Flux moves from one-off actions to executing multi-step workflows including researching parts, creating schematic designs, placing and routing, and running checks. Think of Flux as a capable intern — fast, explainable, and eager to learn, but still needing oversight and occasional help.
Hardware raises the stakes, iteration is slower and costlier, so you can’t stumble on business basics or customer insight. Winning teams de-risk the business model and iterate fast. This bookshelf helps sharpen judgment and give technical founders the tools to build companies people love.
Here’s the hard truth: most hardware startups don’t fail because they can’t build a prototype or find a manufacturer. While still difficult, technical execution is getting easier every year—modern tools, AI included, are streamlining that part of the journey. What kills most teams are the missed fundamentals:
Hardware raises the stakes because iteration is slower and costlier. You can’t afford to stumble on business basics, design fundamentals, or customer insight. The teams that win are the ones that maximize their rate of learning—by de-risking the business model while iterating the product as fast as possible.
That’s why we put together this bookshelf. It’s not just about engineering or manufacturing (though you’ll find the best guides here). It’s about sharpening judgment, broadening perspective, and giving technical founders the tools to build companies people love.
For hardware founders, the hardest part usually isn’t the prototype—it’s building the company around it. These books focus on judgment, focus, and leadership: how to move fast without losing clarity, protect the details that matter, and make the calls that keep a small team alive. They’re about operating at founder speed when time, money, and attention are always scarce.
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Hardware doesn’t forgive sloppy execution. Once you leave the lab, mistakes multiply—costs rise, timelines slip, and quality issues get baked into production. These books help founders treat manufacturing as part of the product itself: learning to engage suppliers early, de-risk decisions, and build systems that scale without collapsing under their own weight.
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Every hardware founder eventually gets burned by the basics. Power rails, grounding, EMI, provisioning flows—these are where folklore and half-remembered rules can cost you entire boards. These books turn “tribal knowledge” into principles you can rely on, helping you avoid expensive surprises and design products that actually hold up in the field.
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Great hardware isn’t just about circuits and enclosures—it’s about making something people actually want to use. These books teach the fundamentals of design thinking, product discovery, and usability. For hardware founders, they’re the bridge between technical execution and customer love—the difference between a product that works and a product that wins.
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Building hardware is a long, uncertain grind. Sometimes what you need isn’t another playbook—it’s proof that others have walked this road before. These books capture the culture, discipline, and stubbornness of teams who built under pressure, kept their vision intact, and shipped work that mattered.
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These books shape how we think at Flux, but the real progress comes from learning together. That’s why we created the Flux Hardware Slack Community. It’s where founders connect to:
You can also book design reviews with the Flux team to receive actionable feedback before you head to production. Please let us know if there are other resources you’d like us to provide that could your hardware startup become a massive success! We’re here to help.
Open Flux now, switch Copilot to “Next-gen” and see how it handles your next design challenge. The sooner you try it, the more your feedback can shape the next leap in AI-powered hardware design.
In the right scenarios, it’s already delivering sharper reasoning, smarter reviews, and more accurate design decisions than anything we’ve shipped before. We wanted to get it into your hands immediately so you can explore what’s possible alongside us. It’s early, it’s raw, and we want you to push it. Break it. Tell us where it shines.
You can start using it right away. Open any project in Flux and launch Copilot. Click the model dropdown at the top of the chat panel, select “Next-gen” and then give it a real challenge. Some great starter prompts to see its strengths include:
“Perform a top-to-bottom schematic review for correctness, completeness, and robustness. Assess power, clocks/resets, signal interfaces, analog paths, protection, and passive choices.”
“Replace all low-stock parts with alternatives that meet the same constraints.”
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The upgrade isn’t just that GPT-5 is a newer model. It brings a different caliber of intelligence to Copilot:
These improvements land harder in Flux because Copilot already has deep, live context on your design—down to parts, pins, nets, properties, constraints, and stackups—so reinforcement models and LLMs can work side-by-side from the canvas up to system architecture. And because Flux is built for agentic workflows—stepwise actions, constraint-aware edits, and iterative design loops right where you work—GPT-5 isn’t starting from scratch; it applies improved reasoning directly to your schematic or layout. Layered on top is a knowledge base of industry best practices and embedded design/process checks, so your AI partner starts from seasoned experience and turns that context into answers that are immediately relevant and actionable.
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In just 48 hours of testing, we saw moments that made us stop and say, “This is new.”
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In this case Flux took a plain-English prompt and produced a full low-noise mic preamp to a 24-bit ADC—calculating the right bias, gain, and filter values, choosing real parts, then placing and wiring the entire block with decoupling, VCM bias, and star-ground best practices. It even audited itself (fixed missed ties, made gain legs switchable). The result is a ready-to-review schematic 80% away from layout built end-to-end—complex, competent, and fast.
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Right now GPT-5 powers Copilot’s chat, but this is just the beginning. We’re already working on:
Open Flux now, switch Copilot to “Next-gen” and see how it handles your next design challenge. The sooner you try it, the more your feedback can shape the next leap in AI-powered hardware design.
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Arduino Nano R4 packs UNO R4 performance into Nano size. Learn specs, standout features, and who should upgrade in this in-depth guide.
The Arduino Nano R4 is a significant upgrade to Arduino’s popular Nano line, powered by the Renesas RA4M1 microcontroller. Imagine taking the powerful brains of the Arduino UNO R4 and shrinking them into a tiny, versatile form. With a 48 MHz Arm Cortex-M4F core, 256 KB of flash storage, and integrated EEPROM, the Nano R4 provides remarkable performance in a miniature footprint.
Regardless of whether you're prototyping, building IoT projects, or designing space-conscious hardware, the Nano R4 is designed to streamline your workflow and empower your creativity.
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The Nano R4 offers exciting new features, making it one of Arduino’s most attractive small boards ever released:
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Browse the shield templates below, each pre-aligned with headers, that let hardware engineers move from concept to working prototype in record time. Choose a template, customize it to your needs, and start building.
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Arduino Nano R4 keeps the classic Nano pin layout, so headers, shields, and breadboard wiring stay the same. Yes, just remap the pin numbers to match the Nano R4 layout. The Nano breakout connectors pinout is shown below:
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Nano R4 packs high-end functionality previously reserved for larger Arduino boards into a sleek, ultra-compact form factor. This allows makers to design more sophisticated, compact IoT and wearable projects without compromising power or features.
Already using Arduino’s popular UNO R4 boards? The Nano R4 offers complete compatibility with UNO R4’s software ecosystem, meaning your existing libraries, sketches, and workflows transfer smoothly to your Nano-sized projects.
The castellated headers and single-sided components ensure easy and cost-effective manufacturing—perfect for makers looking to transition prototypes into commercial products quickly and affordably.
The integrated Qwiic connector and additional I²C lines allow effortless integration of sensors, displays, and other peripherals. Add the RTC and RGB LED, and you have a remarkably versatile board ready for endless applications.
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The Nano R4 meets a variety of needs:
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Compared to older Nano models (Nano Every or Nano 33), the Nano R4 offers substantial performance and memory improvements:
The Nano R4 brings many of the features previously only available in higher-end Arduino boards into a Nano-sized form factor.
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If you're currently using older Nano boards or even an Arduino UNO, here are quick reasons to make the jump to Nano R4:
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The Arduino Nano R4 is available in two variations:
Both versions are available directly from Arduino's online store and major electronics distributors.
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Arduino’s Nano R4 sets a new standard for compact, powerful, and production-friendly microcontroller boards. Whether you’re prototyping the next big IoT device or scaling your prototype for production, the Nano R4 offers the power and flexibility you need.
Visit our Featured Projects page to discover innovative Arduino builds and spark inspiration for your next big idea.
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RP2350 A4 fixes GPIO bug, hardens security, adds 5 V tolerance and on-chip flash. See why every Pico project should migrate.
The RP2350 A4 stepping is the latest iteration of Raspberry Pi's powerful dual-core MCU, designed to correct significant hardware and security issues identified in earlier versions (particularly the A2 stepping). This update provides comprehensive improvements, delivering both enhanced security and optimized hardware performance, making it a must-have upgrade for serious developers and embedded systems designers alike.
If you're connecting the RP2350 to retro computing hardware, there's good news: after extensive testing, the RP2350 is now officially 5V tolerant!
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Absolutely! Because A4 is a pin-compatible, drop-in replacement, your existing Pico designs work right away, often with nothing more than a rebuild on the latest SDK. Here are four examples you can migrate today:
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You can identify the stepping version from the marking on the top surface of the chip, as illustrated below.
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No, great news for hardware engineers! The pin configuration and layout of the RP2350 A4 stepping remain identical to earlier versions, making it a perfect drop-in replacement. You can upgrade existing hardware designs without any modifications to your PCB layouts.
Below, I've included a detailed pinout mapping for quick reference.
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This stepping addresses several critical issues and introduces highly requested features:
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Raspberry Pi already stopped manufacturing the A2 stepping, shifted all production exclusively to A4, and removed remaining A2 inventory from distribution channels. The A4 stepping is a direct, drop-in replacement for A2, so you shouldn't encounter any issues transitioning to the newer version.
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Follow these simple steps to leverage the power of RP2350 A4 in your Raspberry Pi Pico projects:
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The RP2350 A4 stepping significantly upgrades the potential of Raspberry Pi Pico-based designs. Enhanced security, hardware reliability, simpler designs, and broad compatibility make this stepping a turning point for professional and hobbyist projects alike.
Explore our Featured Projects page to discover more Raspberry Pi projects and fresh ideas that will jump-start your next hardware prototype.
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Today, we’re excited to share our Summer Update to Flux AI Auto‑Layout, a collection of improvements designed to make one‑click PCB routing more reliable, transparent, and adaptable to your real‑world workflows.
This update is a set of pragmatic steps toward our vision of Auto‑Layout as your trusted routing assistant. Here's what's improved:
Auto‑Layout still works best when guided by thoughtful placement, clear net names, and rulesets—but now it’s a more predictable, collaborative partner in your design process.
Classify your nets into seven priority buckets—High Speed, Analog, Power, Medium Speed, Low Speed, Uncertain, and Ground—and Auto‑Layout will route them in that exact order. Flux will infer the Net Type of each net in your design, but you can check and change the inference by selecting a net and altering the Net Type property.
High‑speed nets go first.
Analog nets get their own quiet lanes.
Power nets find robust copper paths.
This helps ensure your most sensitive signals aren’t forced into awkward detours, delivering a draft layout that mirrors your own routing instincts.
Previous versions of Flux Auto‑Layout often scrunched traces up against neighboring pads or nets to minimize length. We’ve softened that bias so traces now favor open board areas—even if they grow a few mils longer.
Think of it as trading a few extra mils for a huge win in clarity and yield.
Earlier, Auto‑Layout could inadvertently slice through copper pours—especially smaller ones. Now, any polygon covering less than 10% of the board area is automatically protected from wires and vias unless you explicitly disable that rule.
Auto‑Layout shines when you guide it. Here’s a quick workflow that scales from beginners to power users:
Either way, Auto‑Layout becomes a force multiplier—not a replacement for your expertise.
This Summer Update is a milestone on our roadmap. In the coming months, expect deeper AI understanding of complex topologies, tighter integration with constraint management, and collaborative features that let teams iterate on one layout in real time.
Your feedback is the compass that guides us. Try the Summer Update today—log in, hit “Auto‑Layout”, and tell us where it shined or stumbled via in‑app feedback or our Slack channel. Together, let’s make routing the easiest part of hardware design.
In this post, we’ll show you exactly how to unlock the power of Flux Copilot for yourself: from writing rock-solid triggers to scoping entries at the project, user, and system levels.
Today, EE teams using Flux are already leveraging Knowledge Base to encode their professional know-how—things like project constraints, personal style guides, and industry-vetted best practices—directly into Copilot. In this post, we’ll show you exactly how to unlock that power for yourself: from writing rock-solid triggers to scoping entries at the project, user, and system levels.
Don’t miss out on this opportunity. Take these tips and tricks, apply them today, and watch Copilot transform from a tool into a teammate who thinks—and designs—just like you.
With Knowledge Base, we capture insights at three levels:
Let’s dive into how it works, why it matters, and—most importantly—how you can craft entries that make Copilot truly think like you.
Flux Copilot’s Knowledge Base entries can be thought of at four levels—from narrow rules to high-level mindsets. When you prompt Copilot, it performs a semantic search, a search that uses sentence structure similarity to find matches , then weaves the most relevant guidance into its reasoning.
Every entry begins with a “use when” phrase. Copilot uses vector search, finding similar items in a dataset by comparing their numerical vector representations (embeddings) instead of relying on exact keyword matches, to match your prompt to the right piece of advice based on semantic similarity.
When you ask Copilot, for example, to generate a buck-converter schematic, it retrieves relevant entries—your project’s input-voltage constraint, your favorite inductor series, or a net-naming rule—and seamlessly injects that context into its response.
The “use when” is the most critical piece of any entry—it tells Copilot when to apply your guidance, based on semantic similarity, not just keywords. If this is off, your advice will never—or always—fire.
Pro Tip: After Copilot suggests a “use when,” refine it immediately. A small tweak—“for high-speed analog filters” instead of just “for filters”—can mean perfect recall instead of irrelevant noise.
Project-level entries store all the details that make your current board design one-of-a-kind. They include specific requirements (like voltage tolerances), physical or thermal constraints, chosen topology decisions, and any reference calculations you’ve performed. By capturing the reasoning behind each architectural choice, Copilot can apply context-aware guidance tailored solely to this project. This prevents generic suggestions from slipping through and keeps your design aligned with its unique specifications.
use when: selecting temperature sensitive components
content: this design is exposed to temperatures of -10 F to 110 F on a Northeastern US State yearly temperature cycle.
use when: board size constraints
content: Ensure components selected are optimized for a wearable device sized board.
use when: designing a power distribution network
content: Optimize for small size and effeciency for each power component.
User-level entries capture your personal design preferences, workflows, and preferred subcircuit patterns so that Copilot reflects how you work. They let you encode procedural steps—like your favorite LDO selection or filter-design process—directly into Copilot’s memory. With these entries, Copilot adopts your schematic conventions, part choices, and step-by-step habits, producing outputs that feel tailored and familiar. In effect, it transforms Copilot from a generic assistant into one that thinks and advises just as you would.
use when: LDO selection process
content: When selecting an LDO, follow a structured four-step workflow: screen basic parameters, filter performance (PSRR, noise), prioritize the key metric, and check optional features.
use when: filter design process
content: When formalizing filter design, begin with clear specs (ripple, f_c, f_s, attenuation) and then proceed with topology selection, component choice, simulation, and disciplined prototyping.
use when: naming nets for differential pairs
content: Prefix with SIG_DP_ or SIG_DM_ and suffix with _N/_P for polarity clarity.
use when: naming nets with series resistors
content: Add a suffix _R to the name of the incoming net to the resistor and use it for the outgoing net name.
use when: designing op-amp instrumentation amplifiers
content: Add 10 Ω series resistors on each input to decouple source capacitance.
use when: using TI SN65HVD230 CAN transceiver
content: Place 120 Ω termination resistors close to the transceiver and add 0.1 µF decoupling on VCC.
Our EE team crafts system entries with the highest rigor—so every user benefits from vetted best practices.
Note: Every word is chosen deliberately—“use when” must be as true as the “content” it triggers.
As your KB grows, keep it relevant and helpful by:
Adding your knowledge to Copilot doesn’t just make it smarter—it makes you faster, more consistent, and more confident. Open Flux Copilot, watch for that “Knowledge Suggestion” button in the response, and begin teaching your AI teammate how you design. Over time, your Knowledge Base becomes a living encyclopedia of your best practices—project by project, decision by decision.
