Artificial intelligence has dramatically lowered the barrier to software development, making it easier than ever for manufacturers, engineering organizations, and startups to build custom applications. But just because you can build your own software doesn't always mean you should.
In Episode 143 of Stay Sharp in Digital Engineering, co-hosts Juliann Grant and Jonathan Scott welcome back Jonathan Girroir, Technical Evangelist at Tech Soft 3D, for a forward-looking discussion about how AI-assisted coding is reshaping engineering software development. Together they explore the growing "build versus buy" dilemma, why software components are becoming more valuable than ever, and how organizations should think about protecting their intellectual property while embracing modern cloud architectures.
From AI-generated code and engineering toolkits to data hubs, APIs, and digital thread strategies, this episode examines the technology trends that will influence how manufacturers develop, deploy, and manage engineering software over the next decade.
In this episode, you'll learn:
- Why AI-assisted coding is fueling an explosion of engineering software startups
- How manufacturers are building custom applications faster than ever
- When it makes sense to build software—and when buying is the better strategy
- How reusable software components accelerate product development
- Why data sovereignty has become a critical consideration
- The hidden costs of maintaining custom software
- How cloud delivery models and hybrid architectures are changing engineering workflows
- Why APIs and data hubs may become more important than traditional file formats
- The growing role of standards like STEP AP242, QIF, and Universal Scene Description (USD)
- Why connected engineering data is becoming one of manufacturing's greatest competitive advantages
- How digital thread strategies create richer AI training data for future innovation
Key Takeaways
AI isn't replacing engineering software developers—it's making software creation dramatically more accessible. Organizations now have the opportunity to prototype and deploy specialized engineering applications much faster than in the past.
However, successful organizations won't simply build everything themselves. They'll carefully evaluate where commercial software provides mature capabilities and where custom development creates true competitive differentiation.
The conversation also highlights an important shift occurring across manufacturing: engineering data is evolving from isolated files into connected, API-driven data ecosystems. Companies that invest in clean, connected digital thread data today will be better positioned to leverage AI tomorrow.
Whether you're evaluating PLM modernization, developing engineering applications, or planning your organization's AI strategy, this episode offers practical guidance for making smarter technology decisions.
Be sure to subscribe for more conversations on digital engineering, PLM, AI, MBE, digital thread, manufacturing, and engineering technology.
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