Why programming fundamentals matter more than ever in the age of AI

AI coding tools can generate a lot of code very quickly, but the quality of such code can vary wildly. We need people who can actually read and write code to guide, critique and question the LLMs, helping to guard against insecure, inflexible, hard to maintain and untestable code.

Understanding concepts such as variables, data structures, control flow, exception handling, and modularisation will help teams  recognise the results of questionable decisions and debug problems.

StayAhead coding courses cover core programming concepts across languages including Python, Java and JavaScript, helping learners build the technical foundations needed to understand and assess code. AI changes how code is produced; it does not remove the need to understand what that code is doing.

What AI tools get wrong without a human who understands the fundamentals

The recent StayAhead webinar ‘Coding with AI: Why the fundamentals still matter’ demonstrated the problem using a deliberately simple Java task. The AI was asked to create an object-oriented program that calculated measurements for a circle from its radius. The resulting code worked and produced the expected output.

For a novice developer, that might have been enough. Closer examination by an experienced programmer revealed a different picture.

The AI had made the Circle class final without being asked. When challenged, it claimed this made instances of the class immutable and thread-safe, neither of which is true. Other decisions introduced assumptions about business rules that had never been specified.

Most revealingly, questioning one part of the solution prompted the AI to change its original code without being asked to do so. The first answer had looked convincing and had worked, yet the tool itself was willing to revise it once challenged.

This is why AI-assisted development still requires low-level knowledge. Generating working code and understanding whether it represents a good solution are very different skills.

Why learn to code when AI can write it for you?

Learning to code gives you the knowledge needed to direct AI effectively and judge what it produces.

AI-generated code does not always fail obviously. A program might compile and return the expected result yet contain poor design decisions that create problems later, as with the circle example. Someone who lacks the underlying knowledge may have little reason to question a plausible-looking solution.

Developers with stronger foundations are in a different position. They understand what the code is attempting to achieve and recognise when a particular approach deserves closer inspection. AI then becomes a tool they supervise rather than an authority they follow.

The webinar compared this relationship with delegating work to a junior developer. Delegation may increase productivity, but responsibility remains with the person reviewing the work. AI-assisted coding creates a similar requirement for scrutiny.

That scrutiny extends beyond testing. Unit tests are important, but they do not necessarily reveal every questionable design decision.

What are programming fundamentals?

Programming fundamentals are the concepts at the core of every program regardless of the particular language being used.

Variables provide a way to store and later work with data.  Data structures organise data so it can be processed effectively. Control flow determines which instructions execute under different conditions. Exception handling enables a program to recover from problems, and modularisation is the organising of code into maintainable, substitutable, and testable chunks.

These concepts transfer between programming languages. Syntax changes, but understanding how data moves through a program or why a particular condition produces a particular result remain the same.

An understanding of these concepts is crucial when working with AI. If an AI tool generates an unfamiliar piece of code, someone with solid programming fundamentals has a basis for interrogating it. They are better equipped to ask why an approach was chosen and assess whether the explanation makes sense.

This does not mean beginners need to master computer science before they start building useful software. Fundamentals are learned progressively through study and practical experience. StayAhead's Coding courses provide structured routes into these skills across different programming languages.

AI itself may also support that learning. AI can be used to explain unfamiliar generated code rather than simply accepting it. When utilised this way, the tool becomes part of the learning process instead of a shortcut around it.

Is learning to code still worth it?

Yes. Learning to code remains worthwhile because using AI effectively still requires people who understand the software it produces.

What is changing is the way coding skills are applied. Writing every line manually may become less central to some development workflows as AI takes on more routine generation. The developer's ability to review that output and identify problems therefore becomes increasingly important.

For people entering the profession, this makes skipping the fundamentals particularly risky. Producing software quickly with AI may create the impression of competence without developing the understanding needed when the generated solution does not work or makes an assumption the user did not intend.

Experienced developers face a related challenge. AI offers genuine opportunities to work more efficiently, but those gains depend on maintaining the judgement required to question its output. The stronger the underlying knowledge, the easier it is to recognise where automation deserves trust and where closer examination is needed.

The question is therefore becoming less about whether developers should learn coding or use AI. Modern development increasingly requires both.

StayAhead's Coding with AI course explores how developers can use generative tools alongside the technical judgement needed to evaluate their output. While our wider coding courses help learners build core programming knowledge across languages including Python, Java and JavaScript & TypeScript. Together, these learning options can help teams develop the coding foundations needed to understand code, then apply that knowledge when reviewing and working with AI-generated output.

FAQs

Why learn to code if AI can generate code?

Learning to code allows you to understand and evaluate what AI generates. Without that knowledge, it is difficult to identify subtle errors or challenge decisions that look plausible but are inappropriate for the project. Coding knowledge turns AI from something you depend on into a tool you are equipped to supervise.

Should I learn to code in 2026?

Yes. AI is changing development workflows, but understanding programming remains extremely valuable. Beginners should focus on transferable concepts rather than treating the ability to reproduce syntax from memory as the main measure of coding skill.

Is learning to code worth it for a career in technology?

Learning to code is crucial for careers that involve building or maintaining software. AI tools are altering some entry-level tasks, but they also increase the importance of being able to assess generated code and understand why it works. Programming knowledge provides the foundation for developing those skills.

Build strong coding fundamentals with StayAhead.