YC Root Access

How Diode Is 10x-ing Hardware Design

Davide Asnaghi and Lenny Khazan started Diode Computers with a question: why does hardware design still move so slowly? Drawing on their backgrounds in software and electrical engineering, they set out to reframe circuit board design as a software problem. One that AI could help solve. They went from building a tool to catch design mistakes to creating an end-to-end AI-powered system that generates production-ready boards. Along the way, they discovered that most companies didn’t want a better tool — they wanted the whole solution. That insight led to rapid growth, real customers, and over 100 boards designed in just a few months, all by a two-person team. Today, they announced $11.4M in Series A funding led by a16z. This is the story of two engineers trying to make hardware move at software speed, and the infrastructure making it possible. Learn more about Diode Computers at https://diode.computer. Apply to Y Combinator: https://ycombinator.com/apply Chapters: 00:22 - What is Diode? 00:31 - Customer Base and Early Growth 00:51 - The Origin Story 02:46 - Initial Challenges and Pivot 04:01 - Finding the Right Problem 05:02 - First Successful Deal 05:29 - Realization and Validation 06:40 - Reframing PCB Design as a Software Problem 11:28 - Technical Choices and Challenges 11:56 - Innovative Language Design 12:31 - Infrastructure and Security 13:33 - Future Prospects 14:21 - Recruitment and Team Building

DHDiana HuhostDADavide AsnaghiguestLKLenny Khazanguest

Jul 23, 2025·15m·Watch on YouTube ↗

📖 CHAPTERS

1. 1
   0:22 – 0:31

   Diode’s mission: AI that automates PCB (circuit board) design

   Diana Hu opens by introducing Diode’s founders and their rapid traction post–YC, including a newly closed Series A. The founders frame Diode as an AI-enabled PCB design shop that automates board design end-to-end.

2. 2
   0:31 – 0:51

   Who’s buying: Fortune 100 + frontier hardware startups

   The team describes a surprisingly strong customer roster for such an early company. They serve both large enterprises and ambitious hardware startups that need PCB design capacity quickly.

3. 3
   0:51 – 2:46

   Origin story: software engineer meets hardware pain firsthand

   Lenny recounts moving from software into hardware during COVID, mentored by Davide, and discovering the pace and tooling gap in electronics. They later worked together again and saw repeated “silly mistakes” in boards despite strong teams.

4. 4
   2:46 – 4:01

   Initial YC thesis: “compiler-like” verification for PCB mistakes

   The founders originally believed the key need was verification—catching errors the way compilers catch bugs in code. They built technical infrastructure to generate boards, inject mistakes, and train systems to detect issues.

5. 5
   4:01 – 5:02

   Customer reality check: 100+ conversations and a painful pivot

   After extensive user discovery, they learned customers didn’t value the “find my mistakes” pitch—whether because of pride or process, it wasn’t the perceived pain. The real pain was getting the design produced in the first place.

6. 6
   5:02 – 5:29

   Finding the right problem through YC network: the Jetson Orin moment

   A chance conversation with another YC founder revealed repeated demand for custom Jetson Orin development boards in robotics. That concrete, repeatable need gave Diode a crisp wedge and immediate direction.

7. 7
   5:29 – 6:40

   First deal and instant validation: customers want the full solution

   Unlike the lukewarm reception to verification, the new pitch landed immediately—an instant “yes.” They realized buyers didn’t want a component tool; they wanted someone to own the outcome because PCB talent is scarce and outsourcing is common.

8. 8
   6:40 – 11:28

   Services-as-a-product: solving the 80/20 with AI + owned verification

   Diana challenges how a services-like offering becomes venture-scale; Davide explains the model: AI makes them dramatically more productive, while the team still owns correctness. They combine automation with a verification pipeline and explicit acceptance criteria, resembling software delivery but faster.

9. 9
   11:28 – 11:56

   Reframing PCB design as a software problem (and unlocking LLM capability)

   Lenny explains that modern models already “know” much of electrical engineering, but traditional PCB tools are visual and don’t match how LLMs work. By translating PCB design into code, Diode lets models express their latent knowledge, then outputs visuals engineers are comfortable reviewing.

10. 10
    11:56 – 12:31

    Velocity in practice: building internal tools to ship 100+ boards

    The founders discuss how they split responsibilities—Davide leading EE and Lenny leading software—treating the EE team as the first customer of internal tooling. That tooling makes it feasible for a tiny team to manage many clients and produce an unusually high volume of designs.

11. 11
    12:31 – 13:33

    Technical architecture: language design + Rust/Wasm for conservative industries

    To sell into aerospace/medical and other security-sensitive sectors, Diode made deliberate technical choices. They created a schematic language that works for both humans and LLMs, and built an isolated core compiler in Rust with Wasm bindings to enable local, browser-based compilation and visualization.

12. 12
    13:33 – 14:21

    Future outlook: bringing AI’s “10x” gains from software into the physical world

    Davide describes the broader ambition: apply AI acceleration to real-world, physical systems, where reliability and correctness matter deeply. They see hardware as the next major frontier for top engineers and a core driver of long-term impact.

13. 13
    14:21 – 15:28

    Hiring and team building: researchy problem-solvers who also ship

    Lenny closes with what they look for in recruits: curiosity, comfort with open-ended exploration, and the discipline to deliver practical outcomes. They also emphasize product-minded engineers who can build customer-facing interfaces for reviewing and handing off designs.