Use His Hardware Cheat Code

I'm joined by Serge Kadjo, Founder & CEO at Wearer Lab dba Productflo.io, as we explore how AI-powered design tools are revolutionizing hardware development and compressing the medtech innovation cycle.

From African Robotics Dreams to Global Hardware Innovation
→ Serge's journey spans West Africa, military service, and multiple continents (Poland, China, Morocco, France) with exits in smart agriculture and deep tech, culminating in Product Flow's mission to democratize hardware development
→ His multidisciplinary background across IoT systems, BCI neurotechnology (partnered with CERN), and medtech sleep devices informs Product Flow's systems-thinking approach

Haitch: The AI Design Engine Transforming Ideas Into CAD
→ Haitch converts text prompts or engineering drawings into parametric 3D CAD models in minutes, generating complete design briefs with DFM analysis, dimensions, and manufacturing constraints automatically
→ Real application: Serge took a client's screenshot, prompted Haitch to design sliding mechanisms, generated three options with exploded views, and produced manufacturable CAD files conversationally

Product Flow: Breaking Down Engineering Silos
→ Consolidates mechanical files, PCBs, code repositories, and drawings into one version-controlled workspace, enabling 75-80% faster development through unified visibility
→ Generates dependency trees showing how functions, components, and tasks interconnect—critical for complex systems like drug delivery devices with mechanical, electrical, and software components

The AI-Academia Application Gap
→ NVIDIA's ML simulation engines perform FEA 10x faster, yet medtech domain experts remain unaware these tools exist because researchers and practitioners occupy separate worlds
→ Transit/ship testing and EO residuals involve known variables that computational models could simulate, potentially compressing 3-month, $40K validation cycles into days

Security and the Zero-Trust Framework
→ Never trust AI providers even when they claim not to train on your data—design systems assuming they might, especially since legal obligations require permanent data storage
→ Product Flow decoupled the AI engine from collaboration—teams use file sharing without AI, then selectively enable Haitch for generation tasks

Why Hardware Takes 4 Years and $4M
→ Companies spend equal time on every phase instead of using AI to compress the middle 70% of grunt work, preserving human expertise for critical first 10% and final 20%
→ Tools like Haitch for rapid prototyping and computational validation could cut development timelines and costs by 50-60%

Best Quotes:

"Building hardware is more about design system thinking. Break products into functions, tools, and solutions—you're way more able to communicate and collaborate."

"There's a barrier between AI research and real-world application. Folks with domain knowledge don't know how to apply ML. They're not even aware those models exist."

"We're in a wonderful era. The limits are on your imagination. Lower expectations at first, but try it—you'll be surprised."

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Connect:
Serge: https://www.linkedin.com/in/swkkadjo/
Product Flow: https://www.productflo.io
Spencer: https://www.linkedin.com/in/spencer-jones-xo/

Timestamps:
0:00 - Serge's global innovation journey
5:45 - Smart agriculture, BCI/TDCS ventures
14:15 - Product Flow and Haitch introduction
22:05 - Security and zero-trust framework
28:45 - Haitch demo: engineering drawings to CAD
36:20 - Product Flow: version control demo
42:10 - AI-academia gap in medtech
49:00 - Compressing timelines: 4 years to 18 months
54:15 - Computational validation models
1:00:25 - Final thoughts on imagination