AI-Native Engineering: Why Enterprises Must Rethink Software Development
AI coding assistants have made software development faster, but enterprises will need to rethink more than how developers write code to realise the full potential of artificial intelligence. As AI agents take on increasingly complex engineering tasks, organisations must redesign workflows, rethink quality assurance, establish boundaries for autonomous execution and redefine how they measure productivity.
The shift from AI-assisted coding to AI-native software engineering involves embedding AI across the software development lifecycle (SDLC), from requirements and development to testing and release. However, simply introducing coding assistants into existing workflows may deliver limited returns if teams continue to struggle with fragmented processes, integration delays and repetitive work.
Kanakalata Narayanan, Vice President – Engineering at Ascendion, believes the fundamental change lies in how enterprises organise engineering work. In this conversation with CIOL, she discusses what it takes to scale AI-native engineering, measure its business impact and prepare software engineers for a workplace...
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