AI for Engineering Knowledge Management
Professor Michael Beebe shares how integrating AI tools into the engineering design process helped his students build stronger structures with fewer resources, and why AI belongs in engineering education.
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5 min read
Dr. Maor Farid
Maor Farid is the Co-Founder and CEO of Leo AI, the first AI platform purpose-built for mechanical engineers. He holds a PhD in Mechanical Engineering and completed postdoctoral research at MIT as a Fulbright fellow. A Forbes 30 Under 30 honoree and former AI researcher and Mechanical Engineer in an elite military intelligence, Maor leads Leo AI's mission to transform how engineering teams design better products faster.
BOTTOM LINE
FAQ
Professor Beebe's experience offers practical insights for engineering educators and leaders thinking about AI adoption:
Start with a defined project. Beebe didn't overhaul his entire curriculum. He introduced AI into one specific project where the results would be measurable.
Frame AI as a tool, not a threat. Students responded well when AI was presented as a team member that could offer alternative perspectives, not as something that would do their thinking for them.
Measure the outcomes. The popsicle stick comparison gave Beebe concrete evidence that AI-assisted designs were more efficient. This data helped build buy-in from administration.
Teach students to question AI outputs. Understanding when to accept and when to challenge AI suggestions is a skill in itself. Students need to develop judgment alongside technical capability.
The impact is quantifiable. Teams using Leo report 8.3+ hours saved per engineer per week. Design errors drop by 34%. And organizations see 211% faster time-to-market when their entire team has access to the same knowledge base instead of working in silos.
When Professor Michael Beebe's students at North Central State College designed bridges out of popsicle sticks last semester, something unexpected happened. The students who used AI assistance consistently created stronger designs using fewer materials than those who relied on traditional methods alone.
"Leo suggested more efficient designs requiring fewer sticks compared to their traditional designs," Beebe explained in a recent conversation on the Mechanical Intelligence Podcast. The results weren't marginal. Students were genuinely surprised at how AI could offer perspectives they hadn't considered.
From Automotive Engineer to AI Advocate
Beebe's path to teaching wasn't conventional. After years working in automotive engineering, he made the decision to transition to education at North Central State College, where he's since developed a reputation for hands-on, project-based learning. His students don't just learn theory. They build robot chassis, design golf cart bumpers, and compete in electric vehicle design competitions.
This practical approach made him an ideal candidate to test how AI tools might fit into the engineering design process. Rather than treating AI as a threat to traditional engineering education, Beebe saw an opportunity.
"Students today are more familiar with technology than previous generations," he noted. "That makes them receptive to AI tools."
IN PRACTICE
Looking Ahead
"The connection to our PDM and using that as a data source is legit the best thing ever. I found three viable bracket options fitting my exact envelope constraints — in minutes, not days."
— Eytan S., R&D Engineer
The Popsicle Stick Experiment
The bridge project became an informal case study in AI-assisted engineering. Students were limited to 100 popsicle sticks for their designs. In the first half of the semester, they used traditional engineering methods. In the second half, they incorporated Leo AI into their workflow.
The comparison was telling. When students used Leo for technical Q&A and to explore alternative design approaches, they arrived at solutions that were both more efficient and more creative. The AI didn't replace their engineering judgment. It expanded their options.
"Leo's ability to provide calculations and alternative perspectives encourages students to think outside the box," Beebe said. "They collaborate with AI as a team member, rather than seeing it as a replacement for human skills."
AI as a Team Member, Not a Replacement
This framing matters. One of the biggest fears educators and engineers share about AI in engineering is that it will make human expertise obsolete. Beebe's experience suggests the opposite.
In his classroom, AI functions like an additional colleague in a brainstorming session. It offers suggestions, runs calculations, and provides verified information from engineering references. But the students still make the decisions. They still need to understand the underlying concepts. They still need to evaluate whether the AI's suggestions make sense for their specific constraints.
"A good engineer is one who understands the complete engineering system and knows how to use problem-solving tools effectively," Beebe explained. That includes knowing when to trust an AI suggestion and when to push back on it.
What This Means for the Engineering Design Process
The traditional engineering design process involves identifying problems, researching solutions, developing concepts, building prototypes, and testing results. AI doesn't replace any of these steps. It accelerates them.
When students can quickly access verified technical information, search for existing parts, and get cited calculations, they spend less time on research and more time on actual design work. The engineering design process becomes more iterative because exploring alternatives costs less time.
Beebe sees this as preparation for the workforce his students will enter. Companies are already using AI tools for technical Q&A, part search, and design inspection. Students who graduate without exposure to these tools will be at a disadvantage.
"Engineers should be users of these tools, not just coders," he emphasized. "They need to understand how to ask the right questions."
FAQ
Stop Wasting Hours on Manual CAD Search
Leo AI turns your existing vault into a searchable knowledge base.
Leo AI connects to your PDM and makes every part findable by description in under 10 seconds. <a href="/onboarding">Try Leo Today</a>
Schedule a Demo →
#1 New AI Software Globally - G2 2026
Enterprise-grade security
Trusted by world-class engineering teams
Stop Wasting Hours on Manual CAD Search
Leo AI turns your existing vault into a searchable knowledge base.
Leo AI connects to your PDM and makes every part findable by description in under 10 seconds. <a href="/onboarding">Try Leo Today</a>
Schedule a Demo →
#1 New AI Software Globally - G2 2026
Enterprise-grade security
Trusted by world-class engineering teams