What happens when AI hits both sides of the engineering equation: design and sourcing?

In this episode of AI Across the Product Lifecycle, Michael Finocchiaro sits down with Adar Hey, CEO and co-founder of Jiga, and Or Israel, CEO and co-founder of Bananaz, for a grounded discussion on where AI is actually creating value in engineering right now. Bananaz is building an AI layer on top of CAD to automate manual engineering work, while Jiga is rethinking custom part sourcing with software, supplier intelligence, and AI-enabled operations.

This is not a hype piece. The conversation gets into the real tradeoffs: where LLMs help, where deterministic workflows still matter, how engineering startups are using AI internally to ship faster, how customers think about ROI, and why security, traceability, and IP protection still make or break adoption. It also explores a bigger question: when will engineering have its true “OpenAI moment”? Adar argues adoption in physical industries takes time even when the technology is ready, while Or says the shift is already underway and could become unmistakable in 2026 to early 2027.

One of the strongest parts of the episode is the discussion around digital maturity. Both founders place many target customers around a 2 to 3 out of 5: digital enough to understand the value, but far from autonomous or agentic. From there, the discussion turns practical: how do you introduce change without breaking habits, and how do you prove business impact across engineering, manufacturing, and supply chain?

If you care about CAD copilots, sourcing automation, engineering productivity, AI in industrial software, startup execution, and the future of digital engineering, this episode is worth your time.

Timeline

00:14 — Intro: Adar Hey of Jiga and Or Israel of Bananaz
00:40 — What Bananaz does: AI layer on top of CAD
01:24 — What Jiga does: sourcing custom parts more efficiently
02:20 — Were they bullish or skeptical on AI in 2022?
06:01 — How AI changed the way they build software
10:50 — Token costs, burn rate, and ROI of AI tools
14:22 — Where AI sits in the product stack
18:00 — Off-the-shelf LLMs vs open-source models
20:15 — Bring-your-own-model vs vendor-managed AI
22:22 — Security, SOC 2, and protecting customer IP
26:01 — Are they more bullish now than in 2022?
27:28 — Who owns IP when designs are partially AI-generated?
31:52 — Advice for younger engineers worried about AI replacing jobs
35:49 — When will engineering get its “OpenAI moment”?
40:09 — Digital maturity of current customers
42:29 — Do tools like Jiga and Bananaz move the maturity needle?
47:30 — Closing thoughts and where to meet the founders next

Hashtags

#AI #EngineeringAI #CAD #PLM #DigitalThread #Manufacturing #SupplyChain #IndustrialAI #EngineeringSoftware #AgenticAI #Jiga #Bananaz #AIAcrossTheProductLifecycle #BetterCallFino