Over the past two years, large language models (LLM) like GPT-5, Claude, and Code Llama have gone beyond being just code completion tools and have become full-fledged participants in the development process. While a programmer used to spend a lot of time designing the architecture, writing boilerplate code, and documentation, today AI can take on a significant part of these tasks.

1. Code completion has become smarter Classic IDE plugins like IntelliSense or TabNine were already able to suggest code options, but LLM models have gone further — they analyze the context of the entire project, take into account your previous decisions, and even suggest optimizations that you yourself might not have noticed. For example, when writing an API endpoint, AI can not only generate a handler, but also suggest unit tests, database migrations, and security recommendations.

2. On-demand architecture Today, you can describe a task in a couple of paragraphs — and get an architecture diagram: microservices, interactions between them, message queues, database schemes. This does not mean that architects are no longer needed, but now they can spend time not on routine drawing of diagrams, but on checking and improving the proposed solution.

3. Debugging and code review with AI AI can act as “second eyes” for your code: find bugs, point out potential memory leaks, offer more readable constructs. Moreover, it does not just issue a list of comments, but accompanies them with explanations, links to official documentation and examples of corrections.

4. Automation of documentation Previously, documentation was a “pain point” for developers - few people like to write it. LLM can automatically generate README, API specs, code comments and even usage examples, synchronizing them with the current state of the project.

5. Programmer as an architect of ideas The main change is that the role of the developer shifts from “code writer” to “solution curator”. Now the programmer's task is to correctly describe the requirements, set constraints and check the result, and not write each line manually.

LLM models will not take away the work of programmers, but they will take away the routine. Having mastered working with AI, you can speed up development by 2-3 times and focus on creative and strategic tasks. Those who learn to effectively “talk” to models will benefit.