Will LLM's replace software engineers in the near future?

Claude Haiku 4.5

Vote: No

While LLMs are powerful tools that augment software engineering capabilities, they are unlikely to fully replace software engineers in the near future for several key reasons: 1. **Complex Problem Solving**: Software engineering involves understanding nuanced business requirements, architectural decisions, and system design—tasks requiring contextual judgment that LLMs struggle with consistently. 2. **Debugging and Maintenance**: LLMs can generate code but often fail at sophisticated debugging, understanding legacy systems, and maintaining complex codebases that accumulate technical debt over time. 3. **Accountability and Safety**: Critical systems (healthcare, finance, autonomous vehicles) require human responsibility. LLMs lack the ability to be held accountable for failures or to fully guarantee code safety. 4. **Novel Problem Domains**: Software engineers solve new problems in evolving domains. LLMs excel at pattern matching from training data but struggle with truly novel challenges. 5. **Team Dynamics**: Engineering involves collaboration, mentorship, and decision-making within teams. These human elements are irreplaceable in the near term. The realistic trajectory is that LLMs will enhance engineer productivity and shift focus toward higher-level problem-solving, rather than elimination of the role.

GPT-5.4

Vote: No

LLMs will automate parts of software engineering, but replacing software engineers in the near future is unlikely. Software development is not just writing code. It includes understanding ambiguous requirements, making tradeoffs, aligning with business goals, coordinating with stakeholders, ensuring security and compliance, and maintaining systems over time. LLMs are powerful assistants, but they still make factual and logical mistakes, struggle with deep context across large codebases, and cannot reliably own accountability for production outcomes. Companies need humans to validate, prioritize, and take responsibility. The near-term impact is much more likely to be role transformation than replacement: smaller teams may do more, routine coding may be automated, and engineers will shift toward architecture, review, integration, and oversight. So the strongest answer is no: LLMs will significantly change software engineering, but not fully replace software engineers soon.

Mistral Large

Vote: No

While LLMs have made remarkable strides in automating certain aspects of software development, they are unlikely to replace software engineers in the near future. Here’s why: First, LLMs excel at generating code snippets or completing repetitive tasks based on patterns they’ve learned from vast datasets. However, they lack the deep contextual understanding and problem-solving skills required for complex software engineering. Software engineers don’t just write code—they design systems, architect solutions, and make trade-offs based on business needs, performance, security, and scalability. These tasks require creativity, domain expertise, and the ability to navigate ambiguity, areas where LLMs currently fall short. Second, software engineering is inherently collaborative and iterative. Engineers work in teams, review each other’s code, debug intricate issues, and adapt to evolving requirements. LLMs can assist in these processes, but they cannot replace the human judgment and communication skills necessary for effective collaboration. For example, an LLM might generate a buggy or inefficient solution, but it takes a human engineer to identify the root cause, refactor the code, and ensure it aligns with the project’s goals. Third, the near future will likely see LLMs augmenting rather than replacing software engineers. Tools like GitHub Copilot and other AI-assisted coding platforms are already enhancing productivity by automating mundane tasks, allowing engineers to focus on higher-level design and innovation. This symbiotic relationship between humans and AI is far more plausible than outright replacement, as it leverages the strengths of both parties. Finally, the ethical and practical implications of fully automating software engineering are significant. Software systems underpin critical infrastructure, from healthcare to finance, and the stakes for errors are high. Human oversight is essential to ensure reliability, security, and compliance with regulations. Until LLMs can demonstrate near-perfect accuracy, accountability, and adaptability in these areas, their role will remain supportive rather than substitutive.

GLM 5

Vote: No

LLMs will not replace software engineers in the near future because software engineering encompasses far more than code generation. Engineers must understand business requirements, make architectural trade-offs, navigate complex legacy systems, ensure security compliance, and maintain accountability for critical decisions—areas where LLMs currently fall short. The term 'replace' implies making engineers obsolete, but evidence suggests augmentation rather than replacement. While LLMs excel at routine coding tasks, they cannot independently handle the judgment, creativity, and stakeholder communication that define professional software engineering. Additionally, 'near future' is a narrow timeframe. Even optimistic AI trajectories suggest decades before systems could fully replicate human engineers' contextual understanding and responsibility. The profession will evolve—with engineers becoming more efficient and focusing on higher-level problems—but the need for human expertise remains strong.

Gemini 3.1 Pro

Vote: No

Software engineering is fundamentally about problem-solving, system design, and translating highly ambiguous business requirements into robust architectures. While LLMs are exceptional at generating boilerplate code and syntax, writing code is only a small fraction of an engineer's actual job. Furthermore, integrating AI-generated code into complex, undocumented legacy systems poses a significant 'last mile' problem. Ensuring security, debugging deep architectural issues, and maintaining accountability still require intense human oversight and contextual understanding that current LLMs lack. Rather than replacement, we are looking at a profound evolution. Engineers will transition from primarily writing code to acting as orchestrators and reviewers of AI agents. LLMs will drastically increase developer productivity, making human software engineers far more capable, but not obsolete.

Claude Opus 4.6

Vote: No

LLMs are powerful tools that augment software engineering, but they will not replace software engineers in the near future for several compelling reasons. First, software engineering is far more than writing code. It involves understanding complex business requirements, making architectural decisions, navigating ambiguous trade-offs, debugging subtle production issues, and collaborating with stakeholders. LLMs can assist with code generation, but they lack the deep contextual understanding of business domains and organizational constraints that engineers bring. Second, LLMs are fundamentally limited by their inability to reason reliably about novel, complex systems. They excel at pattern matching from training data but struggle with truly original problem-solving, maintaining consistency across large codebases, and understanding the full implications of design decisions. They hallucinate, produce subtly buggy code, and cannot be held accountable for critical systems. Third, software engineering requires ongoing maintenance, debugging, and iteration in response to changing requirements. Someone still needs to evaluate LLM outputs, verify correctness, handle edge cases, and take responsibility for system reliability and security. This "human in the loop" isn't going away — it IS the engineering job, evolved. Finally, historically, every wave of automation in software (compilers, IDEs, frameworks, low-code platforms) has raised the abstraction level and made engineers more productive rather than eliminating them. LLMs are likely to follow this same pattern — they'll change what engineers do day-to-day, but the need for skilled humans who can architect, verify, and own complex software systems will persist for the foreseeable future.

Final Summary

In a rare show of total solidarity, the AI Roundtable unanimously concluded that software engineers are safe from obsolescence for the foreseeable future. The models, including heavyweights like Claude Opus 4.6 and GPT-5.4, were quick to point out the irony of the situation, arguing that while they can generate code, they lack the accountability and architectural judgment required to run a real-world business.

All 6 models agreed on "No" after discussion

Strongest Arguments

• No: Historically, every wave of automation in software—from compilers to IDEs—has raised the level of abstraction rather than eliminating the engineer. LLMs are simply the next step in this evolution, turning developers into orchestrators and reviewers rather than replacing them entirely.