In a recent LinkedIn post, 🌀 Luca Rossi discusses how AI is changing engineers’ work and challenging their professional identities. This article covers Rossi’s reflections in that post; it is journalistic reporting, not an article written by Rossi.
“When our work changes, our identity gets challenged too, and engineers take a lot of pride in what they create.”
Rossi distinguishes today’s AI-related shifts from earlier cycles of change in software development. Recalling a friend’s 2018 complaint about the pace of JavaScript framework changes, Rossi jokes that those now seem like “the good old times.” The comparison sets up a more serious concern: in Rossi’s view, AI is affecting engineers at a deeper level than changing tools or frameworks.
Professional identity amid technological change
According to Rossi, engineers’ attachment to the work they create means that changes in how they work can also unsettle how they understand their roles. The post describes conversations with engineers who are struggling with that transition. Rossi does not claim that every engineer responds in the same way, but frames identity as an important part of the adjustment.
Rossi says a newsletter essay lays out principles for navigating these changes, and highlights three of them in the LinkedIn post. The first is to develop a broader sense of professional identity. Rossi uses an image of weight concentrated on a single point breaking through ice to argue that relying on just one role or skill can leave a person more vulnerable. A broader identity, Rossi suggests, can support resilience both personally and in the job market.
Taking an active role in the transition
“Drive the change — even without permission, because it is going to happen across the industry whether you or your manager like it or not.”
Rossi’s second principle emphasizes agency. The post argues that engineers can take part in shaping the adoption of AI at work, even when they lack formal authorization to lead that change. Rossi presents the shift as an industry-wide development, making active engagement preferable to waiting for a manager to initiate it.
That advice also reflects the practical tension in the post: change may feel difficult, but Rossi sees it as underway regardless of individual preference. The recommendation is to engage with the transition and help direct how it unfolds in a team or organization.
Experimenting ahead of the curve
“Be slightly too ambitious with AI — AI is like a bus that keeps moving: if you are behind it you are stuck, while if you are ahead, it eventually reaches you.”
Rossi’s third principle calls for a degree of ambition in experimenting with AI. The moving-bus metaphor encourages engineers to explore the technology before they feel fully prepared, while implying that early efforts can still pay off as the tools and practices evolve.
Rossi links these ideas to a keynote at code.talks, where the post says the same themes would be discussed. Taken together, the principles outline Rossi’s approach: broaden professional identity, participate in change, and engage with AI proactively. The post presents those steps as a way for engineers to meet a transformation that, in Rossi’s assessment, is already reshaping the industry.
📝 About This Content
This article is based on insights shared by 🌀 Luca Rossi on LinkedIn.
📅 Originally posted on November 4, 2026 | View original post on LinkedIn →