AI, AI, AI... can we stop talking about it?

On one side of the coin, artificial intelligence (AI) can make images, sound, and video — a final product presented by the user as if they made it. On the flipside of that coin, AI is able to make code, solve problems, analyze, automate, process and parse data — the user creates a machine that performs work or produces an output, invisible in relation to the final product they present.  

I think we engineers have a unique and healthy relationship with AI. We’re asked to create a “thing” that does “something.” AI is at the core of that “thing,” helping it do “something.” AI is not the “thing” but how it does the “something.”  

Let me give an example. I made a washing machine sensor device that measures vibration and sends a text message when that behavior changes. I spent about a month developing the circuit, build, and code for it. I ported this idea to a few other platforms, too, which also took quite a bit of time. 

Then NanoEdge AI Studio from STMicroelectronics came along. The company built a similar system in about 30 minutes. If I had NanoEdge AI Studio, I would have a month of my life back, and I would have made the same vibration sensing device. 

The code or design files we let AI generate aren’t going into galleries or presented as artwork. It’s a means to an end. I suppose I could claim I’m the next Nikola Tesla and pretend everything I AI-generate is my handcrafted work. I’m not. I’m generating a machine that does work.  

Am I giving the OK to use AI on the job? I would say it’s time to augment your engineers’ prowess. There are AI-laden tools for just about every nuance of the job. Everything is about to get easier after you see the following list. Will this collection of tools make you a better engineer or a lazy one? 

Either way, enjoy this reference cheat sheet.

Circuit Design, Simulation, and Electronics Prototyping 

• CELUS focuses on electronic design automation by helping translate product requirements into component choices, schematic blocks, and manufacturable design starting points.
• Circ AI turns circuit ideas and SPICE-style inputs into browser-ready designs that can be simulated, adjusted, and exported without setting up a local EDA environment.
• Circuit Mind helps engineers move from system requirements to workable circuit concepts by generating schematics and bill-of-materials options early in the design process.
• Cirkit Designer gives students and makers a visual way to build and test circuits online, making it useful for learning electronics without needing every physical component on hand.
• Flux AI is a collaborative electronics design workspace that brings schematic capture, PCB layout, simulation, and AI-guided design help into one browser-based tool.
• NI Multisim Live + AI Assist gives students and engineers a browser-based SPICE environment for building, testing, sharing, and learning from circuits before committing to physical hardware.
• Proteus Design Suite combines schematic capture, microcontroller simulation, PCB layout, and newer AI-aware design support, making it especially useful for embedded electronics projects that need both circuit and firmware testing.

PCB Layout, Routing, and Board Optimization 

• Altium Designer with AI Assistants brings schematic design, PCB layout, simulation, documentation, and design-data management into a unified professional environment that can be extended with AI-supported review, research, and workflow assistance.
• DeepPCB is aimed at PCB auto-routing, using AI to help reduce tedious manual layout work while improving board-routing efficiency.
• KiCad AI Plugins extend the open-source KiCad ecosystem with add-ons that can help automate design review, streamline repetitive PCB tasks, or connect board files to external AI-assisted workflows.
• Quilter generates PCB placement and routing options with an eye toward electrical constraints, manufacturability, and faster board iteration.
• Zuken AI PCB Design adds AI-assisted PCB capabilities to Zuken’s professional EDA ecosystem, especially for complex, high-density, and enterprise electronics workflows.

Electrical CAD, Hardware Design Automation, and Verification 

• Agnisys supports semiconductor and SoC teams by automating specification-driven outputs such as registers, documentation, verification collateral, and design assets.
• Cady acts like an automated schematic reviewer, checking designs against datasheets and common electrical mistakes before a board reaches fabrication.
• Cadence Cerebrus AI Studio applies AI to chip implementation workflows, helping semiconductor teams explore design options and optimize power, performance, area, as well as schedule tradeoffs across complex SoC projects.
• JITX approaches hardware design like software, letting teams describe circuits in code so that designs can be regenerated, revised, and reused more consistently.
• Siemens EDA AI brings purpose-built AI into semiconductor, 3D IC, and PCB workflows, aiming to reduce manual tool operation while improving design analysis, verification, and implementation productivity.
• WSCAD ELECTRIX is an AI-assisted electrical CAD platform for designing schematics, control cabinets, building automation systems, electrical installations, fluid systems, and piping and instrumentation diagram (P&ID) documentation in one connected environment.

Component Search, Selection, and Sourcing 

• SnapMagic combines PCB component search, symbols, footprints, sourcing data, and design assistance to help engineers pick parts that are actually easier to build with.
• Zenode helps users search for electronic components using plain-language requirements instead of relying only on exact part numbers or manual datasheet browsing.

Advanced Simulation, System Modeling, and RF Optimization 

• Ansys Twin Builder + TwinAI helps engineers create digital twins that combine simulation models with real-world data, allowing products and systems to be monitored, predicted, and optimized after deployment.
• Keysight PathWave Design AI supports RF, microwave, millimeter-wave, and high-speed digital design by pairing advanced simulation workflows with AI-assisted optimization for difficult signal-integrity and wireless-design problems.
• MATLAB + Simulink AI Toolboxes help engineers build, test, simulate, and deploy AI models inside larger engineered systems, making them useful for controls, signal processing, embedded systems, and model-based design.
• Wolfram Alpha / Mathematica provide computational tools for solving math, modeling systems, analyzing signals, and exploring engineering calculations.

Engineering Productivity 

• Autodesk Fusion 360 with AI Plugins gives engineers a connected CAD, CAM, CAE, PCB, and manufacturing workspace where AI-assisted tools can help generate design options, automate repetitive work, and speed up product-development decisions.
• Codeium / Devin Desktop is an AI coding environment descended from Codeium and Windsurf that supports code completion, repository-aware assistance, and agent-based software development workflows.
• Explainpaper helps users work through dense technical papers by letting them upload a document, highlight confusing sections, and get simpler explanations of the selected material.
• Heuristica gives engineers a visual concept-mapping workspace for exploring unfamiliar topics, organizing research paths, and building a clearer mental model of a new technical area.
• Leo Ideation helps engineers turn early product requirements into visual concept directions and supporting project documentation, making it useful for brainstorming before detailed CAD work begins.
• Perplexity is an AI research assistant that searches the web, summarizes findings, and provides source-backed answers for quick technical lookups, component research, and documentation questions.

Academic Research and Paper Understanding 

• Consensus is a research-search platform that helps users find evidence-backed answers from academic literature instead of relying on general web results.
• SciSpace helps students and researchers understand papers by explaining dense sections, equations, figures, and terminology in more approachable language.

Coding, Firmware, and Engineering Assistants 

• AskSia Electronics AI is built as a learning assistant for electronics students, with explanations aimed at making circuits, laws, and signals easier to understand.
• Augment Code is an agentic software-development platform built for larger codebases and engineering teams, helping coding agents access project context, coordinate workflows, and scale beyond one-off autocomplete tasks.
• ChatGPT Custom GPTs let users create task-specific AI assistants for electronics work such as explaining concepts, generating code, drafting documentation, or organizing repeatable workflows.
• Claude Code is Anthropic’s coding agent for understanding existing codebases, making multi-file edits, running tests, and helping engineers move from plain-language requests to working software changes.
• Codex is OpenAI’s ChatGPT-powered coding agent for writing, editing, reviewing, and running code, which is handy when electronics projects need firmware support, automation scripts, data-processing tools, or engineering software prototypes.
• Gemini Code Assist / Gemini CLI gives developers Google’s Gemini-powered coding support across IDE and terminal workflows, helping with code generation, debugging, project understanding, and multi-step development tasks.
• GitHub Copilot supports firmware and software development by suggesting code, helping complete functions, reviewing changes, and speeding up work in languages commonly used around embedded systems.
• Roo Code is a legacy open-source VS Code coding agent that could generate code, refactor projects, debug issues, update documentation, and use model-agnostic workflows, though its official extension has moved into a transitional/discontinued state.
• Visual Studio Code is a widely used open-source code editor that now serves as a hub for AI-assisted development, letting engineers combine extensions, debugging tools, terminals, and coding agents in one workspace.
• Warp is an AI-native terminal and agentic development environment that assists engineers in using natural language to run commands, debug errors, manage repositories, and coordinate coding agents from the command line.

Technical Writing, Documentation, and Organization 

• Notion AI helps organize engineering notes, project plans, meeting records, and research material into a more searchable and usable workspace.
• Overleaf AI helps with LaTeX-based technical writing, which is useful for lab reports, research papers, theses, and engineering documentation.