NeuroDesigner

Hey Product Hunters! I’m Reiyo, one of the makers behind NeuroDesigner. Why we built NeuroDesigner (V 1.0) Designing neural-network architectures still feels like wiring a circuit board in the dark. We wanted a visual canvas where anyone can drag-and-drop layers, connect them, and instantly export clean TensorFlow code. What you can do today 🎨 Build visually: Sketch models with blocks and connections. 🦾 AI recommendations based on current layer 🚀 One-click export: Download runnable scripts, diagrams , diagram plain text description What’s next (our public roadmap) V 2.0 — Research-grade templates: Drop-in YOLO-v9, Transformer variants, diffusion backbones, and more (drag-and-drop templates ready). V 3.0 — Code-in-context: Deep IDE integration — VS Code, Cursor, and other “AI coding sidekicks” — so you can design and run your model without leaving your favorite editor. Why that matters Drag-and-drop design tools slash setup time for ML pipelines datasciencedojo.com , and visual ONNX editors like NVIDIA’s Nsight DL Designer prove how powerful a no-code graph approach can be . Pairing design with IDE-native AI assistants (e.g., Cursor’s VS Code workflow) keeps the experiment loop tight and developer-friendly producthunt.com . We’d ❤️ your feedback Does the canvas feel intuitive? Which pretrained architectures or IDE plugins should we prioritise? Hit us with edge-cases or dream features — we’re here all launch-day (and beyond) to chat! Thanks for stopping by and happy building! 🚀 – Reiyo & the NeuroDesigner crewa