Every few months, someone announces that an old way of working is dead. Headlines claim that “vibe coding” is being replaced by “agentic swarms” and that “prompt engineering” is giving way to “context engineering.” While these claims attract attention, the reality is more nuanced. These practices are not vanishing; they are evolving and integrating into larger AI systems.
Vibe coding describes programming as a conversation with AI. You could say, “make this function better” or “help me think through this problem.” The process felt natural and creative. It lowered barriers for beginners, encouraged quick prototyping, and often produced insights that would have been difficult to anticipate.
Prompt engineering extended this conversational spirit. It involved experimenting with phrasing to guide an AI. Context engineering shifts the focus from clever wording to organized input. This involves providing examples, curating data, and setting up the environment so the AI has everything it needs. The shift moves emphasis from individual creativity toward structured frameworks. Human judgment, however, remains essential.
Building on context engineering, agentic swarms coordinate multiple AI agents to accomplish tasks at scale. Imagine a scenario where one agent writes tests while another generates documentation, and a third optimizes the code. A coordinator keeps everything aligned, ensuring the system works smoothly without constant human intervention. Companies favor this approach because it scales, standardizes workflows, and reduces reliance on individual prompting skill.
Even in highly orchestrated systems, humans remain central. People still set goals, resolve misunderstandings, and make creative choices. Conversational exploration remains valuable, and prompt skill still matters inside structured frameworks. Older practices are absorbed and reimagined within larger systems, complementing rather than being replaced by automation.
These benefits come with trade-offs. Vibe coding’s openness encouraged exploration, and prompt tinkering often revealed new ways of thinking about AI. Systematization risks losing those creative sparks. Accessibility is also affected. Conversational AI and prompts were open to anyone curious enough to try. Swarms and context frameworks may demand significant resources, which can limit who gets to participate.
The future likely lies in blending approaches, not replacing them. Picture a development environment where you can brainstorm with an AI conversationally, capture the best experiments, and then scale them through coordinated workflows and orchestrated agents. One agent might refactor code while another checks for edge cases, and a third documents the process for team review. Human creativity, careful phrasing, organized context, and orchestrated swarms could all work together. This combination could define the next generation of AI-assisted development and AI workflows.
Some technologies truly do die. Floppy disks and Flash are gone for good, and organizations can accelerate these transitions when better options emerge. But practices like vibe coding and prompt engineering are not vanishing. They are evolving and being reimagined within larger systems. The real question is not “what is dead?” but “what is changing, and what do we risk losing if we stop practicing it?”
In the end, all these approaches share the same goal: helping people build better software. Declaring things “dead” hides the more interesting story. It is about how methods evolve, combine, and carry forward. Progress rarely erases the past. More often, it transforms it. Mastering AI is less about replacing humans and more about guiding the transition from conversation to orchestration, while still exercising personal direction.
