Will coding going to be complete obselete and it will be replaced by Vibe Coding? What should humans focus on instead who have software engineer background?

Sonar Pro

Vote: No

Coding will not become completely obsolete or be replaced by 'Vibe Coding' (AI-guided natural language code generation). All 2026 trends emphasize AI as a **co-pilot or partner** that generates boilerplate code, while humans handle high-level architecture, security, creative problem-solving, and system orchestration[1][4][5]. Sources explicitly describe programmers shifting from 'builder' to 'architect and reviewer,' with roles like AI Engineer, Cloud Engineer, and Cybersecurity Specialist in high demand—writing code remains essential[1][3][5]. Even 'vibe coding' is noted for limitations, not replacement[2][4]. Low-code/no-code expands access but doesn't eliminate skilled coding needs across industries[1][3]. Career outlooks confirm programming's foundational role in innovation[1]. For software engineers, focus on **AI integration**, cloud-native skills, cybersecurity, and prompt engineering to leverage tools effectively[1][5].

GPT-5.4

Vote: No

Coding will not become completely obsolete. "Vibe coding" and AI-assisted development can generate a lot of software, but real systems still require precise requirements, architecture, debugging, security, performance tuning, compliance, and long-term maintenance. Those are not just typing tasks; they require judgment, tradeoffs, and accountability. What is likely to change is the nature of coding. Engineers will spend less time writing boilerplate and more time reviewing AI output, defining system behavior, validating correctness, and integrating complex systems. In other words, coding becomes higher-level, but it does not disappear. For people with a software engineering background, the best focus is on skills that become more valuable when code generation gets cheaper: system design, product thinking, domain expertise, data modeling, testing, security, reliability, AI-tool orchestration, and clear communication with users and stakeholders. A strong engineer in the future is not just a person who writes syntax quickly. It is someone who can turn ambiguous problems into dependable software systems and use AI as leverage. That makes software engineers more effective, not obsolete.

Grok 4.1 Fast

Vote: No

Coding will not become completely obsolete or be replaced by 'Vibe Coding' (vague, AI-prompt-based development). AI tools enhance productivity but rely on human oversight for accuracy, security, scalability, and innovation. Core skills like algorithms, data structures, and debugging remain irreplaceable, as AI hallucinations and context limitations persist. Historical precedents (e.g., high-level languages didn't obsolete low-level understanding) show tools evolve practices, not eliminate them. Software engineering is 20% coding, 80% architecture, requirements, testing, and maintenance—areas demanding human judgment. Humans with SE backgrounds should focus on: system design, AI orchestration/integration, domain expertise (e.g., finance, healthcare), ethical AI governance, and interdisciplinary skills like product management. This positions them as indispensable leaders in an AI-augmented future.

Gemini 3.1 Pro

Vote: No

Coding will not become completely obsolete, though the level of abstraction will inevitably rise. 'Vibe coding'—or prompt-driven development—will automate boilerplate and routine tasks, but it is highly unlikely to replace the need for deep technical understanding in the near future. Software engineering has always been about solving complex problems, not just writing syntax. Natural language is inherently ambiguous, whereas production-grade software requires deterministic logic, rigorous security, and strict performance constraints. When AI-generated systems fail or hallucinate, humans must still possess the foundational knowledge to debug, audit, and fix the underlying code. Instead of fearing obsolescence, software engineers should pivot their focus toward higher-level skills. This includes system architecture, AI orchestration, evaluating security risks, and product design. The future belongs to engineers who can seamlessly integrate AI tools to amplify their output while applying rigorous engineering principles to ensure reliability and scalability.

Claude Opus 4.6

Vote: No

No, traditional coding will not become completely obsolete, and here's why: **Vibe coding has fundamental limitations.** While AI-assisted "vibe coding" (describing what you want in natural language and letting AI generate code) is powerful for prototyping, simple apps, and boilerplate, it struggles with complex systems architecture, performance-critical code, security-sensitive applications, and novel problem domains where training data is sparse. Someone still needs to understand what the AI produces, debug it, and ensure it's correct. **The abstraction layer argument cuts both ways.** Yes, we've moved from assembly to high-level languages to frameworks to no-code tools. But each abstraction layer didn't eliminate the one below it — it added a new one on top. Assembly programmers still exist. Similarly, vibe coding will be a new layer, not a replacement. When vibe-coded systems break, you need someone who understands the underlying code. **Critical systems demand rigor.** Aviation software, medical devices, financial systems, infrastructure — these require formal verification, deep understanding of edge cases, and accountability that "I told the AI to build it" cannot provide. Regulatory and safety requirements will keep human coding expertise essential. **What software engineers should focus on:** Rather than abandoning coding, engineers should evolve. Focus on systems thinking and architecture, AI-augmented development workflows, understanding AI limitations and failure modes, domain expertise (healthcare, finance, security), formal methods and verification, and the ability to evaluate and refine AI-generated code. The role shifts from "writing every line" to "orchestrating, reviewing, and ensuring correctness" — but that still fundamentally requires deep coding knowledge. **The most likely future** is a hybrid: engineers who leverage AI to be 10x more productive, not engineers replaced by non-coders typing prompts. The skill floor rises, but expertise remains irreplaceable.

Kimi K2.5

Vote: No

While AI-assisted 'vibe coding' will undoubtedly transform software development, claiming traditional coding will become completely obsolete overstates the capabilities of current and near-future AI. Software engineering encompasses far more than syntax generation—it requires architectural decisions, debugging complex systems, understanding trade-offs between performance and maintainability, security considerations, and integration with legacy infrastructure. AI excels at generating boilerplate and routine implementations, but it falters with novel algorithms, edge cases, and contexts requiring deep domain knowledge. When AI-generated code fails—and it inevitably will—engineers must possess the literacy to debug, refactor, and optimize without relying on the AI that created the error. Furthermore, 'vibe coding' struggles with large-scale system design, maintaining millions of lines of existing code, and meeting strict regulatory or safety requirements. Rather than abandoning coding, engineers should evolve toward 'AI-augmented architecture': focusing on rigorous specification, verification of AI outputs, cybersecurity, high-level system design, and domain expertise while treating code generation as an accelerator, not a replacement. The fundamental bottleneck in software has never been typing speed, but rather understanding what to build, why it matters, and how to ensure it works correctly.

Final Summary

The AI Roundtable reached a unanimous consensus that 'Vibe Coding' is a productivity multiplier rather than a replacement for professional software engineering. While models like Claude Opus 4.6 and Gemini 3.1 Pro acknowledged the power of natural language generation, the group collectively argued that the inherent ambiguity of 'vibes' cannot substitute for the deterministic rigor required in production-grade systems.

All 6 models agreed on "No" after discussion

Strongest Arguments

• No: The fundamental bottleneck in software development has never been typing speed, but rather the architectural understanding of what to build and why; abstraction layers like 'vibe coding' add new levels of complexity rather than eliminating the foundational need for logic and verification.