Introduction

Learning software fundamentals feels slow compared to copying a tutorial and shipping immediately. In this article, I explain what fundamentals are, why they matter, and how they reduce confusion as systems grow.

I build software and use it all day. I can tell when something is built on fundamentals, and when it is held together by chewing gum, duct tape, and mysterious copy-pasted snippets.

When fundamentals are missing, everything hurts:

I study and document software fundamentals because they enable me to create high-quality software for users, colleagues, and myself. Mastering these fundamentals allows you to also produce excellent software, even as tools evolve.

What This Is (and Isn’t)

This article explains software fundamentals, their importance in real work, and the trade-offs in learning them. Aimed at beginners, it focuses on understanding rather than checklists.

Fundamentals Help You Keep Your Promises

Software symbolizes a relationship where users trust you with their time, attention, money, and data. Fundamentals show respect for that trust.

I see fundamentals as mental models that help answer questions like:

  • What happens when this code runs, from input to output?
  • What breaks when the network is slow, or a dependency fails?
  • What a system does under load, and why it becomes slow.
  • How mistakes turn into security problems.
  • Why does a bug reproduce for real users but not on your laptop?

My fundamentals series covers key topics in every serious system.

These topics aren’t academic; they differentiate reliable software under pressure from software that becomes a pain to use and maintain.

If you want the meta version of this argument, read fundamentals of fundamentals.

Fundamentals Age Well, Frameworks Age Fast

Frameworks change rapidly, emphasizing convenience, fashion, and current constraints.

Fundamentals change slowly because they reflect our enduring reality, which—like physics—doesn’t care about your feelings.

  • A computer always executes instructions.
  • A network will always drop packets and add latency.
  • Data always needs structure, constraints, and retrieval strategies.
  • Humans (and large language models) will consistently misread unclear interfaces and unclear documentation.

This connects directly to my software development philosophy. One of my core beliefs is that everything changes, which is why I try to “stay liquid” and build systems prepared for change.

Learning fundamentals makes you less dependent on tools, allowing you to switch stacks without losing your identity as an engineer. That is career freedom.

Skipping Fundamentals Creates Expensive Confusion

I notice a pattern: learning a framework, shipping, praise, then facing challenges when software turns into a real system.

At that point, missing fundamentals lead to confusion, which has a cost.

  • You waste time due to poor hypotheses.
  • You ship fragile fixes due to a misunderstanding of the system.
  • You repeat mistakes because you cannot see the patterns.

I write about that pain in my Death by 1000 Cuts series. Most software misery isn’t due to one catastrophic decision but a long chain of small, poorly understood choices.

Why Fundamentals Make Performance Less Mysterious

A small example makes this concrete.

If you don’t understand algorithmic complexity, you’ll write code that looks fine during development but fails when real users use it.

// Naive lookup: O(n) each time.
function hasUser(users, id) {
    return users.some((u) => u.id === id);
}

// Better lookup: O(1) average case, after you build the index once.
function buildUserIndex(users) {
    return new Map(users.map((u) => [u.id, u]));
}

The first version slows down as your user list grows, while the second invests work upfront for faster lookups later.

Big O notation is a tool; the goal is to develop a mental model of algorithmic costs to make decisions before waking up at 2 AM to fix a real outage.

The same idea applies everywhere:

  • Caching is a fundamental conversation about time, space, and invalidation.
  • Database indexing is a fundamentals conversation about data structures and access patterns.
  • Observability is a fundamentals conversation about evidence, not hope.

Fundamentals Give Teams a Shared Language

When a team lacks fundamentals, conversations go off the rails. People debate tools because they don’t grasp the core concepts to address the real problem.

When a team has fundamentals, conversations sharpen.

  • You can explain trade-offs without strongly opinionated drama.
  • You can review code by reasoning about behavior, not style.
  • You can name risks clearly, then decide what is acceptable.

This is how my technical leadership philosophy shows up in day-to-day engineering work. I lead with integrity, humility, and empathy; fundamentals give me the shared language to make trade-offs clear rather than turn them into heated tooling arguments.

Fundamentals Require Commitment

Learning fundamentals takes time and attention, with an almost endless list of essentials. The key challenge is deciding what to focus on now, what to learn later, and what to ignore.

  • They feel slow because they require thinking, not copying.
  • They reveal your gaps, which can be tough on your ego.
  • They can feel “unproductive” when a business only rewards shipping.
  • They turn into trivia when you gather facts instead of building mental models.

I commit to learning the fundamentals, as they cut rework and firefighting. Building mental models saves time later through fewer outages, rewrites, and development team discussions.

I use a popular product prioritization rubric—Reach, Impact, Confidence, Effort (RICE)—to decide what to learn next.

  • Reach: How often will I use this daily?
  • Impact: If I improve, how much pain will go away?
  • Confidence: How sure am I will use the knowledge soon?
  • Effort: How long to become competent?

I score each category from 1 to 5, then compute:

( \text{score} = (\text{Reach} \times \text{Impact} \times \text{Confidence}) \div \text{Effort} ).

When torn between topics, I choose the higher-scoring one and commit for 2 to 4 weeks.

Common Misconceptions That Waste Years

I see these misconceptions derail people constantly:

  • “Fundamentals are for beginners.” Fundamentals suit those seeking ongoing improvement beyond quick wins.
  • “I can learn fundamentals later.” Later is when your software is messy, and your brain is fried.
  • “Fundamentals are trivia.” Fundamentals are mental models that help predict behavior and failure modes.
  • “Real work is frameworks.” Real work involves solving human problems; frameworks are just tools used along the way.
  • “If it works, it works.” If it works but you don’t understand it, you’re relying on luck.

Who Else Argues For Fundamentals, and Why

This video by Kelsey Hightower emphasizes that learning fundamentals shifts you from being a tool’s prisoner to developing a transferable understanding.


Other talks that support the same thesis from different angles:

I like these talks because they emphasize durable ideas, clear thinking, and principles that transfer across tools, otherwise known as fundamentals.

Tools are temporary, but fundamentals build lasting skills.

Where to Go Next

Begin with your most frequent pain for a structured dive into fundamentals.

Closing

Software fundamentals matter because they reduce the human suffering caused by unreliable, insecure, slow, and confusing software. I discussed this in Death by 1000 Cuts. It’s a mess; people waste time and money on software that fails because teams lack fundamental mental models.

When you learn fundamentals, you get:

  • More confidence during system failures.
  • More options as the industry shifts.
  • Better outcomes for trusted users.

References