Opinion: Engineers are working in the same way as 20 years ago
- Ofir Raninian
- Feb 7
- 2 min read
Alone, Inefficient with average results.
Are Engineers Stuck in the Past?
Even though technology has advanced a lot, the way engineers work hasn’t changed much in 20 years. Many still work in solo efforts, with few check-ins and little review until big project milestones. This way of working can be slow and lead to only average results. Without regular feedback, small daily choices go unchecked and can turn into big problems that are hard to fix later. Adding to this challenge is the overload of information available today. Engineers have access to more data than ever before. But with so much to sift through, it’s nearly impossible for anyone to stay fully up-to-date. This constant juggling of new information, while trying to meet tight deadlines, often results in engineers making decisions based on only part of the picture. Every decision, whether it’s a small tweak or a major design change, impacts the project. But is it realistic to expect engineers to handle all these challenges by themselves?
A New Partner for Engineers: GenAI as an Engineering Assistant
Imagine if engineers had an AI agent working alongside them—a virtual partner that could provide real-time feedback, check decisions, and handle routine tasks. This wouldn’t replace the engineer but rather support them, giving quick insights and helping avoid costly mistakes. Engineers could focus on their expertise and rely on the AI to help with repetitive work and data reviews. This AI agent would be more than just a tool; it would be a trusted partner. Engineers could feel supported, knowing they have an unbiased advisor to streamline workflows and make information more manageable.
Why Aren't These Tools Trusted Yet?
So, why aren’t these AI tools widely adopted by engineers yet? One reason is the low rate of adoption due to hesitations about trusting non-human agents. Trust takes time to build, and many current tools still lack the seamless user experience engineers expect. For AI to gain full acceptance, it must be 100% reliable, with no bias or errors. Until these tools meet those standards, engineers remain cautious about integrating them into their workflows.
Deep technology, Generative AI, Overcome top challenges
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