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        "title": "Making Claude a better electrical engineer | Claude",
        "url": "https://claude.com/blog/making-claude-a-better-electrical-engineer",
        "date": "Dec 11, 2025"
      },
      {
        "title": "How Diode Is 10x-ing Hardware Design",
        "url": "https://www.youtube.com/watch?v=ryHJuYzUejs",
        "date": "Jul 23, 2025"
      },
      {
        "title": "AI-Powered Circuit Board Design Startup Diode Lands $11.4 Million Series a - Business Insider",
        "url": "https://www.businessinsider.com/ai-circuit-board-diode-a16z-series-a-y-combinator-2025-7",
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        "id": 83244,
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        "tagline": "Diode automates the circuit board design and ordering process for engineers.",
        "body": "Ciao Y Combinator! We’re [Davide](https://x.com/davideasnaghi) and [Lenny](https://www.linkedin.com/in/lennykhazan/) from [Diode Computers, Inc.](https://diode.computer/)\n\n**TL;DR: Diode is an end-to-end platform for circuit board design. With the help of AI, we can finish a months-long design project in days, and then ship working boards straight to your door.**\n\n**Try out our designer at **[**https://pcb.new/**](https://pcb.new/)**, or shop generated boards at **[**https://pcb.store/**](https://pcb.store/)**.**\n\n<https://www.youtube.com/watch?v=aOoG2gl8wdY>\n\n# Problem\n\nDesigning printed circuit boards (PCBs) is really hard. Existing tools provide little opportunity for design reuse, so most projects are started from scratch. Since there’s no good way to test your design, your best bet is to just order them and hope for the best.\n\nThought you were done? Nope — ordering PCBs is a pain too. Now you need to source the components, ship them across the globe to your manufacturer, and constantly be on the lookout for part shortages and replacements. It’s a full-time job.\n\n# Solution\n\nDiode solves this by owning the entire PCB design process end-to-end. It starts with a core of composable, reusable modules that users can stitch together to build their boards. When new use cases come up, our AI generator creates new modules in seconds instead of days. And with rigorously-tested modules instead of de novo designs, we can be confident that each board works first try.\n\n![uploaded image](/media/?type=post&id=83244&key=user_uploads/79914/00e25ff4-abe8-49d4-94c3-e74a925eb0a3)\n\nWe then take the user’s design and automatically translate it into manufacturing requirements to send to the factory. We stockpile all of the necessary components to remove the burden of supply chain management from users and amortize the cost of parts across all designs.\n\nThe result is an all-in-one platform for hardware design: describe what you need and get working boards delivered to your door.\n\n# Why\n\nIn a past life, we designed hardware at companies like Apple, and we encountered a problem: PCBs never worked on the first try. At best, they required micro-soldering surgery under a microscope and, at worst, a whole new board. These issues were driving us mad, so we started a company to fix it.\n\nWe want to make hardware design work more like software. Fast iteration cycles, reusable components with clean composition, and one-click ordering to build your products fast and cheap. Our vision is to turn PCB design into a software problem.\n\n**P.S.** Want a customized NFC business card with your logo? Get your own: <https://pcb.store/products/nfc-business-card>\n\n![NFC Business Card (x10)](https://pcb.store/cdn/shop/files/back.png?v=1724092003&width=1445)\n\n",
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        "full_name": "Rupesh Jeyaram",
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        "full_name": "Antonio Monreal",
        "title": "Founder/CTO",
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        "title": "Business Development Intern – Summer/Fall 2026",
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        "url": "https://www.ycombinator.com/companies/revise-robotics/jobs/peSRWPy-engineering-intern-summer-fall-2026",
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      {
        "id": 87007,
        "title": "Revise Robotics – Automated Electronics Refurbishment 🦾 💻",
        "tagline": "Our robot tests, refurbishes, and resells used electronics devices!",
        "body": "**At Revise Robotics, we’re building automated systems to refurbish and resell used electronics.**\n\n![uploaded image](/media/?type=post&id=87007&key=user_uploads/943950/79b9f19d-2610-4a84-b329-7b8624645181)\n\nEvery year, Americans discard more than **30 million computers**. Many of these devices find a second life on the resale market, extending their usefulness and reducing their environmental footprint.\n\nHowever, the process – inspection, data-wiping, reprogramming, and packaging – is **extremely** **tedious and time-consuming**, limiting how many devices can actually re-enter circulation.\n\nWe’re changing that. With robotics, computer vision, and AI, we’re breaking down these barriers and advancing a more circular electronics industry 💻\n\nWe just completed our first pilot project last month, and we are excited to be iterating and gearing up for our second pilot at the end of February!\n\n**Ask**: Introductions to e-waste recycling facilities or IT asset management/disposition companies. Please reach out if there’s someone you think we should speak to! [rupesh@reviserobotics.com](mailto:rupesh@reviserobotics.com) \n\n# **Full Demo Video**\n\n[**https://youtu.be/QMFTsSG-FyQ**](https://youtu.be/QMFTsSG-FyQ)\n\n# **Still Shot**\n\n![uploaded image](/media/?type=post&id=87007&key=user_uploads/943950/ca646ef9-8d31-4865-93cd-6b629a1612c3)\n\n",
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        "votes": 27,
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        "answer": "We both grew up in the suburbs of Toronto and graduated from Mechatronics Engineering at the University of Waterloo. Despite similar journeys we didn’t finally meet until we interned together at Neuralink during our Junior year. We bonded over our passion for engineering and stayed in touch into our Senior year where we built the first Steinmetz inverter. We have both worked in the automotive industry working with low and high voltage systems at Tesla and have experience across the hardware stack. Between us we have worked on billion transistor GPUs, space systems, neural interface ICs, billion record databases, rail systems, and firmware for mass produced consumer electronics. Steinmetz marks a new chapter for us where we are leveraging our broad experience across the hardware stack to enable the next generation of electric vehicles."
      },
      {
        "question": "What is your long-term vision? If you truly succeed, what will be different about the world?",
        "answer": "Our mission is to accelerate the adoption of electric vehicles of all forms (planes, trains, cars, boats). To achieve this we aim to improve the performance of electric vehicles while **reducing cost** and **volume**. We will enable vehicles that beat their combustion engine equivalents on all metrics. Electric power-trains are capable of achieving nearly **perfect efficiency** converting stored energy to motion which is not possible in combustion engine vehicles. Through the refinement and adoption of electric vehicles we can greatly reduce the cost to transport people and goods. This will have Trillion dollar implications for the global economy."
      }
    ],
    "url": "https://www.ycombinator.com/companies/steinmetz",
    "api": "https://devasheeshg.github.io/yc-api/batches/winter-2025/steinmetz.json",
    "year_founded": 2024,
    "city": "San Francisco",
    "country": "US",
    "linkedin_url": "https://www.linkedin.com/company/steinmetzinc/",
    "x_url": "https://x.com/SteinmetzInc",
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      "name": "Tom Blomfield",
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        "user_id": 596175,
        "full_name": "Owen Brake",
        "title": "Founder/CEO",
        "founder_bio": "Multi-disciplinary engineer with a track record of building across industries—from high-performance brake systems to GHz FCC compliance and scaling production SQL databases with 10B+ records.\n\nPreviously developed motor controllers at Tesla. Held diverse engineering roles at Neuralink, Apple, Parallel Systems, and Ford.\n\nMechatronics Engineering graduate, University of Waterloo. Led the Formula Electric team, driving innovation in EV performance.",
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        "full_name": "Ethan Childerhose",
        "title": "Founder",
        "founder_bio": "Co-founder and CTO at Steinmetz. Previously at Rocketlab, Nvidia, Tesla, and Neuralink. I've worked across the hardware stack from analog transistor level design to 100 lb mechanical fixtures for environmental testing. My work has reached the moon, been mass produced millions of times, and processed the faintest of signals from the human brain.",
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        "title": "Electrical Engineer",
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        "location": "San Francisco, CA, US",
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        "id": 95360,
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        "url": "https://www.ycombinator.com/companies/steinmetz/jobs/wMTbVhT-generalist-hardware-firmware",
        "location": "San Francisco, CA, US",
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        "role_type": "Hardware",
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      {
        "id": 95361,
        "title": "Firmware Engineer",
        "url": "https://www.ycombinator.com/companies/steinmetz/jobs/4dbvLf3-firmware-engineer",
        "location": "San Francisco, CA, US",
        "type": "Full-time",
        "role": "Engineering",
        "role_type": "Embedded systems",
        "salary_range": "$100K - $175K",
        "equity_range": "",
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        "visa": "Will sponsor",
        "skills": [
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    ],
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    "launches": [
      {
        "id": 88019,
        "title": "Steinmetz - Hardware for the Next Generation of Vehicles",
        "tagline": "Steinmetz, the engine of electric vehicles",
        "body": "Hey YC,\n\nWe are Ethan and Owen, building the engine of electric vehicles. Motor controllers with 3x higher power densities, that remain cost competitive with existing solutions.\n\n<https://www.youtube.com/watch?v=uIQkUCxhIG4>\n\n# The Problem\n\nAutomotive manufacturers are quickly transitioning to electric vehicles but initial offerings remain expensive and are largely unprofitable. This has led to slow adoption compared to their combustion engine counterparts.\n\nWe have both witnessed while working at Tesla, the immense difference in design and cost between Tesla's vehicles, and EVs from existing vehicle manufacturers. Incumbent part suppliers and manufacturers are skilled in the intricate mechanical design of combustion engine vehicles, but lack the electrical expertise for EVs which are primarily chips and PCBs.\n\n# Our Solution\n\nAt Steinmetz, we are starting with the inverter (motor controller). This lies between the battery of the vehicle and the motor--it converts the DC power from the battery into 3 phase AC for the motor. Using modern power electronics techniques and tight systems integration, we are able to deliver a motor controller which achieves 3x greater density than the state of the art, at equal or greater efficiency. This allows us to bring down not only the unit cost of inverters in vehicles today but, through greater density and higher efficiencies, the cost and performance of the whole vehicle.\n\n![uploaded image](/media/?type=post&id=88019&key=user_uploads/1381592/997953eb-7e3b-4ba7-9d07-6a1d21f3c43f)\n\nTo give context for the density improvements here, our bandgap product is able to drive a peak power of 200kW through the equivalent volume of 3 yerba mate cans. This is the same power draw as 450x 4090 GPUs or 6.5 server racks fully populated with H100 GPUs (208 GPUs).\n\n![uploaded image](/media/?type=post&id=88019&key=user_uploads/1381592/981f5792-0f6b-42c9-bb4a-dee43a2c8e2b)\n\n# We are on a mission to simplify electric vehicle hardware and accelerate adoption\n\nIf you are working on any electric vehicle (trains, cars, boats, snowmobiles, cranes, submarines, planes, tractors, etc.) learn more at [steinmetzmotors.com](https://steinmetzmotors.com/) or send us an email: [founders@steinmetzmotors.com](mailto:founders@steinmetzmotors.com)\n\n![uploaded image](/media/?type=post&id=88019&key=user_uploads/1381592/28930e11-55a3-4eda-a40d-693b603f0c01)\n\n![uploaded image](/media/?type=post&id=88019&key=user_uploads/1381592/a0ad2acc-de3a-4227-be09-3a8a768f4c96)\n\n",
        "url": "https://www.ycombinator.com/launches/Mtf-steinmetz-hardware-for-the-next-generation-of-vehicles",
        "votes": 27,
        "created_at": "2025-02-25T17:47:52.712Z"
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    "id": 30264,
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    "slug": "stillwind",
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    "website": "https://stillwind.ai",
    "all_locations": "Zürich, ZH, Switzerland",
    "long_description": "Stillwind is a fractional librarian for startups. Customers give us the parts they want to put into designs and we give them footprints, symbols and 3d models made from the manufacturers datasheet.",
    "one_liner": "PCB component librarian",
    "team_size": 3,
    "industry": "B2B",
    "subindustry": "B2B -> Engineering, Product and Design",
    "launched_at": 1740421634,
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        "title": "Stillwind Builder — Zero to BOM in minutes instead of days",
        "tagline": "AI agent that turns your PCB design intent into a complete, verified bill of materials.",
        "body": "❌ **The problem**\n\nEvery PCB design is a constraint problem: you need components that are electrically and functionally compatible with each other. Solving it by hand means hours — often days — of tracking down parts, reading datasheets, adding a component, discovering a conflict, and backtracking. Pick an MCU and the cascade begins: it needs a specific crystal, external flash on the QSPI bus, a regulator that can source its peak current. Every choice ripples through the whole design.\n\n✅ **The solution**\n\nStillwind Builder formalizes your design constraints as an explicit system of equations and solves for matching components.\n\n* **Verified specs.** Before we show you a part, a second model independently re-reads its datasheet and verifies the specs match — so the numbers you design against are what the datasheet actually says, not extraction artifacts.\n* **Dependency-aware.** When you lock in a component, the agent reads its datasheet for the supporting parts it requires — voltage regulators, crystals, external flash — and updates the constraint system. The ripple effects of each choice are handled instead of discovered later.\n* **You stay in control.** You set the direction and make the calls that matter; the agent handles the combinatorial grind.\n\nAt the end, you download your BOM and start wiring.\n\n🚀 **Try it**\n\nThe public beta is live and free during launch week: [**https://stillwind.ai**](https://stillwind.ai)\n\nBuilding hardware and want to tell us what's broken? We'd genuinely love that — grab time with us: <https://calendar.app.google/Bd7KQEAYLgt6SmHZ6>",
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        "tagline": "Improving your AI agents with reinforcement learning.",
        "body": "Hey all 👋, we’re Linus, Hannes, Lukas, and Josef—co-founders of [**Augento**](https://www.augento.ai/)! 🕊️\n\n**TL;DR**\n\nWe align your agents with reinforcement finetuning. You give us your agent, tell us where it fails and we’ll improve it. 🚀\n\nWe are actively looking for **design partnerships**. If you are interested, please shoot us a message at [**founders@augento.ai**](mailto:founders@augento.ai) 😄\n\n**The Problem ❌**\n\n🗣️ AI Agents struggle in real-world environments. Even state-of-the-art reasoning models score below 50% accuracy on non-trivial benchmarks.\n\nThe solution for many is still prompt engineering &amp; expanding the models' guardrails. However, anyone who’s fought with large prompts knows how draining it can be. You’re never quite sure if the model is really following your instructions or if your tweaks make any difference.\n\n**Our Solution ✅**\n\nWe tackle this by replacing prompt engineering with fine-tuning + RL on **your** feedback. We integrate with a two lines of code change in your existing system.\n\n[**https://www.youtube.com/watch?v=Sulzf7VZr3k**](https://www.youtube.com/watch?v=Sulzf7VZr3k)\n\n**The Workflow 💡**\n\n1\\. Swap out your LLM connector URL with ours.\n\n2\\. We intercept every prompt and output, displaying them in our UI.\n\n3\\. Where necessary, you give high-level feedback, like your preferred tone or how a tool should actually be used.\n\n4\\. We continuously post-train the model to match up to your feedback.\n\n5\\. Once you deem it good enough and want to switch over to the model, you can do that with a click of a button, no changes to your code required.\n\n**Our Ask**\n\nWe’d love your input and are looking for early users to test-drive Augento. Shoot us a message at [**founders@augento.ai**](mailto:founders@augento.ai)\n\n**The Team**\n\nLinus previously studied CS @ ETH in Zurich and did research in complexity theory. During his studies, he worked as an ML Engineer &amp; as a Quantitative Developer in High-Frequency Trading.\n\nHannes previously studied CS @ ETH Zurich and worked on decentralized and distributed systems. During his studies, he worked as a paid contributor for a big open source project and as the technical lead for his previous startup.\n\nJosef previously studied CS @ ETH Zurich, and worked on computer systems and networks, as well as ML. During his studies, he worked as a full-stack software engineer and embedded systems developer.",
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        "title": "Axal: Designing and Getting PCB's in China is Dead",
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        "body": "We are launching Axal, a services company that designs, assembles, and tests custom PCBs for hardware startups in days. American manufacturing is back. 🇺🇸\n\nAxal enables hardware teams to get custom PCBs designed and built in the U.S. without needing electrical engineers on staff.\n\nWe’ve helped teams go from no PCB design to a working board delivered in as little as two weeks.\n\nIt’s ridiculous that American hardware startups have to go overseas just to get a PCB designed and built affordably. Together, we can change that and build more hardware in America.",
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        "id": 91586,
        "title": "Axal: Legacy Code, Understood in Hours. Seriously.",
        "tagline": "We help startups who want to integrate their tech into enterprise legacy systems by expediting the process of discovery + rewrite by months.",
        "body": "Hi, we’re Samai and Nand — Co-Founders of Axal 👋\n\nIf you're selling to a sticky product to enterprises, you've probably run into this:\n\n“We’d love to use your product, but our stack is too old...”\n\nThat’s where we come in.\n\nAxal reverse engineers legacy codebases (Java, C#) to generate **functional requirements and user stories in hours** — essentially helping your clients expedite the discovery process of their modernization. A beta version of our tool then figures out what needs to be rewritten and makes an outline for your team so you can easily rewrite their code and integrate your product. \n\nMongoDB already does this to land enterprise deals — they rewrite the client’s legacy system _just enough_ to make it so they can integrate their product and switch up the DB. Then they are sticky forever.\n\nGet setup in less than 1 hour guaranteed. \n\nAxal Demo - Creating Functional Requirement Document and User story of 30k line Java codebase \n\nhttps://www.youtube.com/watch?v=yXWTFxfw2vE\n\nWe make that process instant and repeatable so if you have a sticky product you can integrate with enterprise codebases easily.\n\n**Why it matters to you (YC founder):**\n\nYou’re not just selling software. You’re selling _change_.\n\nIf legacy tech is blocking your deal, let us unblock it — so you can close faster and look like a hero.\n\nTo get started, email me - [samai@joinaxal.com](mailto:samai@joinaxal.com)\n\nJoin the waitlist rewrite tool: ",
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        "title": "Axal - Automate identifying and fixing architectural tech debt",
        "tagline": "Break down monoliths, identify tech debt, and fix it with AI at scale!",
        "body": "Hey everyone, I’m Nand - Founder at Axal👋\\\n\\\nWe built a tool that uses deterministic methods to **automate the hardest parts of application modernization**— identifying architectural bottlenecks and prioritizing those issues based on business value. Once the issues are broken down by Axal, AI can autonomously collaborate with your team to resolve them.\n\n# **The Problem**\n\nEveryone knows that software teams cut corners in development over time, resulting in accumulation of debt tech overtime that slows them down and raises costs. Until now, to address this problem there needed to be long modernization efforts, where stakeholders spent months finding possible solutions to the problem, if you could even find and train the team members needed to do the work. \n\n# **Our Solution: One platform for Application Modernization**\n\nAxal uses deterministic methods to provide teams with clear observability into architectural technical debt.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/5453ac1a-0928-4ba2-91f1-665ad2c142fd)\n\nWe show tech debt scores tailored to your goals. For example, if maintainability is your focus, we display the maintainability index, aligning business impact with priorities to guide effective action.\n\nTechnical teams can leverage our graphs to gain clear insights into class-level and domain-level codebase relationships.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/ceaeb77c-b33c-4ef2-8540-3e5fc5f564d2)\n\nArchitectural issues - domain exclusivity, circular dependencies, dead code, etc. - are automatically detected based on the goals that an organization makes, and engineers can work with Axal to assign their priority.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/f63d172c-c479-4a22-92b6-ab40ffdd2ef7)\n\nOnce prioritized, **Axal leverages AI to autonomously address issues**, while ensuring none of the existing code breaks.\n\n![uploaded image](/media/?type=post&id=86865&key=user_uploads/570999/01d79606-ac19-4fd4-a503-aff34a23a9c8)\n\n**Demo Video** (\\* excludes technical debt scores and AI code fix demonstration)\n\n<https://youtu.be/4WAwWXrpAGU>\n\n# **Our Ask**\n\nPlease reach out:\n\n\\- If you want to see your team's architectural technical debt \n\n\\- If you have a Java, C#, or Go monolithic application you want to modernize, contact us (min. 100k lines of code)\n\nPlease let us know if you have any previous connections to large to medium-sized companies undergoing application modernization\n\nLearn more at [axal.ai](http://axal.ai)",
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        "title": "NODI Energy - Distributed Energy Infrastructure to Rewire the Grid",
        "tagline": "Making the grid flexible to unlock GW power, enabling on-grid interconnection for data centers",
        "body": "Hi everyone 👋! We're [Borong](https://uk.linkedin.com/in/boronghu) and [Catherine](https://www.linkedin.com/in/cathjeong/), co-founders of NODI Energy!\n\n**TL; DR:**\n\nNODI is building distributed energy infrastructure to rewire the grid. We are deploying and aggregating batteries at the edge. All these distributed nodes are orchestrated to make the existing rigid grid more flexible, reducing grid congestion and unlocking more capacity at specific constrained locations. So data centers can get **_on-grid_** connection in weeks instead of waiting on grid reinforcement for decades. ⚡ ️ **Gigawatts unlockable on the way!**\n\nLaunch video: <https://youtu.be/svScryhDnog>\n\n### **Problem**\n\nThe existing power grid was built for the fossil-fuel era, not for tomorrow’s economy. It’s too rigid to deliver power to the right place at the right time.\n\n* 2,000 GW of projects, including data centers, sit stalled in grid connection queues, waiting up to 15 years.\n* 200 TWh of renewable energy was curtailed last year, with several countries dumping over 20% of their generation.\n* Over 1,000 GW of capacity could potentially be unlocked from the existing network, only if the grid is flexible enough.\n\n### **Solution**\n\nWe are building a vertically integrated engine to create a flexible grid. Three layers: \n\n* **Hardware:** originating from the edge, we deploy our own plug-in batteries and aggregate energy assets from third parties.\n* **Software:** orchestrating and operating as these distributed nodes to enable real-time locational flexibility in the grid.\n* **Intelligence:** modeling the grid from edge data, reducing grid congestion, and delivering capacity at the right time and place.\n\n### **It’s giving main character energy**🌟\n\nResults in 6 months:\n\n* 2,000 plug-in batteries on the way, per month!\n* Onboarding >1 GW of batteries in 2026.\n* Secured a pipeline to aggregate 10 GW of assets in 2027.\n* Soon to be one of the largest multinational VPPs.\n\n### **Team**\n\nBorong Hu, PhD in power electronics from Warwick and postdoc at Cambridge University, with 60+ papers, IEEE awards, and government grant funding. Built power conversion systems for AI data centers and one of the world's largest offshore wind turbines. Led R&amp;D collaborations with world-leading industrial partners.\n\nCatherine Jeong, Second-time industrial tech founder with a decade of experience across energy, climate investment, and policy. Holds a BA in Political Science from Brown University and an MSc in Climate Innovation from London School of Economics. Former NCAA Division I fencer, now taking a stab at the grid.\n\n\\\n**Ask**\n\n* **Project developers,** stuck in a connection queue in US, GB, Netherlands, Germany, and Ireland, looking for a demand-side answer. Tell us what a year of delay costs you.\n* **Network operators,** who want to know LV visibility and constraints.\n* **Utilities and energy suppliers,** who need predictable behind-the-meter capacity they can count on\n* **Households and small businesses in urban areas who** think electricity bills are too expensive. \n* Hiring ambitious talent to join the Power Team. \n* Intros to any of the above.\n\nContact: info@nodienergy.com\n\n![uploaded image](/media/?type=post&id=110609&key=user_uploads/2116203/c3942998-0111-4265-9f36-cd3da7b0ba75)\n\n",
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        "created_at": "2026-08-14T22:20:32.941Z"
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        "title": "PowerMatrix: Efficient and Compact Power Supply for AI Hardware",
        "tagline": "Efficient and compact power supply for GPU and data centers to save 50% energy",
        "body": "**TL;DR**\n\nPowerMatrix delivers highly efficient and compact power supplies for cutting-edge applications—from GPUs and data centers to drones, EVs, and aerospace. Based on proprietary technologies, our power supply systems can reduce energy loss by up to 50%. We’ve built working prototypes and are piloting with world-leading partners.\n\n# **The Problem**\n\nAI computing heavily relies on data centers where every watt of electricity is processed and converted by multiple stages of power supplies—from the power grid to processors.\n\nCurrently power supply solutions face significant challenges:\n\n* **Inefficiency:** Data centers consume 5% - 10% of global electricity, while 20% of that (100TWh) is wasted on power supplies.\n* **Size Constraints:** Power supply is given very limited space in server trays and on GPU board surface but required to provide much higher power.\n* **Performance Gaps:** It is required to provide a voltage conversion ratio over 100 and provide 1A/ns dynamics for robust operation of future advanced AI computing processors.\n\n# Our Solution\n\nBased on proprietary technologies, we provide the reverlutionary **single-stage vertical power delivery solution:**\n\n* **Single Stage:** directly convert high voltage to &lt;1V low voltage, eliminating inefficiencies multiple stage power conversion chains.\n\n  ![uploaded image](/media/?type=post&id=90889&key=user_uploads/2116203/943302c9-5ff6-4189-8cd3-47d80cd3b6d0)\n\n* **Vertical Power Delivery:** minimize power transfer loop, locating directly underneath computing chips.\n\n  ![uploaded image](/media/?type=post&id=90889&key=user_uploads/2116203/a4ce171d-72bb-4bfe-b640-23d7eb2db1d6)\n\n\nResults vs. incumbents:\n\n* **80%** smaller form factor\n* **50%** less energy wasted\n* **10×** faster dynamic response\n\nDeploying our modules can save customers **$10 B** annually, cut **30 TWh** of electricity waste, and avoid **100 Mt** of CO₂ emissions each year.\n\n# Team\n\nWe have more than ten years of experience in power electronics and are dedicated to solve the most challenging tasks in this area.\n\nBorong did a Postdoc at the University of Cambridge and got his PhD in power electronics from the University of Warwick. He has extensive experience in research: he published 60 papers that got 650 citations and received the IEEE ECCE William Portnoy Award. He also worked on a power converter for the largest wind turbine at GE, and led a team at Bitmain, a bitcoin miner, to develop a new power supply.\n\nXufu got his PhD in power electronics from the University of Cambridge. He received the Semikron Danfoss Young Engineer Award in 2025, the Trinity Bradfield Prize Award in 2025, and First Place Award of the IEEE ECCE Best Student Project Demonstration in 2023. He also published 15 papers on power electronics that have 41 citations.\n\n# Our Ask\n\nIf you’re building AI hardware, data-center infrastructure, or next-gen power-electronics, let’s connect! [info@pwrmatrix.com](mailto:info@pwrmatrix.com)\n\n![uploaded image](/media/?type=post&id=90889&key=user_uploads/2116203/a8103e69-94a4-451c-9bbd-7f740349c937)\n\n",
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        "id": 105450,
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        "full_name": "Seungmin Hong",
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        "body": "Hey YC! We’re Koosha and Anmol, the founders of Resin. We’re building an AI-native PCB design tool that helps engineers turn ideas into working electronics faster and more reliably.\n\n**Demo: [https://www.youtube.com/watch?v=JByTuaHHHGg](https://www.youtube.com/watch?v=JByTuaHHHGg)**\n\nMandatory GIF:\n\n![uploaded image](/media/?type=post&id=120163&key=user_uploads/501763/ddae1ba4-75e5-43a7-9a30-fe4fa392848f)\n\n**Problem we’re solving**\n\n* **PCB design is slow and manual:** Engineers can spend weeks reading datasheets, finding components, drawing schematics, and routing connections on traditional design tools. \n* **Design mistakes are expensive:** A design error that only gets surfaced _after_ fabrication can require redesigning and manufacturing the board again, adding weeks/months of delay and cost.\n* **Requires expertise:** Good board design takes years of experience to master, so many smaller companies can't do it in-house. Resin makes it accessible to experts and non-experts (including hobbyists) alike.\n\n**How Resin solves this problem**\n\nResin brings AI into a complete ECAD workspace to increase engineering velocity &amp; design reliability:\n\n* **Draft and review schematics:** Describe your requirements. Resin researches parts, drafts schematics, and documents its design decisions. It also reviews existing designs to help catch mistakes before manufacturing.\n* **Find or generate any part:** Tell Resin which component you need. It searches millions of parts, analyzes them deeply and generates accurate symbols and footprints.\n* **Route boards:** Connect selected signals or your whole board with our proprietary routing engine. We’re especially excited about this one!\n* **In the cloud and collaborative:** Resin runs fully in the cloud, and allows seamless collaboration across multiple users!\n* **Prepare for manufacturing:** Check component pricing and availability, manage your bill of materials, and export manufacturing files.\n* **Stay in control:** Resin is a complete EDA workspace with full schematic, PCB tooling (**and not a mere chatbot!**). Users can delegate entire workflows to AI or get hands-on with individual components, connections, and traces. Every AI change is editable and auditable.\n* **Bring existing work into Resin:** We have full support for project &amp; library imports from Altium &amp; KiCad so you can continue existing projects in Resin! There are more integrations on the way!\n* **MCP compatible:** Work from Claude Code, Codex, etc.\n\n**Team**\n\nWe’ve been long time friends — we met in college where we studied Engineering Physics together! Koosha has tons of electronics and hardware experience, having designed very complex hardware at Bosch, Kodak, IHS. Anmol mostly recently led the FDE team at [you.com](http://you.com) and was an early member at various successful AI startups.\n\n**Our Asks**\n\n**Are you or your team building hardware with PCBs? Sign up with this link to get started with some bonus credits [https://resineda.com/signup?promo=YC2026](https://resineda.com/signup?promo=YC2026)!** We’ll reach out for an onboarding!\n\n**Know someone who designs electronics? We’d love intros** to other founders, electrical engineers, hardware leads whether they’re building robots, drones, medical devices, industrial equipment, or consumer products. \n\n**Contact**: Email [anmol@resineda.com](mailto:anmol@resineda.com), text 415 425 4809, or DM me on bookface!",
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        "full_name": "Jonathan Powers",
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