There is so much AI tooling available it can be difficult to categorize everything comprehensively. Many have overlapping functions, so it’s not always clear exactly what a service is designed for. In the following segments however, you’ll see a good number of services and how you can use them based on your needs. In the previous lessons, you went through the more hands-on route to understand the internals of modern AI applications. The first category you’ll learn about is code-first AI platforms.
Code-First AI Frameworks
These frameworks offer low-level access to various tools necessary to build AI applications. They can be very involved, requiring lots of learning and expert knowledge to be able to build advanced and robust applications. Developing with these tools certainly takes more time, as does maintaining them. But they offer the most flexibility and the ability to build highly efficient, complex AI apps at scale. You can also build simple apps with these tools.
Visual LLM Orchestrators
These are effectively a visual IDE for LangChain. They’re a step above the code-first tools. They’re simple to work with and much faster than writing code. With these, you simply connect nodes along edges and define logic where necessary. They use much of the same terminology as you’ve seen in the previous lesson. With a basic understanding of how to build based on the graph structure, that is, nodes and edges, you’ll be able to drag-and-drop till you’re done with your app.
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AI Workflow & Logic Orchestrators
AI agents are arguably the second most used feature of AI applications besides chats or conversations. Thus it’s no surprise that there are a lot of services designed to build agentic workflows. Agentic workflows boost productivity, and are fun to work with.
These are specialized platforms for creating AI agents and chatbots. They have limited use cases and can be restrictive for complex apps. They allow you to build AI-based apps that automate tasks, perform research, converse with users, and deploy and test AI agents. Some have visual builders and can sometimes be similar in many ways to the AI workflow apps described above.
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Full-Stack AI App Builders
While AI builders and workflow platforms allow you to build custom AI apps, these platforms allow you to build custom native apps, such as web and mobile apps, using AI. They don’t offer visual builders but instead provide text boxes for accepting prompts. You describe the app you want to build in detail, sit back, and watch them build it for you.
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Repmyu gwetgs
Act as a Senior Kotlin Multiplatform Developer. Build a fitness tracking app using Compose Multiplatform that targets both iOS and Android.
Project Structure & Tech Stack:
Use the commonMain source set for 100% of the UI and business logic.
UI: Use Compose Multiplatform (CMP) for all screens.
Networking: Use Ktor for API calls.
Local Storage: Use SQLDelight or Room (KMP version) for local persistence.
Architecture: Follow the MVVM pattern with ViewModel (from Jetpack libraries) in the shared module.
App Features:
Dashboard Screen: A central hub showing 'Active Minutes' and 'Calories' using a progress ring component.
Workout History: A list view with smooth scrolling (ensure display-native framerates on iOS).
Platform Integration: In iosMain and androidMain, implement a platform-specific expect/actual function to fetch the device's battery level.
Design Requirements:
Use Material 3 components with a minimalist 'Deep Sea' blue theme.
Ensure native iOS behaviors like swipe-to-back and platform-appropriate text input.
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Act as a Senior Full-Stack Developer. Create a web-based Project Management Dashboard using Next.js and Tailwind CSS. The app should feature:
Kanban Board: A drag-and-drop task management interface with columns for 'To-Do', 'In Progress', and 'Done'.
User Roles: Implement role-based access where Admins can manage tasks and regular Users can only update their own assigned items.
Reporting: A page with monthly task completion charts generated using Recharts.
Integrations: Connect the app to a PostgreSQL database via Prisma for real-time updates.
Auth: Include a secure login page with 'Sign in with Google' and email/password options.
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This content was released on Mar 15 2026. The official support period is 6-months
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An overview of major AI platform types, from code-first frameworks to full-stack AI application builders.
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