Skills for the future software profession: beyond agentic AI!

Researchers and industry practitioners from roundtables in New York and Singapore (2026) identified critical skills for software engineers in an AI-agentic future, with verification and validation emerging as increasingly essential as coding agents handle more implementation tasks. The findings highlight a fundamental shift in software development requiring developers to focus less on coding and more on quality assurance and validation of agent-generated code.

The rapid advancement of AI coding agents fundamentally reshapes the software engineering profession, moving developers away from hands-on implementation toward supervisory and validation roles. This transition stems from the maturation of large language models capable of generating functional code, automating routine programming tasks that dominated traditional development workflows. The roundtable discussions in major tech hubs underscore that the industry recognizes this inflection point and is actively strategizing workforce adaptation.

Historically, software engineers built expertise through coding practice and implementation mastery. However, as agents handle increasingly complex implementation tasks, the bottleneck shifts upstream to specification and validation. This mirrors previous technological disruptions where automation elevated human roles to higher-level oversight rather than elimination. The emphasis on verification and validation suggests developers must develop deeper skills in testing frameworks, formal methods, security analysis, and code review methodologies.

For the talent market, this reshapes training programs and hiring practices. Educational institutions must pivot curricula away from language syntax mastery toward critical thinking about code correctness, security implications, and system architecture. Companies investing in developer training and retention will gain competitive advantages as the talent pool struggles to adapt. Early-career engineers must actively develop verification skills to remain relevant.

Looking forward, the software engineering profession likely bifurcates: senior architects and verification specialists command premium roles, while routine implementation work consolidates into AI tools. Organizations will measure developer productivity through validation efficiency rather than lines of code. The profession's long-term health depends on educators and industry leaders collaborating to develop robust training pathways that position developers as quality gatekeepers in agentic systems.

• →Verification and validation skills are becoming core competencies as AI agents automate code implementation
• →Software engineering roles are shifting from hands-on coding to supervisory oversight and quality assurance
• →Educational institutions must redesign curricula to emphasize testing, security analysis, and code review over syntax mastery
• →The talent market will reward developers who specialize in validation frameworks and formal verification methods
• →Professional bifurcation likely creates premium opportunities for senior architects while routine implementation consolidates into tooling