Industry Insights 12 min read

Why Saying “Coding Is Easy” Insults Every Programmer

The article argues that coding itself is not the hardest part of software work; the real challenges lie in understanding what to build, communicating with stakeholders, navigating AI‑driven change, and balancing craftsmanship with product insight, all of which explain why the industry remains demanding and well‑paid.

AI Engineer Programming
AI Engineer Programming
AI Engineer Programming
Why Saying “Coding Is Easy” Insults Every Programmer

IF EASY

If coding were truly easy, why does programmer demand stay strong, salaries remain high, and burnout persist even before AI can generate thousands of lines of PRs? The myth of the 10× “rockstar” coder and LeetCode‑driven interviews persists, yet junior engineers cannot simply churn out useful software without deeper context.

Why do we have massive books like Clean Code , The Pragmatic Programmer , and Structure and Interpretation of Computer Programs , or even whole university degrees centered on programming? These works exist because mastering code is a craft that requires technique, patience, and experience.

Figures such as John Carmack and Fabrice Bellard are celebrated not merely for timing but for genuine genius.

WHAT TO BUILD

If deciding what to build is the hard part, why do many product managers appear clueless, lack rigorous interview processes, and earn less than developers? Why are market researchers, usability experts, and (honestly) customer success teams often ignored, while business analysts are dismissed as paperwork‑only staff?

When sales promise new features that match real, paying customer needs, developers become frustrated because the true demand has finally been articulated.

NO MEDIAN

Most software work involves talking to stakeholders, clarifying priorities, and aligning expectations. Few programmers actually engage with stakeholders; only freelancers or founders tend to do so. Clear priority means a direct “do this” order without frequent pivots.

Some developers claim they solve customer problems while obsessing over memory safety, DRY principles, or fictional user personas, mistaking affordance for a trivial allowance.

Others treat software as pure theory, insisting every commit tells a story. Uploading a single PHP file to solve a client issue is portrayed as a grave sin.

WHAT MATTERS

Talking to users, empathizing with their experience, and solving real problems are crucial for software success. Writing good code remains a valuable skill that will continue to matter.

Both deep understanding of the system being built and clear reasoning about why it is being built are essential.

Declaring code easy or elevating it to untouchable art are both forms of burying one’s head in the sand.

CONSTANTS

Software will become increasingly complex and will always need maintenance: bit rot and entropy are inevitable. Users always want more for less, yet they struggle to articulate their needs, creating a gap between customers (who pay) and users (who use).

New buzzwords will keep emerging; trends like VR will rise and fall.

CHANGING

Programmers have always disrupted their field: punch cards are gone, assembly and COBOL are rare, and decades of C/C++ memory‑bug experience are now worth little in the Rust, Go, Python, and JavaScript era.

The author reminisces about Valgrind, mysql_real_escape_string(), and legacy tech still running in cafés, illustrating how old tools persist even as they become obsolete.

FLOURISH

Accept change, stay curious yet critical, and distinguish hype from genuinely useful advances. Recognize that the finish line moves as technology, economics, and society evolve.

Senior developers should broaden their perspective beyond deep technical work to user experience, customer interviews, and business strategy. Junior developers should strengthen fundamentals—pointers, recursion, memory hierarchy, networking, HTTP—even if they work on WordPress plugins.

Suggested reading list (titles only, URLs provided as plain text):

Structure and Interpretation of Computer Programs – https://en.wikipedia.org/wiki/Structure_and_Interpretation_of_Computer_Programs

Cracking the Coding Interview – https://www.crackingthecodinginterview.com/

The Mythical Man‑Month – https://en.wikipedia.org/wiki/The_Mythical_Man-Month

Working Backwards – https://www.goodreads.com/book/show/53138083-working-backwards

Team Topologies – https://teamtopologies.com/book

7 Powers – https://7powers.com/

The Soul of a New Machine – https://en.wikipedia.org/wiki/The_Soul_of_a_New_Machine

Obviously Awesome – https://www.aprildunford.com/books

The Design of Everyday Things – https://en.wikipedia.org/wiki/The_Design_of_Everyday_Things

Don’t Make Me Think – https://en.wikipedia.org/wiki/Don%27t_Make_Me_Think

Continuous Discovery Habits – https://www.goodreads.com/book/show/58046715-continuous-discovery-habits

The Mom Test – https://www.momtestbook.com/

THE END

Never outsource your understanding, judgment, empathy, or taste to AI. Keep responsibility for your code, even if AI assists.

Related URLs (provided for reference):

https://blog.senko.net/your-code-is-your-responsibility-even-if-ai-wrote-it

https://gruhn.me/blog/2026-08-03/

https://news.ycombinator.com/item?id=49222189

https://lobste.rs/s/iixlsm/code_was_never_hard_part_is_insult_all

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programmingSoftware Engineeringsoftware developmentproduct managementAI impactindustry insight
AI Engineer Programming
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AI Engineer Programming

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