“Code was never the hard part” is an insult to all programmers
“Code was never the hard part” has become a flashpoint as AI tools increasingly generate working code, raising fears that programming skill is being devalued. Commenters argue over whether typing code was ever the main bottleneck versus harder aspects like understanding requirements, system design, maintenance, and navigating organizational politics. Many see LLMs as amplifying existing tensions: they can speed up routine coding, but they also risk a flood of low-quality “vibe code,” making human judgment, architecture, and long-term responsibility for software more critical than ever.
Meaning of “code was never the hard part”
- Many read it as: “typing code is not the bottleneck” once you’re experienced; the hard parts are deciding what to build, how to design it, and fitting it into messy organizations.
- Others say this phrasing is misleading or insulting because it sounds like “coding is easy” and erases genuine technical difficulty, especially in non‑trivial domains.
Is coding hard?
- Several argue basic coding is intrinsically hard for many people (CS dropout rates, fizzbuzz failures, years of practice required).
- Others say that, compared with requirements, architecture, communication, and politics, the act of implementing code is often the easiest piece of the overall job.
- Distinction is often drawn between “making something run” and writing performant, correct, maintainable, evolvable code; the latter is still seen as hard.
Coding vs. programming / engineering
- Recurrent theme: “coding” = entering instructions; “programming/engineering” = problem solving, design, modeling domains, integrating systems, operating and evolving them.
- Many say good engineers inevitably wear “invisible hats”: requirements refinement, architecture, performance, security, compliance, operations.
AI/LLMs and their impact
- Some claim LLMs have turned much of everyday coding into low‑skill “line cook/burger flipping” work; the real value moves up to design, orchestration, and specification.
- Others report LLMs generate sloppier, buggy, or unsafe code, especially in complex systems (distributed, regulated, performance‑critical), increasing review and maintenance load.
- Shared view: LLMs help with boilerplate and “typing”, but do not replace deep understanding, long‑term maintenance, or correct high‑level decisions.
Product, requirements, and organizations
- Many say real bottlenecks are unclear requirements, shifting priorities, and cross‑functional alignment; “coding days with no meetings” are rare and cherished.
- Disagreement on who should own user understanding: some argue engineers must be involved early; others think product/PM should shield engineers and handle research.
Quality, maintenance, and regulation
- Maintenance and debugging are repeatedly cited as the hardest, most time‑consuming parts; much existing code “wouldn’t pass a basic audit”.
- In regulated or safety‑critical domains, process and documentation can dwarf the code itself, but the code still must be correct and is hard to change safely.
Labor, status, and identity
- Several see “code was never the hard part” as a coping narrative in the face of automation anxiety.
- Others note that high salaries reflected scarcity and leverage, not just difficulty, and that many non‑coding skills (product, management) are also hard but less visibly valued.