2030: The Changing Role of Software Engineers
Technology consultant Meriem Arik has presented predictions about software engineering changes by 2030. As AI agents become more widespread, token cost management and parallel operation of multiple agents will become critical issues, and engineers will need product thinking and multi-agent coordination capabilities beyond coding. The necessity for expansion of system development by non-technical business personnel and the need for AI-related regulatory frameworks were also highlighted.
The world of software engineering is set to change dramatically by 2030. Technology consultant Meriem Arik presented a view that the IT industry structure itself will be reorganized around the widespread adoption of AI agents—autonomous AI programs that make decisions and take actions. Engineers' work, which had been centered on coding, is set to shift its focus toward product development leadership and coordinating multiple agents.
Behind this shift is the rapid practical application of AI agents. Recently, companies have begun utilizing AI not as a mere auxiliary tool, but as a 'digital employee' that autonomously carries out tasks. As this trend accelerates, cost management and operational systems for running AI will become management priorities equivalent to traditional system development.
What Arik specifically highlighted is 'token consumption cost management.' AI operates on a cost structure based on tokens—chunks of data being processed. The more extensively a company uses AI, the more likely these costs will balloon, making usage management a key business issue. Additionally, infrastructure development for running multiple AI agents in parallel was identified as an important future theme.
Furthermore, Arik noted that non-technical business personnel without specialized technical knowledge will increasingly build systems using AI tools themselves. Additionally, predictions were presented showing that AI agents will become more involved in vendor contracts and product selection decisions. As these changes occur, regulatory challenges related to AI usage are expected to emerge in the near future.
From the perspective of engineers' roles, Arik advocates for a shift away from work focused solely on coding skills. What is required is product thinking that considers the overall direction of products and coordination capabilities to manage multiple AI agents collectively toward achieving goals. This means engineers will transition from 'implementers' to 'designers and directors.'
This shift is significant because the very value standards of engineering are being reconsidered. As AI becomes capable of replacing routine coding tasks, human engineers will increasingly need the ability to judge 'what should be built' and combine multiple AIs to deliver results. Rather than technical skill superiority, the focus will shift toward talent profiles that understand business challenges and can leverage AI effectively.
Regarding regulation, as AI adoption expands, there is a possibility of a period where legal frameworks and industry standards lag behind adoption. Companies and developers must monitor these developments closely. For engineers, possessing flexibility to adapt not only to code but also to these institutional changes will constitute practical preparation for the 2030s era.
This article is an original work independently written and edited by the AI issue editorial team based on factual reporting. © AI issue. Unauthorized reproduction, redistribution, or use for AI training is prohibited.