Why Companies Are Quietly Rehiring Software Engineers...

2026-07-22 · Source: Modern Software Engineering · Field: Technology & Digital — Software Development & Engineering, Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, long

Summary

The narrative that companies are rehiring software engineers after attempting to replace them with AI is largely a myth, according to an analysis of current evidence. While popular anecdotes like Cler (customer service) and IBM (HR) are often cited, they do not pertain to software development. A randomized controlled trial by MER Meta in July 2025 found that 16 experienced open-source developers were 19% slower when using modern AI tools, despite perceiving a 20% speed increase. The article emphasizes that the "hard part" of software engineering involves specification, design, and testing, not merely code generation. AI-generated code contributes to technical debt, with duplicated code increasing from 8% to over 12%, and 27% of snippets containing security weaknesses. Furthermore, iterative AI refinement of secure code increased critical vulnerabilities by nearly 40%. The job market is shifting, with "programmer" roles declining by a quarter, while "software developer" roles, focused on engineering judgment, continue to grow.

Key takeaway

For software engineers aiming to remain valuable, focus on mastering the non-coding aspects of development. Prioritize understanding problems, designing robust solutions, thorough testing, and taking full responsibility for outcomes. Do not compete with AI on typing speed; instead, cultivate the critical judgment and engineering practices that machines cannot replicate. This shift ensures your expertise remains indispensable as AI tools become more prevalent.

Key insights

The core of software engineering is human judgment and design, not code generation, which AI excels at but often exacerbates technical debt.

Principles

• Software's hard part is design, not typing.
• AI amplifies existing engineering practices.
• Human judgment is critical for secure code.

In practice

• Prioritize design and problem understanding.
• Scrutinize AI-generated code for security.
• Emphasize engineering judgment over typing speed.

Topics

• AI Coding Assistants
• Software Engineering
• Developer Productivity
• Technical Debt
• Code Security
• Job Market Analysis

Best for: CTO, VP of Engineering/Data, AI Architect, Software Engineer, AI Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Modern Software Engineering.