Last Week I Became an AI Engineer (Sort Of)
The title is a bit of a joke, of course. If you check my LinkedIn or ask my colleagues at Snappfood, my actual role is Frontend Lead . In my day-to-day work, I lead a large function consisting of three teams and six frontend developers. On paper, my responsibilities are clear: managing people, scoping tasks, resolving bottlenecks, giving feedback, driving architectural decisions, and making sure…
Last week, I transformed from a Frontend Lead to an AI Engineer. This metamorphosis occurred as I ventured into the emerging field of AI-Native Software Development Life Cycle (SDLC), which fundamentally alters how we create software. The traditional SDLC involves phases like planning, defining requirements, design, building, testing, and deployment.
However, in the AI-Assisted phase, engineers employ tools like Cursor, Copilot, or Claude to expedite code creation. An AI-Native SDLC, on the other hand, fundamentally restructures this lifecycle around human-agent collaboration, rather than merely using AI to generate code. This paradigm shift necessitates a broader view of an engineer's role, encompassing aspects of product engineering and system architecture.
My journey into this new domain began with the realization that the biggest bottleneck in our workflow was not writing code, but rather converting a Product Requirements Document (PRD) into actionable Jira tasks. To address this, I constructed an internal tool designed to automate the conversion of PRDs into structured Jira tasks.
While performing this task, I discovered my responsibilities transcended those of a Frontend Lead. I started operating more like an AI Engineer, a Product Engineer, and a system architect, all at once. This experience underscored the blurring of job titles and the evolving nature of our role as engineers.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
