A software engineer with over 15 years of experience at JPMorgan Chase has shared personal observations on how artificial intelligence is fundamentally changing software development. While the engineer notes that AI adoption varies across the large bank and that guardrails are in place, the overall impact is significant. AI tools have enabled the engineer to accomplish tasks that were previously difficult, especially in unfamiliar areas like infrastructure automation.
Despite the benefits, measuring the return on investment (ROI) for AI in engineering remains challenging. It is unclear whether AI-driven work is more cost-effective or faster compared to traditional methods, and experiments comparing different AI model sizes and costs have yet to be conducted. The engineer highlights the emergence of smaller, more affordable AI models, predicting that inference costs could soon become negligible, potentially leading to automation beyond coding.
The rapid evolution of AI models means that practices and capabilities change quickly, sometimes rendering previous approaches obsolete. The engineer admits that AI now codes faster and better than they can, marking a significant shift after years of honing coding skills. This change has altered how they learn new technologies, moving away from building code to understand concepts toward relying on AI-generated solutions.
There is concern about the potential decline in deep understanding of code and the cognitive demands of managing multiple tasks simultaneously, as AI encourages parallel workflows. However, the engineer remains optimistic about the profession’s future, emphasizing that software development extends beyond coding. Strong communication, leadership, and well-rounded skills remain essential, especially as AI raises the baseline for programming capabilities.
The engineer also warns that AI may replace many entry-level programming roles, making self-driven learning and skill development more critical than ever. They advocate for a broad education that includes both technical and non-technical disciplines to prepare for the evolving landscape.
This perspective underscores a broader industry trend where AI is transforming software development, challenging traditional roles, and requiring professionals to adapt their skills and approaches.