Decoupled Processors That React to Events

Each processor can evolve independently because they’re only coupled to the event structure, not to each other.

How this works: When OrderWasCreated occurs:

Inventory Service reacts by updating stock counts
Email Service reacts by sending confirmation
Analytics Service reacts by updating dashboards
None of these services know about or depend on the others

The benefit: You can add new reactions without changing existing systems.

Establish Shared Business Language

It is important to establish a shared model that is comprehensible to everyone involved in the project.

Events become vocabulary: Business stakeholders can understand CustomerSignedUp, OrderWasShipped, and PaymentFailed without technical translation.

The result: Technical architecture directly reflects business processes instead of hiding them behind API abstractions.

Design for Independent Evolution

In this paradigm shift, we move away from traditional messaging and send events without relying on API coupling to a remote service.

Applications can add new reactions to existing events without changing the systems that emit them.

Example: Need to start sending SMS notifications when orders ship? Add a new processor that reacts to OrderWasShipped events. No changes to the shipping service required.

Address Trust and Transactionality Concerns

Evaluating this architecture involves many considerations: How do we ensure transactionality? How can we trust execution, security, lineage, and origin?

These are solvable challenges, not insurmountable barriers:

Event sourcing provides audit trails and replay capability
Saga patterns handle distributed transactions
Dead letter queues handle failure scenarios
Event schemas ensure backward compatibility

After implementing this approach across multiple systems:

Development velocity:

Changes to business logic required updates to individual processors, not coordinated system changes
New features could be added by creating new event processors without touching existing code
Deployment became independent—teams could ship without coordinating releases

Business alignment:

Business stakeholders understood system behavior because events matched their mental models
Requirements became clearer because we modeled what actually happens in business processes
As a result, the team gains a deeper understanding of the business processes being constructed

Technical benefits:

Horizontal scaling became natural because processors could be distributed independently
System complexity decreased because dependencies were explicit and minimal
A sequence of events captures temporal behavior, making business workflows visible and debuggable

Common Concerns and How to Address Them

“Direct API calls are simpler to understand”: The complexity is in understanding business processes, not the technical pattern. Events make business logic explicit rather than hidden in coupled services.

“Events add unnecessary abstraction”: This apparent complexity is actually clarity—you’re seeing the business rules that were always there, just previously hidden in service-to-service calls.

“What about consistency and transactions?”: Event-driven systems use eventual consistency and saga patterns. These are well-established patterns that work effectively for most business scenarios.

“How do we debug distributed event flows?”: Event sourcing and proper logging make event-driven systems more debuggable than traditional systems, not less.

Don’t try to rewrite your entire system overnight. Start with awareness:

This week: Look at one direct API call in your current system. Ask: “What business event is this representing?”

Next week: Identify one workflow that requires multiple services to coordinate. Map out the business events that occur in this workflow.

Week 3: Consider whether one of those events could be handled reactively instead of imperatively. What would change if systems reacted to events rather than being commanded?

Week 4: Prototype a simple event-driven flow. Publish one business event and create two independent processors that react to it.

Event-driven architecture isn’t about technology—it’s about modeling systems that reflect how business actually works.

The goal: Build systems that adapt to business changes naturally instead of requiring architectural overhauls.

The outcome: New requirements become new processors, not system redesigns. Business logic stays visible and comprehensible to all stakeholders.

The practice: Model what happens in business reality, then let systems react appropriately.

As systems grow, the benefits compound:

Small systems: Event-driven architecture might seem like overkill Medium systems: The decoupling benefits become apparent Large systems: Event-driven design becomes essential for managing complexity

It allows for horizontal scaling and fosters a shared language with the business. This isn’t just about technical benefits—it’s about building systems that serve business needs sustainably.

Every time you design service interactions, you choose: command or event, control or reaction, coupling or independence.

The questions that guide everything:

How much of our system’s brittleness comes from tight coupling that could be solved with event-driven thinking?
What business events are we currently modeling as imperative commands?
How would our architecture change if systems reacted to reality instead of trying to control it?

Start today: Look at one direct API call in your current system. Ask “What business event is this representing?” Consider whether that event could be handled reactively.

Systems should react to what happens, not control what should happen. Business alignment is waiting on the other side of that architectural shift.

What would your systems look like if they reflected business reality instead of fighting against it?

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