AI PCB Routing Without the Epic Fails: Inside DeepPCB

AI PCB routing only works when the tool understands your design intent, and in this OnTrack Podcast episode Zach Peterson sits down with Alain-Sam Cohen and Nabil Chouba of InstaDeep's DeepPCB to find out what that actually takes. They explain why classic autorouters fail on configuration rather than on routing, how a reinforcement-learning routing engine paired with Cooper, a natural-language orchestrator, detects net classes, decoupling caps, reference planes, and USB impedance problems before a single trace is drawn, and where LLM-driven PCB-as-code tools fit alongside placement and routing.

Then they open one of Zach's own boards live, let Cooper flag what the design file left unspecified, and compare it with a run they let converge before the show. If you've watched a one-line AI prompt produce an epic hardware fail, this is the case for task-based AI in PCB design and the design knowledge you still need to bring to it.

📚 More from this Episode:- DeepPCB: https://deeppcb.ai - InstaDeep: https://instadeep.com

💡 Watch Next:- AI PCB Autorouting: What's Real and What's Hype: https://youtu.be/YJTbsoxPg7E- AI PCB Layout vs. Human Design: The Honest Truth: https://youtu.be/qX29OWSYTmI- The Black Box Problem With AI PCB Layout Tools: https://youtu.be/JiR10b7f41g- Code-Based PCB Design with AI: Inside atopile: https://youtu.be/J1Dl5bUvm6E- When to Use an Autorouter in PCB Design: https://youtu.be/Hgl7DttRaoo

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