Building AI systems for entire engineering workflows

9547 Collegeview Road is not a mailing address but makes a good navigational reference; or “Continuing Education and Customized Training at Normandale Partnership Center,” near the Japanese Garden;
between Lot 5 and the south lot off 98th, but not well accessible from either.

abstract

Artificial intelligence is rapidly expanding beyond software development into electrical, mechanical, and systems engineering. AI can already generate HDL, create programmatic schematics, produce parametric CAD, run simulations, analyze results, and iterate against defined success criteria. But the most important change is not that AI can perform individual engineering tasks. It is that we can now build systems capable of performing—and continuously improving—entire workflows.

That changes the engineer’s job.

In this talk, Steve Zielinski examines the shift from personally executing every step of the work to designing “the machine that builds the machine”: an engineered environment of agents, tools, structured information, verification methods, feedback loops, and human oversight. Drawing on examples from agentic software development, AI-assisted electrical and mechanical design, and regulated product development, he will show why the loop—not the model—is becoming the true unit of engineering productivity.

For systems engineers, this represents both an opportunity and a responsibility. Someone must define intent, decompose the work, establish interfaces, make context machine-readable, specify completion criteria, manage risk, and determine what evidence is sufficient to trust the result. Those are fundamentally systems-engineering problems.

The future does not eliminate the engineer. It elevates the engineer from operator to architect—from doing every task to building trustworthy systems that can do the work repeatedly, visibly, and at scale.

speaker

Steve Zielinski, CSEP, is Chief Technology Officer of Clairio and a partner at Recursive Awesome, where he focuses on the adoption and responsible use of artificial intelligence in regulated industries. He also serves as the AI/ML Track Leader for the INCOSE Systems Engineering in Healthcare Conference.

Steve has more than 20 years of experience spanning systems, software, hardware, and product development in the medical-device and defense industries. His work sits at the intersection of systems engineering, emerging technology, organizational leadership, and the disciplined development of complex, regulated products.

Steve holds a Bachelor of Arts from the University of St. Thomas, a Bachelor of Electrical Engineering from the University of Minnesota, and a master’s degree in Software Design and Development from the University of St. Thomas. He is a Certified Systems Engineering Professional and is named on six U.S. patents.

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