This topic covers the emerging class of AI app development platforms that fuse visual low‑code/no‑code builders, in‑IDE AI copilots, and agentic workflows to shorten the path from idea to production. Platforms range from visual, enterprise-oriented tools that design and operate AI agents (for example, MindStudio) to web‑native IDEs with instant hosting and integrated assistants (Replit), AI‑native code editors with agent frameworks (Windsurf, Cursor), and embedded copilots inside traditional IDEs (JetBrains AI Assistant). Complementary utilities—like PulpMiner’s webpage→JSON extraction and open‑source assistants such as CodeGeeX—fill data ingestion and model‑choice gaps. As of 2026‑03‑23 this convergence is timely: improved large language models and multi‑model architectures have made program synthesis, live previews, and agentic orchestration practical, while enterprise demand for faster delivery, governance, and less developer handoff pushes organisations toward low‑code approaches. Key trends include built‑in deployment and hosting, multi‑model support, live preview/feedback loops, and enterprise controls for security and compliance. Practical trade‑offs remain — abstraction versus control, vendor/model lock‑in, data privacy, and the need for observability and testing of generated artefacts. Evaluating offerings requires matching use cases (citizen development, prototype→ship workflows, or production engineering) to categories: Low‑Code Workflow Platforms, No‑Code App Platforms, and AI Code Generation Tools. This topic frames those choices and highlights where specialist tools and major cloud vendors (Google, Microsoft, Amazon) are accelerating integrated low‑code experiences for teams.