# Introducing Copilot Knowledge Base for Flux Engineers Discover how to unlock Flux Copilot’s full power by building a custom Knowledge Base with your design rules, constraints, and best practices. Written by [Ryan Fitzgerald](https://www.flux.ai/ryanf) Published Jul 2025 - 6 min read [![](https://www.flux.ai/p/assets/blogs/how-to-transfer-your-knowledge-to-copilot/main.webp)](#) ## Designing hardware is complex—and every credit and cycle counts. With Copilot Knowledge Base, you can not only **boost Copilot’s accuracy** but also **speed up your designs** and **waste far fewer credits** chasing avoidable mistakes. 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](https://www.flux.ai/p/blog/teach-copilot-how-you-work-with-knowledge), we capture insights at three levels: - **Project-level**: Requirements, calculations, and architecture choices unique to your current board - **User-level**: Your personal style guides, part-family preferences, and schematic conventions - **System-level**: Flux-curated best practices and EE-expert recommendations that benefit everyone 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**. ### 1\. How the Knowledge Base Works & Why It Matters 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. [![The four levels of Flux Copilot knowledge base entry](https://www.flux.ai/p/assets/blogs/how-to-transfer-your-knowledge-to-copilot/four-levels-of-knowledge-base-entry.webp)](#) #### Semantic Triggers 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. #### Context Injection 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. #### Three-Tier Scope - [Project](https://docs.flux.ai/reference/knowledge-base#project-level-knowledge): Active only within the board you’re editing - [User](https://docs.flux.ai/reference/knowledge-base#user-level-knowledge): Applies across all your Flux projects - **System**: Flux-approved, peer-reviewed EE best practices #### Impact & Examples of Good Results [![A electronics engineer prompting Flux copilot for help designing a buck converter and low drop out voltage regulator](https://www.flux.ai/p/assets/blogs/how-to-transfer-your-knowledge-to-copilot/design-a-buck-converter-and-LDO.webp)](#) ### 2\. Crafting Effective “Use When” Statements The **“**[**use when**](https://docs.flux.ai/reference/knowledge-base#getting-started-with-knowledge)**”** 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. - **Keep it short** (6–9 words) - **Lead with your key concept** (noun or verb first) - **Be 100% true** to the context you’re capturing - **Use action verbs** (e.g. *designing*, *validating*, *calculating*) - **Broad vs. Specific**: - - Broad: use when: filtering power rails - Specific: use when: designing Pi filters for multi stage power rail > 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. ### 3\. Project-Level Knowledge (with Examples) 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. - **Design requirements** *Example:* > 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. - **Design constraints** *Example:* > use when: board size constraints > content: Ensure components selected are optimized for a wearable device sized board. - **Architecture decisions** *Example:* > use when: designing a power distribution network > content: Optimize for small size and effeciency for each power component. ### 4\. User-Level Knowledge (with Examples) 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. - **Procedural instructions** *LDO selection* > 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. - *Filter design* > 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. - **Schematic style guidelines** *Example 1:* > use when: naming nets for differential pairs   > content: Prefix with SIG\_DP\_ or SIG\_DM\_ and suffix with \_N/\_P for polarity clarity.   - *Example 2:* > 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.   - **Tips for specialized circuits** *Example:* > use when: designing op-amp instrumentation amplifiers   > content: Add 10 Ω series resistors on each input to decouple source capacitance.   - **Component-specific instructions** *Example:* > 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. ### 5\. System-Level Knowledge (How We Build It) Our EE team crafts **system entries** with the highest rigor—so every user benefits from vetted best practices. 1. **Source & Draft**‍ - Extracted from whitepapers, application notes, and our expert’s experience**‍** 2. **Peer Review**‍ - Our team of senior engineers validate technical accuracy and remove any vendor bias**‍** 3. **Semantic Validation**‍ - We test “use when” triggers against hundreds of prompt variations to ensure relevance > Note > > Every word is chosen deliberately—“use when” must be as true as the “content” it triggers. ### 6\. Managing Your Knowledge Base As your [KB grows](https://docs.flux.ai/reference/knowledge-base#example-use-cases), keep it relevant and helpful by: 1. **Watching Scopes**‍ - ✅ Don’t mix project-specific facts into user-level entries**‍** - **Edit user entries**: Profile → Knowledge → User Knowledge**‍** - **Edit project entries**: Project → Knowledge → Project Knowledge**‍** 2. **Monitoring Performance**‍ - Hit the **👎 thumbs-down** when Copilot misapplies an entry or forms a bad response - Identify entries causing loops: “Why does it always suggest the same value for an inductor?”**‍** 3. **Signs of Harmful Entries** - **Over-fixation**: Copilot insists on one solution for every design**‍** - **Inaccuracies**: Obvious part-selection errors or illogical guidance**‍** 4. **Regular Audits**‍ - Periodically review and prune outdated or narrow entries - Elevate broadly useful user entries to system level for team-wide benefit ### Start Building Your KB Today Adding your knowledge to Copilot doesn’t just make it smarter—it makes **you** faster, more consistent, and more confident. [Open Flux Copilot](https://flux.ai/), 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. ## About the author [Ryan Fitzgerald](https://www.flux.ai/ryanf) Electronics Engineer at Flux Ryan is an electronics and electrical systems engineer with a focus on bridging the gap between deep learning intelligent algorithms and innovative hardware design. Find him on Flux [@ryanf](https://www.flux.ai/ryanf) 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. 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[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)