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Altium incident on October 27, 2026: Some customers can observe delays in the projects data generation. We identified the source or the problem and our team is working on the fi Started 10:43 AM UTC, resolved ongoing (● 5m). Affected: Europe, US-East.

Hi! I want to share my open-source project, EasyEDA Copilot. It allows AI agents to create and edit schematics and PCBs directly in EasyEDA Pro. I work with both programming and electronics. I studied electronics in college, where we learned to use EasyEDA. I found it much easier to learn than Altium Designer, so I continued using it for my own projects. The idea for EasyEDA Copilot came about quite a while ago, even before GPT-6 Astra learned to design PCBs in KiCad. At the time, I wanted to try building my own AI agent and combine two areas I'm interested in: programming and electronics. The first version could only edit schematics. Over time, I added more features: schematic creation, component search, automatic component placement, and PCB routing. Now EasyEDA Copilot can handle a large part of the design process, and the result is still a normal, editable EasyEDA document. ## How EasyEDA Copilot Works The main integration uses MCP. The architecture looks roughly like this: `AI agent => MCP => specialized algorithms => EasyEDA` The MCP server connects to the EasyEDA extension through a local WebSocket. The agent can access information about schematics, components, connections, layers, and other objects. A separate Skill can also be built from MCP. The main difference between my approach and simply giving AI access to the editor is that the model doesn't have to do all the work itself. For example, there's an official EasyEDA API Skill that allows agents to execute JavaScript through the editor's API. I took a slightly different approach. In EasyEDA Copilot, the model mostly describes what needs to be done. For example, which components should be placed close together, where connectors should go, or which routing rules to use. Then regular algorithms do the actual work. At the same time, the agent can still execute JavaScript directly in EasyEDA. If it needs to do something unusual or manually fix part of a PCB, it can use the editor's API. So the model defines the tasks, but it doesn't have to calculate the coordinates of every component or trace segment itself. ## How Component Placement Works Placement uses a separate algorithm that receives components, connections, board geometry, and constraints. The agent describes the requirements using a DSL. Here's a small example: board.rect(40, 30, { layers: ["top"], clearance: 0.3 }); block("MCU", ["U1", "C1", "C2"], "mcu"); block("CONNECTORS", ["J1", "J2"], "connector"); edgeMount("J1", "left"); edgeMount("J2", "right"); veryNear(pin("C1", 1), pin("U1", 5)); veryNear(pin("C2", 1), pin("U1", 8)); Here we define a 40×30 mm board, two groups of components, connector positions, and a requirement to place capacitors close to specific microcontroller pins. The algorithm then finds a suitable placement on its own. GPU acceleration is used to speed up placement calculations. Many operations can run in parallel, which is especially useful when working with a large number of components. The algorithm also takes into account component dimensions, overlaps, electrical connections, mechanical constraints, and placement rules. After the calculations, the agent can inspect a preview, change the constraints, or apply the placement in EasyEDA. ## How PCB Routing Works Routing uses a similar approach. The agent describes the rules: trace widths, clearances, layers, vias, differential pairs, and other requirements. For example: drc({ trackWidthMm: 0.2, clearanceMm: 0.15 }); powerNet("+5V", { trackWidthMm: 0.6, allowedLayers: "OUTER" }); diffPair("USB", { positive: "USB_DP", negative: "USB_DM", trackWidthMm: 0.2, gapMm: 0.15, maxSkewMm: 0.5 }); plane({ net: "GND", layers: "BOTTOM" }); runAll(); In this example, we define general routing rules, a separate trace width for power, a USB differential pair, and a ground plane on the bottom layer. The current implementation uses KiCad Routing Tools. I wrote an integration that passes board data from EasyEDA to the router, runs the routing process, and then brings the result back into the editor. After that, the agent can check for remaining unrouted connections and run EasyEDA's built-in DRC. There's also a checkpoint system. The document state is saved before changes are applied. If something goes wrong while applying the result, the previous version can be restored. Of course, routing isn't perfect yet. Complex boards require multiple attempts or manual fixes. I'm currently developing my own routing algorithm. The main goals are to increase speed and improve routing completion rates on complex boards. ## Project Examples ### STM32 CAN AND RS485 One example is an STM32 board with CAN and RS-485 interfaces. I used EasyEDA Copilot to work on both the schematic and PCB in this project. ### 5A USB-PD Trigger Another example is a USB-PD trigger designed for up to 5 A. It has a completed schematic and a fully routed PCB. ### Other Projects I've also tried EasyEDA Copilot on other schematics and PCBs. For example, I have a project for a portable single-channel oscilloscope with a target bandwidth of 200 MHz. So far, only the schematic is ready. The repository also contains examples of an ESP32-C3 controller, a four-layer MIMXRT1011 board, and a 2 GHz RF amplifier. You can see them in the GitHub repository. ## SPICE Simulation Besides PCB design, EasyEDA Copilot can also run SPICE simulations using ngspice. For this, I've put together a library of around 40,000 components. For example, you can ask the agent to design an input stage for a trigger. It can select components, calculate values, build the circuit, and run a simulation. This allows you to check how a circuit behaves before building the actual device. Of course, a simulation doesn't guarantee that the real circuit will behave exactly the same way. The results depend on component models and simulation conditions. For now, SPICE is available through the original built-in interface of EasyEDA Copilot. Most of the project's development is now focused on MCP. ## What's Next I'm continuing to work on my own PCB router. I also plan to add PCB analysis tools: Signal Integrity (SI), Power Integrity (PI), and thermal analysis. I'd like the agent to be able not only to create schematics and PCBs, but also to run engineering calculations, find problems, and fix them. But these features are still under development. ## Source Code EasyEDA Copilot is an open-source project licensed under MIT. GitHub: https://github.com/biosshot/easyeda-copilot To use it, you need EasyEDA Pro Desktop, Node.js, and an MCP client such as Claude Code or Codex. The repository contains installation instructions, documentation, and project examples. I'd be happy to hear feedback, especially from people who work with electronics and have tried automating the design process.

I've watched a lot of AI demos this year. Most of them are about writing code or making images and videos. This one is about building a real circuit board, and it got me a bit more excited than I was expecting. Adom Industries, a small startup in Fort Worth, Texas, just posted a short video they titled "1st Ever: AI Designs a Complete PCB in Altium." It's under five minutes long. I highly recommend watching it first, and then we can go over the recap. ## Why This Got My Attention What's cool to me is how accessible building your own electronics is becoming with the help of AI. For most people, designing a circuit board has felt out of reach. You needed years of training, pricey software, and a lot of patience. Some of that is still true. But this video shows one sentence turning into a finished board design in under two hours. The ability for people to actively prototype ideas has just become incredibly simplified for the average hobbyist. ## What Adom Actually Built The board is a small power converter. Adom calls it a "buck converter." In plain words, it takes 12 volts in and gives you a steady 5 volts out, the kind of power a lot of small gadgets run on. It's about the size of a postage stamp, 28 by 20 millimeters. Here's the prompt their team typed, word for word: "Use adom-aiflow to design a 12 V to 5 V, 1 A buck converter using the TPS54202, and build it as a complete board in Altium Designer." Altium Designer is the professional software that engineers use to lay out circuit boards. Adom built a tool they call the Altium Bridge, which lets an AI agent (Claude, running inside Adom's Hydrogen app) drive Altium one step at a time and check its own work as it goes. Adom says nobody touched Altium during the run. ## What the AI Did, Step by Step Adom's CEO John and software engineer Colby walk through it in the video. Here's the recap. Based on Adom's description and write-up, the AI: * Picked the parts and pulled in their drawings and 3D models. * Drew the schematic, which is the wiring diagram for the board. * Tested the design in simulation before anything was built. Adom reports all 18 of its checks passed. * Placed the parts, routed the copper connections, and filled in the copper areas. * Checked current, heat, and electrical noise with Adom's own analysis tool, then reworked the board until it passed. * Exported the manufacturing files. That includes Gerbers (the files a board factory uses to make the board), a parts list, and placement files for the assembly machines. Adom says it took 1 hour 48 minutes from prompt to finished board, and used about 1% of the weekly limit on a $200 a month Claude plan. Adom also has a full write-up on their wiki with the project files, simulation results, and a 3D model: https://wiki.adom.inc/kcknox/altium-buck-12v5v-molecule ## The Honest Part, and Why I Like It Here's what I respect most. Adom doesn't hide the rough edges. Their wiki page has a section called "Open items before ordering," and they list the flaws themselves: * The board hasn't been built yet. Everything so far is design, simulation, and analysis. That matters because a board can pass every check on screen and still surprise you on the bench. * Altium kept a default board thickness that doesn't match what the design assumed. If you ordered it as is, the heat numbers wouldn't hold. Easy to fix, but only if you know to look. * One copper path is longer than their own target, and some printed labels crowd each other. * Their analysis flagged a possible ground loop and no protection diodes on the inputs and outputs. That list is a point in their favor. It tells me the tool is checking real things, and it tells you what a person still needs to review before spending money on boards. The AI did the heavy lifting. A human still makes the final call. ## What This Means for the Rest of Us This is part three of a series. Adom already built the same board in KiCad and Fusion 360, so it isn't tied to one expensive program. They also say it works with other AI agents, not only Claude. For a solo builder, a hobbyist, or a small business owner with an idea for a gadget, that's a big deal. The gap between "I have an idea" and "I have a board design I can order" is getting a lot smaller. You still need to learn enough to check the work. But you no longer need a whole engineering team to get started. Technology is a tool. It still needs the human piece. What's changing is how many people get to pick up the tool. ## Go Watch It and Follow Adom If any of this sparked something for you, watch the video, then follow Adom Industries on YouTube: https://www.youtube.com/@adominc They're a small team building in the open, and they ask their viewers what they should build next. I'd love to see more people take them up on that. Here's my question: If you could describe a gadget in one sentence and get a board design back, what would you build first?

Altium incident on October 19, 2026: We are currently experiencing intermittent issues with search-related functionality in A365 in EU region. Our team is actively working to re Started 9:10 AM UTC, resolved ongoing (● 9m). Affected: Europe.

Required Skills: Altium Designer