“Our Goal Is to Build an Electrical Engineer.” (Davide Asnaghi, Co-Founder & CEO of Diode)

2026-06-02 · Source: The Generalist · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Manufacturing & Industrial · Depth: Intermediate, extended

Summary

Diode, a Brooklyn-based startup founded two years ago, is utilizing AI to modernize printed circuit board (PCB) design and manufacturing in the United States. CEO Davide Asnaghi highlights that PCB design has seen little innovation since the 1980s, contrasting it with Shenzhen's highly automated, efficient production. Diode's ambition is to create an "AWS for electronics," becoming the West's equivalent to Foxconn for the AI era by bringing software development speed to hardware. The company automates schematic design, achieving 90% automation, and layout, currently 40-50% automated internally, using large language models. Diode has secured customers like physical intelligence and Saronic, and partnered with Amfropic to enhance Claude models' electrical engineering capabilities.

Key takeaway

For hardware startups and AI engineers aiming to accelerate product development and reduce prototyping cycles, Diode offers a critical solution. Its AI-powered platform streamlines printed circuit board design and manufacturing in the US, compressing timelines from months to weeks. By automating up to 90% of schematic design, Diode enables software-like iteration speed in hardware, crucial for rapid innovation and onshoring production. Evaluate Diode to enhance your team's efficiency and bring new hardware products to market faster.

Key insights

Diode automates printed circuit board design and manufacturing using AI to accelerate hardware development and onshore production.

Principles

• Co-designing for assembly boosts manufacturing efficiency.
• Incentive alignment drives superior design software.
• AI automation can replicate advanced manufacturing efficiency.

Method

Diode captures specifications, uses AI agents for initial design (90% schematic, 40-50% layout automation), integrates human review, and offers customer confirmation via a platform.

In practice

• Automate library management with LLMs for symbols and datasheets.
• Generate AI-driven reference designs for single components.
• Integrate design language into general LLMs for engineering tasks.

Topics

• Printed Circuit Boards
• AI in Manufacturing
• Hardware Development
• Automation
• Supply Chain Resilience
• Large Language Models
• Electrical Engineering

Best for: Director of AI/ML, Entrepreneur, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Generalist.