Resisting the Rush: Why Careful Planning Beats Quick Coding

Quality Software is not developed in a rush

In the fast-paced world of tech startups and software companies, there’s a
persistent pressure to deliver products rapidly. Teams are often celebrated for
shipping features quickly, and managers may reward short time-to-market above
all else. This culture, focused on “moving fast and breaking things,” creates
an environment where the urge to dive straight into coding is almost
irresistible.

“No matter how slow you are writing clean code, you will always be slower if you make a mess.”

— Robert C. Martin (Uncle Bob)

However, this emphasis on speed often comes at a significant cost. When we
prioritize immediate results over thoughtful design, we risk creating software
that is fragile, difficult to maintain, and poorly suited for growth. It may
look good in the short term, but in just a few months or years, these quick
wins can turn into costly technical debt.

The advent of AI-powered development tools—like Cursor, Windsurf, or code
co-pilots—has, in some cases, made it even easier to bypass essential design
phases. With these tools, developers can generate “production-ready” code from
brief descriptions and minimal guidance. But while AI can accelerate certain
tasks, it does not replace the need for solid architecture, robust interfaces,
and a deep understanding of the domain. As impressive as AI might be, shipping
code quickly is not the same as shipping code well and more than anything else,
code that will last the test of time.

In reality, writing code is the easy part. The real challenge, and where the
majority of value is created, lies in designing the architecture and shaping
the interactions between components. The structure and relationships of your
classes, modules, and data flows matter more to long-term success than any
clever piece of implementation.

Let’s take a deeper look at why resisting the rush and investing time in
thoughtful software planning leads to far better outcomes—not just for
developers, but for businesses and users as well.

Understanding the Domain

Before even opening your IDE, take a step back and immerse yourself in the
problem space. Understanding the domain is the foundation upon which robust
software is built. This stage involves several key activities:

• Gathering Requirements: Talk to people who will use or be affected by
  your software—end users, business stakeholders, domain experts. Get a
  360-degree view of their needs, pains, and desires.

• Engaging with Stakeholders and Subject Matter Experts: Their insights
  help clarify what’s essential and what’s not, and often bring context that
  goes beyond written requirements.

• Surveying Similar Solutions: Review how others have solved similar
  problems. Are there best practices or common pitfalls to be aware of? Often,
  you can avoid reinventing the wheel.

• Writing a Design Document: Capture your domain understanding,
  assumptions, and key requirements in a living document. This isn’t just for
  process; it ensures everyone shares a common language and mental model.

Skipping this phase is a recipe for building the wrong thing, no matter how
quickly you do it.

The Importance of Written Design Plans

Many developers find planning tedious, especially if they’re eager to get their
hands dirty with code. But a written design plan acts as a critical
thinking tool. It clarifies your vision, exposes hidden assumptions, and spot
challenges early on.

Drafting pseudocode, creating UML diagrams, or even sketching simple flowcharts
helps you see problems before they become costly. These tools push you to
answer the tough questions: How will components communicate? What interfaces
will you expose? Where might bottlenecks or risks arise?

Investing a few hours (or days for large projects) upfront will pay huge dividends
throughout the project lifecycle. A clear plan leads to fewer surprises, less
stress, and much higher quality work.

Designing Software: From Interfaces to Implementation

Experienced developers know that software should be crafted from the top down,
starting with its public interfaces and working inward. On the other hand
concentrating on implementation details too early can not only delay the project
but can easily lead to a tangled mess of code that is missing the big picture
and the general architecture.

This means:

• Think in Terms of Interfaces: Define how each module, service, or class
  will interact with the rest of the system. Start generically: what do you need
  to accomplish, and what information needs to move between parts?

• Progress from Generic to Specific: After high-level outlines are clear,
  gradually fill in the lower-level details. This process prevents
  over-complication and keeps the design flexible.

• Determine Class Interactions: Carefully define how your core classes
  interact—not just with each other, but with third-party libraries, APIs,
  databases, and external services.

• Anticipate Change: A well-designed interface isolates parts of your
  system so that changes in one area don’t ripple through the rest, reducing
  the risk of bugs and making maintenance far easier.

Rushing past this phase leads to tightly-coupled, fragile code, where a single
change can break unrelated features—a nightmare scenario for scaling teams.
Wishful thinking about cutting corners and “getting it done” will only lead to
a technical debt that will haunt you soon as the project will be adopted by
users and getting more complex and demanding.

Planning Before Coding

With your domain understanding and interfaces outlined, it’s time to flesh out
the technical details:

• Architecture Sketching: Lay out your solution at a high level
  (pseudocode, UML, flow diagrams, or even index cards on a wall).

• Class and Module Interfaces: Precisely define method signatures, expected
  inputs/outputs, and communication channels. Make parameters to functions as
  simple as possible, and avoid passing complex objects unless absolutely
  necessary.

• Select Design Patterns: Identify patterns (such as MVC, Observer,
  Singleton, Proxy etc) that are suitable for your problem.

• Plan for Testing: Decide early what data you’ll need for realistic
  testing, and integrate testability into your design.

• Third-Party Libraries: List any external packages or APIs you plan to
  use, considering issues like licensing, support, and potential for vendor
  lock-in. Develop having in mind to avoid dependencies to third parties and
  considering that they can be replaced in the future by another similar.

• Custom Algorithms: Highlight where off-the-shelf solutions won’t work,
  and isolate areas for bespoke development.

Deliberate planning at this stage not only streamlines implementation but also
makes it easier to onboard new developers and pass code reviews.

Thoughtful Coding and Deployment Practices

Once coding begins, resist the temptation to abandon your careful plans. You
should:

• Build in Small Increments: Focus on delivering small, working slices of
  functionality. This enables continuous feedback and reduces the risk of
  large, hard-to-debug problems.

• Start Generic, Move to Specific: Begin implementation with the most
  abstract base classes and work toward specific subclasses and features. This
  order maximizes reuse and minimizes refactoring.

• Write Clean, Readable Code: Prioritize clarity over cleverness. Document
  crucial functions and decisions inline. Consistent style and naming prevent
  confusion.

• Decouple from External Dependencies: Abstract away third-party libraries
  as much as possible. This minimizes vendor lock-in and allows you to swap out
  components with fewer headaches in the future.

• Design for Testability: Integrate automated tests as you go. High test
  coverage reduces the possibility of regressions and makes refactoring less
  risky.

• Frequent Deployment and Feedback: Deploy early and often. Encourage real
  users to provide feedback; it’s the only way to catch usability issues and
  corner-case bugs before they escalate.

Resist shortcuts and “quick and dirty” hacks—even under time pressure. These
choices may save a day or two now but will cost you weeks or months later.

The Value of Literate Programming

All of the above approaches align with the principles of literate programming,
introduced by Donald Knuth. Literate programming treats code as
communication—not just with machines, but with humans. Code should be
accompanied by explanations, design rationales, and structured commentary.

Knuth’s philosophy suggests that code and documentation go hand-in-hand. By
explaining your intentions as you design and build, you produce software that
is not only correct but also comprehensible and sustainable. This pays off when
onboarding new developers, debugging, or adapting your system years later.

Aim to make your programs readable for both current collaborators and your
“future self,” who may have forgotten today’s context. As Knuth says:

Programs should be written for people to read, and only incidentally for machines to execute.

Conclusion: Building Software That Lasts

The temptation to cut corners, dive straight into coding, and deliver solutions
as quickly as possible is understandable in the competitive landscape of
modern software development. However, the true measure of software isn’t how
fast it’s built, but how gracefully it evolves, how easily it’s maintained, and
how well it serves its users over time.

Quality software emerges from careful planning, thoughtful design, and
disciplined implementation. Starting with a deep understanding of the problem,
documenting a clear plan, defining robust interfaces, and coding with
testability and maintainability in mind separates high-performing teams from
those continually fighting fires.

So next time you’re handed a new project or feature, pause before typing your
first line of code. Invest the time to chart your course. Resist the rush.
Build smartly—not just quickly—and your software will reward you and your users
for years to come.