Insights
Engineering-focused perspectives
Visions and perspectives about the role of AI in the future of traditional engineering enterprises, with a focus on practical delivery and real-world impact.
The Sea Is Rising — Learn to Swim
Generative AI is shifting the role of engineers from task execution to system direction. Those who can clearly define problems and leverage AI tools will build faster, test earlier, and reduce dependency on traditional development cycles.
From Document Chaos to Structured Intelligence in EPC Projects
EPC projects struggle with fragmented teams, inconsistent standards, and misaligned requirements. An agentic AI approach can centralise requirements, tailor them per discipline, and automate compliance—reducing rework and enabling engineers to focus on engineering.
Why Simpler Agent Architectures Can Win (When the Data Is Right)
In agentic AI systems, performance is driven less by architectural complexity and more by prompt clarity, context management, tool design, and data ingestion quality. A well-structured knowledge base enables reliable outcomes—even with simpler agent architectures.
What Is an AI Agent? A Practical Definition for Engineers
An AI agent is a language model with access to tools. When combined with functions, APIs, and systems, LLMs can execute workflows, retrieve data, and support engineering decisions while keeping humans in control.
AI in Engineering: Finding the Right Balance
AI is neither magic nor useless in engineering. The real value lies in combining deterministic engineering systems with AI orchestration—ensuring safety, reliability, and productivity without compromising technical integrity.