# Flux Copilot: Under the Hood Flux Copilot transforms PCB design by combining LLMs in hardware with real-time part data and design insights. Written by [Nico Tzovanis](https://www.flux.ai/nico) Published Jun 2025 - 8 min read [![Flux copilot under the hood - an AI agent with access to real tools, structured data, and your active design context. Because it understands your schematic — the parts you’ve used, their interconnections, net names, designators, and annotations — it can reason about your design. ](https://www.flux.ai/p/assets/blogs/flux-copilot-under-the-hood/main.webp)](#) ## What if you could turn an idea into a manufacturable circuit board — just by describing what you want? That’s the vision behind Flux Copilot. But to get from where we are today to that future, we need more than just a powerful tool. We need people who understand how to use it well — and help us shape what comes next. This post will give you a deeper understanding of how Copilot works, how large language models (LLMs) and agentic systems operate under the hood, and why grounding them in engineering context matters. You'll walk away with concrete strategies to get better results — and a clearer sense of how your feedback can shape the future of AI-assisted design. ### The Gap Between AI Hype and Reality **If you've ever used an AI tool and felt disappointed, you're not alone. Engineers expect precision, and sometimes get something unpredictable**. However, that doesn’t mean AI is overhyped. Rather, it means AI is evolving, and we need to learn how to work with it. AI — especially large language models — is already an incredibly powerful tool. It can synthesize knowledge from thousands of documents, surface insights instantly, and assist in real-time decision-making. But like any tool, it needs to be used correctly. Understanding how it works helps you unlock its full potential. That’s why we’re writing this. The more you understand how Flux Copilot works under the hood, the more empowered you’ll be to use it effectively, and help shape what it becomes. ### How LLMs Work (and What Makes Copilot Different) At the core of Copilot is a large language model (LLM) — a deep neural network trained on massive datasets to predict the next token in a sequence. In practice, this means it can understand natural language prompts, reason across technical contexts, and generate structured responses. **LLMs aren't "search engines" or "knowledge bases." They don’t retrieve information, they generate it, based on patterns learned during training.** This is both their power and their risk: they can generalize across domains and produce fluent output, but they can also produce confident-sounding nonsense — what we call hallucinations. That’s why Copilot isn’t just a raw LLM. It’s an LLM grounded in structured, trustworthy data: - Your active design: schematics, PCB, parts, netlist - Our 750K+ part library, complete with datasheets and metadata - Context from the Flux editor (mouse focus, selection, properties, descriptions, etc.) - [Copilot Knowledge](https://www.flux.ai/p/blog/teach-copilot-how-you-work-with-knowledge), which encodes your preferences and reusable logic. It’s also being constantly updated by Flux experts and professional electrical engineers, making Copilot smarter everyday. [![](https://www.flux.ai/p/assets/blogs/flux-copilot-under-the-hood/image-1.webp)](#) By combining generative reasoning with factual, contextual inputs, we reduce hallucinations and increase the reliability of Copilot’s suggestions. But it's not bulletproof. It can still generate plausible-sounding errors if the grounding data is missing, incomplete, or misinterpreted. ### How Copilot Works Copilot isn't operating in a vacuum. It's more than just an LLM generating text — it's an AI agent with access to real tools, structured data, and your active design context. Because it understands your schematic — the parts you’ve used, their interconnections, net names, designators, and annotations — it can reason about your design. [![](https://www.flux.ai/p/assets/blogs/flux-copilot-under-the-hood/image-2.webp)](#) Under the hood, Copilot is connected to a series of tightly integrated tools, each exposing a specific capability: - [Library Tool:](https://docs.flux.ai/reference/library-tool) Copilot can search Flux’s part library — over 750,000 components — and return results filtered by function, footprint, specs, availability, or manufacturer. When you ask for a part, it’s not guessing from memory; it’s querying a live, structured catalog. - [Calculator Tool](https://docs.flux.ai/reference/calculator-tool): For tasks involving math — whether it’s computing a power budget, estimating voltage drops, or calculating decoupling values — Copilot uses a dedicated calculator that handles unit conversions and component-specific formulas. - [Code Interpreter](https://docs.flux.ai/reference/code-tool): When analytical tasks require logic or visualization (e.g. generating a filter response curve, performing statistical tolerance analysis, or plotting a charging profile), Copilot can write and execute Python code using an isolated interpreter. This adds a layer of precision and repeatability you won't get from a standard LLM. Together, these tools give Copilot the ability to behave more like a true assistant with systems-level access — not just a text generator. This kind of functionality bridges the gap between assistant and collaborator. It’s what makes Copilot feel less like a chatbot and more like a teammate. An AI engineer that doesn’t just explain what to do — but starts doing it. And because Copilot isn’t just responding in a chat bubble — it's connected to your active design — it can take actions: edit the schematic, add components, modify net connections, and flag inconsistencies. ### Why It Sometimes Gets It Wrong LLMs are generative. They don’t pull facts from a database — they generate answers word by word, based on statistical likelihood. This means they can *hallucinate*: confidently stating something that sounds plausible but is completely false. In hardware design, hallucinations can show up as incorrect pin mappings, wrong default values, or oversimplified assumptions. This can lead to real mistakes if the user isn’t validating what Copilot outputs. **While Copilot can take actions inside your project — like editing schematics or inserting parts — some actions may succeed, others may only partially complete**, and some prompts might be misunderstood altogether. This is especially true in more complex scenarios, where multiple steps or system-level understanding is needed. The goal is a seamless experience where intent leads to correct execution, but today, users should still expect to guide and verify every step. Grounding Copilot in real data — through datasheets, project context, and part metadata — helps reduce these risks. But it doesn’t eliminate them. The model might overlook a constraint, misread a spec, or provide a solution that looks reasonable but doesn’t work in practice. It’s essential to treat Copilot as you would a new team member: capable, fast, but not infallible. Always review its suggestions. Provide feedback. Ask clarifying follow-ups. That interaction is what turns AI into a truly useful design partner. We’re also actively working on helping Copilot surface uncertainty — so it can tell you when it’s guessing, and explain what it's basing its answers on (or what information it lacks). ### How to Get Better Results Using Copilot effectively is less about being technical and more about being clear. It’s like working with a new hire who’s smart but unfamiliar with your preferences. The more context you give it, the better it performs. If you’re looking for a regulator, don’t just say “add an LDO.” Try something like: > “Suggest a 3.3V LDO for an ESP32 with <100uA quiescent current and SOT-23 footprint.” That level of detail dramatically increases the relevance of the result. And because Copilot sees your schematic, you can ask things like: > “Which nets are missing decoupling capacitors?” > “Wire up a power tree for these ICs.” > “Add pull-ups to all I²C lines.” These are tasks that might take you 10–15 minutes. Copilot can do them in seconds — not because it knows better than you, but because it has access to the same information and applies it faster. You can also refine prompts through iteration. If a response misses the mark, say: > “That’s too high power — optimize for <10mA draw,” or > “I’d prefer a Texas Instruments part here.” Copilot remembers the context of your project and previous replies. Treat it like an interactive design partner, not a search engine. Getting better results with Copilot’s action-taking features — especially for part insertion and wiring — requires a bit of strategy. When asking Copilot to add parts, keep your request scoped to a small, related group of components. For example, instead of saying > “add a power supply,” try > “Add an 500mA 3.3V linear regulator with a ceramic input capacitor and output capacitors,” This helps Copilot reason about the function and relationships between components. Similarly, when wiring things up, ask Copilot to connect two or three components at a time — like wiring up a sensor to a microcontroller with the necessary pull-ups — rather than asking it to connect an entire subsystem in one go. This makes the task more manageable, and improves the accuracy and completeness of the result. And when it comes to reviewing your work, Copilot can already identify common mistakes, missing components, or inconsistent naming. As we continue building, that design review capability will become even more comprehensive — combining simulation, datasheet validation, and layout context. ### The Vision: Prompt → PCB Everything we’ve shown so far — contextual understanding, structured reasoning, agentic actions — is just the beginning. The real goal is to make hardware design more fluid, iterative, and collaborative. We’re building toward a future where describing what you want is enough to begin the design process. Where Flux Copilot understands your intent, accounts for constraints, and takes meaningful steps forward — not just by suggesting, but by executing. Imagine typing: > “Design a BLE-enabled temperature sensor with 6-month battery life. Optimize for low power.” And Copilot delivers: - A schematic tailored to your requirements - Part suggestions with sourcing in mind - A block diagram - A BOM with pricing - A breakdown of assumptions and trade-offs This isn’t sci-fi. It’s the direction we’re actively building toward — and your feedback plays a big role in making it real. ### Join the Journey Copilot improves fastest when it’s used by real engineers solving real problems. Here’s how you can help: Give feedback — What did Copilot do well? Where did it fall short? Be specific. Train it — Add your naming rules, preferred suppliers, or circuit patterns to Copilot Knowledge. Push it — Ask for things you wish it could do. Even if it can’t yet, your input helps shape what we build next. You're not just using a tool. You’re helping define what engineering looks like when AI becomes part of the workflow. Let’s build it together. ## About the author [Nico Tzovanis](https://www.flux.ai/nico) Nico is a professional electronics and PCB design engineer at Flux. Find him on Flux [@nico](https://www.flux.ai/nico) Let’s start building Build your big idea together with Flux. All you need to do is describe what you want to make, or what problem you want to solve. Flux will work with you to make it a reality. ![Close-up photo of a PCB made with Flux, with an ESP32 module, buttons, and a microSD slot.](https://www.flux.ai/p/assets/blogs/miscellaneous/sidebar-cta-pcb.webp) [Try it Free](https://www.flux.ai/signup) ## More in AI & Prompt Engineering for Hardware [ ![What Makes a Perfect PCB Design Prompt](https://www.flux.ai/p/assets/blogs/how-to-write-a-perfect-pcb-design-prompt/main.webp) ### What Makes a Perfect PCB Design Prompt 8 Min Read](https://www.flux.ai/p/blog/what-makes-a-perfect-pcb-design-prompt)[ ![Flux, an AI hardware engineer pointing out the dos and don'ts when prompting.](https://www.flux.ai/p/assets/blogs/prompting-guide/main.webp) ### Prompting Guide: Working with Flux from Idea to Schematic 9 Min Read](https://www.flux.ai/p/blog/prompting-guide-working-with-flux-from-idea-to-schematic)[ ![A space-themed image with a central cartoon astronaut helmet against a backdrop of stars and nebulae in shades of purple. Surrounding the helmet are eight speech bubbles with text relating to electronic design considerations, such as 'Review unconnected pins,' 'Check my design for errors,' and 'Radiation Hardness.' A ninth bubble says 'Share Review Template,' with a share icon.](https://www.flux.ai/p/assets/blogs/ai-design-reviews/main.webp) ### AI Design Reviews 6 Min Read](https://www.flux.ai/p/blog/ai-design-reviews)[ ![5 Pro Tips for Better Routing with AI Auto-Layout](https://www.flux.ai/p/assets/blogs/5-tips-for-ai-auto-layout/main.webp) ### 5 Pro Tips for Better Routing with AI Auto-Layout 5 Min Read](https://www.flux.ai/p/blog/5-pro-tips-for-better-routing-with-ai-auto-layout)[ ![Top 20+ Flux Copilot Prompts for Hardware Design](https://www.flux.ai/p/assets/blogs/top-copilot-prompts-2/main.webp) ### Top 20+ Flux Copilot Prompts for Hardware Design 9 Min Read](https://www.flux.ai/p/blog/top-20-flux-copilot-prompts-for-hardware-design)[ ![More than 20 amazing Flux Copilot prompts on a starry background](https://www.flux.ai/p/assets/blogs/top-copilot-prompts/main.webp) ### 20+ Amazing Flux Copilot Prompts for Hardware Design 5 Min Read](https://www.flux.ai/p/blog/amazing-flux-copilot-prompts)[ ![Top 20+ Flux Copilot Prompts (Refreshed)](https://www.flux.ai/p/assets/blogs/top-copilot-prompts-3/main.webp) ### Top 20+ Flux Copilot Prompts (Refreshed) 7 Min Read](https://www.flux.ai/p/blog/top-20-flux-copilot-prompts-refreshed)[ ![a space-themed background with stars and a floating astronaut helmet to the left. Large, bold text reads '6 Prompting Tips to Get the Most Out of Copilot', indicating a focus on maximizing the use of a digital assistant or tool.](https://www.flux.ai/p/assets/blogs/copilot-6-prompting-tips/main.webp) ### 6 Prompting Tips to Get the Most Out of Copilot 6 Min Read](https://www.flux.ai/p/blog/6-prompting-tips-to-get-the-most-out-of-copilot)[ ![Graphic showing a red printed circuit board design with a list of common asked questions in Flux, such as overlapping copper and missing footprints. Based on the most common questions we hear from our users, it walks through practical solutions to unblock your designs and give you more confidence as you build.](https://www.flux.ai/p/assets/blogs/top-10-troubleshooting-tips-n-tricks/main.webp) ### Top 9 Most Asked Questions in Flux 6 Min Read](https://www.flux.ai/p/blog/top-9-most-asked-questions-in-flux)[ ![A screen that looks like the part of a game where you choose your character. Except the characters are different helmets, representing how Copilot can change for each application. The categories are Aerospace, Edge Computing, UAV, Telecom, Robotics, Audio, Marine and Defense](https://www.flux.ai/p/assets/blogs/copilot-templates/main.webp) ### Flux Copilot Can Adapt To Your Objectives 4 Min Read](https://www.flux.ai/p/blog/flux-copilot-ai-hardware-assistant-adapts-to-your-requirements)[ ![Design Circuits with Natural Language: Copilot Upgrade](https://www.flux.ai/p/assets/blogs/copilot-takes-action/main.webp) ### Design Circuits with Natural Language: Copilot Upgrade 6 Min Read](https://www.flux.ai/p/blog/design-circuits-with-natural-language-copilot-upgrade)[ ![Flux Copilot can learn how you work—your design principles, part selection preferences, schematic, and testing workflows—and remember them automatically](https://www.flux.ai/p/assets/blogs/copilot-knowledge/main.webp) ### Teach Copilot How You Work with Knowledge 4 Min Read](https://www.flux.ai/p/blog/teach-copilot-how-you-work-with-knowledge)[ ![The First AI Hardware Engineer](https://www.flux.ai/p/assets/blogs/first-ai-hardware-engineering-intern/main.webp) ### The First AI Hardware Engineer 5 Min Read](https://www.flux.ai/p/blog/the-first-ai-hardware-engineer)[ ![A schematic diagram of a project on Flux showing an electrical engineer accessing the Copilot shortcut](https://www.flux.ai/p/assets/blogs/ai_shortcut/main.webp) ### AI Shortcuts for PCB Design 2 Min Read](https://www.flux.ai/p/blog/ai-shortcuts-for-pcb-design)[ ![Flux Copilot’s faster workflows with the new AI-first UI](https://www.flux.ai/p/assets/blogs/new-ai-first-ui/main.webp) ### Less Clicking, More Building: The New AI-First UI 4 Min Read](https://www.flux.ai/p/blog/less-clicking-more-building-the-new-ai-first-ui)[ ![Screenshot of a PCB design tool showing an AI-powered review panel. The review panel highlights capacitor C56 with a red error indicating a voltage rating of 16V, below the required safe margin. A chat response suggests replacement capacitors with part numbers, demonstrating the AI's capability to recommend fixes for flagged issues.](https://www.flux.ai/p/assets/blogs/ai-drc-panel/main.webp) ### Introducing the AI Design Review Tab 4 Min Read](https://www.flux.ai/p/blog/introducing-the-ai-design-review-tab)[ ![Flux Copilot - The First AI Powered Hardware Design Assistant can now route your PCB. Introducing AI Auto-Layout. With just one click, Copilot tackles the repetitive task of routing your board, delivering clean, human-like results that are easy to work with and iterate on.](https://www.flux.ai/p/assets/blogs/ai-auto-layout-v1/main.webp) ### Introducing AI Auto-Layout 4 Min Read](https://www.flux.ai/p/blog/introducing-ai-auto-layout)[ ![Flux Copilot astronaut points at a PCB with the text “Smarter AI Auto‑Layout” overlaid, highlighting the intelligence of Flux’s AI Auto‑Layout feature.](https://www.flux.ai/p/assets/blogs/ai-auto-layout-summer-update/main.webp) ### AI Auto-Layout Just Got Smarter 3 Min Read](https://www.flux.ai/p/blog/ai-auto-layout-just-got-smarter)[ ![An astronaut placing electronics components and tracing complex signals on a complex glowing PCB board.](https://www.flux.ai/p/assets/blogs/ai-auto-layout-v2/main.webp) ### AI Auto-Layout Winter Update 9 Min Read](https://www.flux.ai/p/blog/ai-auto-layout-winter-update)[ ![Flux Copilot suspended in space, intellegently scanning electronic components datasheets](https://www.flux.ai/p/assets/blogs/ditch-datasheets/main.webp) ### Ditch Datasheets with this Flux Copilot Upgrade 2 Min Read](https://www.flux.ai/p/blog/ditch-datasheets-with-this-flux-copilot-upgrade)[ ![Illustration of an astronaut helmet superimposed over a circuit board background, stylized as 'Flux Copilot Vision.' The helmet is detailed with a prominent, reflective visor in shades of purple and white, with a simplified antenna on the side, set against a complex pattern of digital circuits and glowing nodes. This is Copilot Vision, first multi-modal AI for hardware design for electronics and PCB engineers](https://www.flux.ai/p/assets/blogs/copilot_vision/main.webp) ### Flux Copilot Can Now See 3 Min Read](https://www.flux.ai/p/blog/copilot-can-now-see)[ ![Flux copilot writing and optimizing a firmware code of an electronic project](https://www.flux.ai/p/assets/blogs/firmware-productivity-with-ai/main.webp) ### AI for Firmware Development: How to Code Firmware Faster 3 Min Read](https://www.flux.ai/p/blog/code-firmware-faster-with-ai)[ ![Research Components Faster with AI](https://www.flux.ai/p/assets/blogs/ai-component-selection/main.webp) ### Research Components Faster with AI 5 Min Read](https://www.flux.ai/p/blog/research-components-faster-with-ai)[ ![Flux copilot, a hardware design assistant is responding to a user request to provide him drop-in replacement for an electronic component in his project. Behind is a complicated realistic printed circuit board.](https://www.flux.ai/p/assets/blogs/streamline-component-research-with-ai/main.webp) ### Streamline Component Research with AI 2 Min Read](https://www.flux.ai/p/blog/streamline-component-research-with-ai)[ ![Instant Hardware Analysis with AI: Meet Copilot's Code Interpreter](https://www.flux.ai/p/assets/blogs/code-interpreter/main.webp) ### Instant Hardware Analysis with AI: Meet Copilot's Code Interpreter 4 Min Read](https://www.flux.ai/p/blog/instant-hardware-analysis-with-ai-meet-copilots-code-interpreter)[ ![This image displays a sophisticated electronics testing setup. In the foreground, a person's hand holds a probe connected to a circuit board densely populated with various electronic components. The background features an oscilloscope screen showing waveform outputs and a digital meter displaying the number 0.95. A digital overlay on the image presents a test plan for signal integrity checks, listing steps such as confirming a voltage level of 3.3V, checking for a PWM signal at 1 kHz, and ensuring zero voltage (ground). The layout emphasizes precision and methodical testing in electronic design and development.](https://www.flux.ai/p/assets/blogs/ai-electronic-testing-and-debugging/main.webp) ### AI for Electronics Testing and Debugging 3 Min Read](https://www.flux.ai/p/blog/ai-for-electronics-testing-and-debugging)[ ![A hardware design assistant wearing a spacesuit helmet, automatically reading test points in a complex printed circuit board and doing design analysis](https://www.flux.ai/p/assets/blogs/ai-functional-testing/main.webp) ### AI for Functional Testing 4 Min Read](https://www.flux.ai/p/blog/ai-for-functional-testing)[ ![AI design assistant named Copilot wearing a space helmet is scanning an electronic schematic diagram to optimize for production total cost by looking at every single electronic components, stackup configuration and packages](https://www.flux.ai/p/assets/blogs/ai-driven-cost-optimization/main.webp) ### AI-Driven PCB Cost Optimization 4 Min Read](https://www.flux.ai/p/blog/ai-driven-pcb-cost-optimization)[ ![Simulate Circuits with a Prompt](https://www.flux.ai/p/assets/blogs/simulate-circuits-with-a-prompt/main.webp) ### Simulate Circuits with a Prompt 5 Min Read](https://www.flux.ai/p/blog/simulate-circuits-with-a-prompt)[ ![Meet Files: AI-Native Project Documentation](https://www.flux.ai/p/assets/blogs/meet-files-ai-native-project-documentation/main.webp) ### Meet Files: AI-Native Project Documentation 5 Min Read](https://www.flux.ai/p/blog/meet-files-ai-native-project-documentation)[ ![An illustration showing AI-driven PCB design workflows with automated routing and placement optimization](https://www.flux.ai/p/assets/blogs/how-ai-is-changing-pcb-design/main.webp) ### How AI Is Changing PCB Design 11 Min Read](https://www.flux.ai/p/blog/how-ai-is-changing-pcb-design)[ ![A screenshot displaying the Flux Copilot Chat dialog box on a computer screen, featuring a selection of specialized AI models, each uniquely tailored for various aspects of hardware design.](https://www.flux.ai/p/assets/blogs/copilot_got_smarter/main.webp) ### Flux Copilot Just Got Smarter 2 Min Read](https://www.flux.ai/p/blog/flux-copilot-just-got-smarter)[ ![An astronaut in silhouette stands on a ledge, gazing at stars and planets that resemble electronic circuits, imagining the endless possibilities Flux Copilot offers in realizing his dream](https://www.flux.ai/p/assets/blogs/future-of-copilot/main.webp) ### The Future of Flux Copilot 5 Min Read](https://www.flux.ai/p/blog/the-future-of-flux-copilot)[ ![Flux Copilot is creating a block diagram or architectural diagram of an electronic PCB project](https://www.flux.ai/p/assets/blogs/ai-powered-architecture-design/main.webp) ### AI-Powered Architecture Design 4 Min Read](https://www.flux.ai/p/blog/ai-powered-architecture-design)[ ![An illustration of astronaut helmet spacesuit suspended in space.](https://www.flux.ai/p/assets/blogs/copilot_v1/main.webp) ### Flux Copilot - The First AI Powered Hardware Design Assistant 8 Min Read](https://www.flux.ai/p/blog/flux-copilot-the-first-ai-powered-hardware-design-assistant)[ ![A schematic diagram with two integrated circuit symbols with a message bubble above it, featuring Copilot AI hardware assistant](https://www.flux.ai/p/assets/blogs/generative-ai-for-hardware-design/main.webp) ### Generative AI for Hardware Design 3 Min Read](https://www.flux.ai/p/blog/generative-ai-for-hardware-design)[ ![Flux copilot optimizing the initial phase of hardware development process](https://www.flux.ai/p/assets/blogs/ai-research-and-planning/main.webp) ### AI Research & Planning 5 Min Read](https://www.flux.ai/p/blog/ai-research-planning)[ ![Flux copilot just got smarter, cleaner layouts, fewer bugs. An astronaut traversing the galaxy having full control.](https://www.flux.ai/p/assets/blogs/copilot-getting-smarter/main.webp) ### Smarter Copilot, Cleaner Layouts, Fewer Bugs 2 Min Read](https://www.flux.ai/p/blog/smarter-copilot-cleaner-layouts-fewer-bugs)[ ![Introducing Copilot Knowledge Base for Flux Engineers](https://www.flux.ai/p/assets/blogs/how-to-transfer-your-knowledge-to-copilot/main.webp) ### Introducing Copilot Knowledge Base for Flux Engineers 6 Min Read](https://www.flux.ai/p/blog/introducing-copilot-knowledge-base-for-flux-engineers)[ ![Flux + GPT-5 (Beta)](https://www.flux.ai/p/assets/blogs/flux-and-gpt-5/main.webp) ### Flux + GPT-5 (Beta) 4 Min Read](https://www.flux.ai/p/blog/flux-gpt-5-beta)[ ![Design hardware in the fast lane with Flux's new steerable agent](https://www.flux.ai/p/assets/blogs/new-steerable-hardware-agent/main.webp) ### Design hardware in the fast lane with Flux's new steerable agent 3 Min Read](https://www.flux.ai/p/blog/new-steerable-hardware-agent) See All (41) ## Let’s start building. Let’s build your idea together. All you need to do is describe what you want to make, or what problem you want to solve. Flux will work with you to make it a reality. [Try it Free](https://www.flux.ai/signup) ![Close-up of a Flux-designed printed circuit board](https://www.flux.ai/p/assets/homepage-v2/mission-visual.webp)