The rise of agentic AI and coding assistants

Agentic AI – systems that can perform complex tasks autonomously – has moved from science fiction to production reality. In the developer world, tools like GitHub Copilot harness large language models to generate code, fix bugs and even orchestrate multi-step workflows. Adoption is rapid: Copilot already has 15 million users and 230,000 organizations use Copilot for Business. Benchmark tests show that coding speed can increase by 126% when developers pair with AI coding tools. These numbers capture the momentum behind agentic AI: according to recent reports, 78% of organizations use AI in some form and 85% have adopted agents in at least one workflow.

Why AI won't replace programmers

Despite impressive gains, it is misguided to assume that software engineers are on the verge of extinction. Tools like Copilot excel at generating boilerplate code and suggesting fixes, but they are far from self-sufficient. A Stack Overflow analysis notes that while you can generate a lot of code very quickly, you can't trust what comes out; the odds are "50/50 that the result is completely made up". Generative AI behaves like "an excitable junior engineer who types really fast," the article adds, meaning you still have to understand, test, instrument and retrofit the output to fit your code base. In short, AI can accelerate routine coding tasks, but humans must provide architectural judgement, system design, security review and domain context. Complex work—understanding user requirements, translating business needs into technical solutions, maintaining large sociotechnical systems and collaborating across teams—remains beyond the reach of today's AI.

New roles for developers in an AI-augmented world

The advent of agentic AI does not eliminate the need for engineers; it redefines their roles. As AI handles repetitive tasks, human developers shift toward higher-level responsibilities: crafting prompts, curating training data, reviewing and refining AI-generated code, and focusing on system design and user experience. Recent reports point out that recruiters are already seeking developers who are comfortable working alongside AI tools and know how to prompt agents for better outputs. This means engineers must learn new skills – from prompt engineering and model evaluation to ethical AI and governance – to fully leverage AI's potential.

The bottom line: augmentation, not replacement

The question "Will programmers disappear?" stems from a misunderstanding of what programming entails. Writing syntax is only a fraction of a software engineer's job; the rest involves problem decomposition, communication, collaboration and continuous learning. Agentic AI and coding assistants can boost productivity by more than 100% and free engineers from drudgery, but they cannot make decisions or ensure that code serves the business purpose. In fact, generative AI often produces plausible but incorrect code that must be carefully inspected and integrated. Far from making programmers obsolete, AI is turning them into orchestrators of intelligent tools. Those who embrace this partnership—learning to harness AI's speed while maintaining human oversight—will thrive in the next decade.