Where are we now?

Modern AI systems such as GitHub Copilot, ChatGPT, Amazon CodeWhisperer can:

• Complete code based on a comment or a started line,

• Offer solutions to algorithmic problems,

• Generate boilerplate code and templates,

• Help with documentation and tests. Even today, programmers save hours and days by delegating routine work to AI. But these are assistant tools, not full-fledged developers.

What can AI do and what can't it do?

AI can:

• Generate code based on already known patterns,

• Find and offer optimal (or almost optimal) solutions for typical tasks,

• Explain, correct, and refactor existing code.

But it can’t yet:

• Design complex architectures from scratch,

• Make meaningful technical decisions at the product level,

• Be responsible for the security, responsibility, and ethics of decisions,

• Fully debug or take into account the business context.

AI does not yet have a real understanding of code — it analyzes statistics, not meaning. Even advanced models are just very smart auto-completions.

Will manual programming die?

Most likely — no, but it will change a lot:

1. The role of the programmer will change Programmers will write code “manually” less, but will set tasks, evaluate the result, integrate, test, and think architecturally more. This will be something like an “AI code engineer”.

2. The threshold of responsibility will increase Automation of routine tasks will free up time for more complex work: design, security, scalability, interaction with other systems. 3. Code will become more declarative Instead of “how to do it,” programmers will increasingly write “what should be done.” This is similar to working with SQL, Terraform, Docker, or even no-code platforms.

4. New professions will appear Prompt engineer, AI code reviewer, specialist in training models for internal development.

Who should be worried?

Those at risk are those who do routine work and do not delve into understanding the architecture and context: juniors, coders, freelancers who are not striving for development. Those who benefit are those who understand the system as a whole, can think in product terms, manage a team, teach others, and adapt to new tools.

What's next? AI will probably write up to 80–90% of the code for typical tasks. But human control, responsibility, and creativity will remain critically important. We will create not just code, but systems that create other systems. The programmer of the future is an architect of ideas, a navigator of complexity, a conductor of the AI orchestra.

Code will not die — it will evolve. Programmers will not disappear — they will become those who teach and guide AI so that it makes code faster, more accurately and more safely. AI is not the end of programming. It is a new round of its development. And if you learn, adapt and develop — you have a great future.