The intersection of AI and front-end development is reshaping how we build, test, and manage our applications. At the end of this month I will give a talk at 4CEE about AI in modern Angular workspaces. This post will walk you through the core themes, insights, and takeaways from my presentation, while showcasing how AI is transforming the way we work with Angular.
Why AI in Angular?
Well, forget Angular. Why AI in coding in general. We still love to code but we don't want to lose time on simple time-consuming stuff like writing utilities, refactoring projects, moving elements in our architecture around, writing unit-tests etc etc. I started with simple prompts, then I realised, the more context, the better the result. And then I realised, the more context, the quicker the LLM started to hallucinate 😅
It was time to learn some proper prompt engineering, like few shot prompting, COT, TOT, prompt chaining etc... My journey started with prompt engineering, gradually evolving into more complex concepts such as retrieval-augmented generation (RAG) and building AI agents within Angular workspaces. If you're curious about how AI can write unit tests, refactor code, and even generate speaker notes or LinkedIn posts, stay tuned.
Key Concepts Covered
1. AI and Large Language Models (LLMs)
LLMs such as GPT-4 are powerful enough to generate human-like text, but they are also changing how we code. By understanding how to craft effective prompts, developers can guide AI models to write code snippets, generate forms, and even automate certain tasks that usually take hours.
2. Prompt Engineering: A Developer’s Superpower
Prompt engineering is all about crafting inputs that help guide AI models towards desired outputs. A well-designed prompt can make all the difference between useful results and “AI hallucination” (when AI gives irrelevant or inaccurate answers).
For instance, I can instruct AI to build a dynamic Angular form with complex logic and validation, just by using the right prompts. The results weren’t just decent – they were mind-blowing.
3. RAG: Retrieval Augmented Generation
If you work with large data sets, it's impractical and costly to feed every possible detail into an AI prompt. That’s where RAG comes in. This technique retrieves relevant documents or data chunks from a database and then feeds them into an AI model, allowing it to provide accurate and context-aware responses. For example, instead of asking the AI about the thousands of products in a catalog, RAG fetches just the relevant ones and improves efficiency, cost, and speed.
4. AI in Angular: Automating Dev Processes
By integrating AI into our Angular workspaces, we can streamline many development processes. Here’s a glimpse into what’s possible:
- Automating utility functions: AI generates utility functions based on project requirements, saving developers hours of repetitive coding.
- Unit tests: Imagine a world where unit tests are generated automatically based on your code changes. I recently fixed 3 bugs in one minute by doing the following: Asking LLM to write unit test, executing the unit test, telling LLM which tests failed, and replacing my logic with the updated logic of the LLM. INSANE!
- Refactors: AI can help refactor large codebases consistently, ensuring code follows the best practices and project architecture guidelines.
- Code consistency: The AI can assist by the workspace's architecture rules, making sure elements like components, services, guards, and types all follow specific file naming conventions and folder structures.
5. Nx: Scaling Angular Workspaces with AI
For those working with Nx, the powerful tool for managing large monorepos, AI makes it even better. In my talk, I will showcase how custom Nx generators can be combined with AI models to generate code, enforce architecture rules, and make developers’ lives easier by reducing complexity and providing consistency across projects. By doing this, AI can help keep workspaces consistent, enforce architecture rules, and make refactoring a breeze.
6. Building an AI-powered Workspace
One of the most exciting aspects of my talk is how you can build an AI-powered workspace in Angular. Imagine an AI agent that understands your codebase, the components, services, and libs it contains. You could ask it to write a form, generate reusable components, or even optimize your code – all with AI understanding your architecture.
The Future of AI and Angular: Embrace the Change
The core message of my talk is simple: don’t ignore AI. It is reshaping our industry, and as developers, we should embrace it. While some might worry about job displacement, the truth is we can't predict it.
What we do know is that AI will enhance our capabilities, allowing us to focus on the creative and complex tasks that truly matter.
Here are a few tips for embracing AI in your workflow:
- Start small: Use AI tools like ChatGPT for simple tasks such as generating utility functions or writing tests.
- Learn prompt engineering: Knowing how to craft the right input can significantly improve the quality of AI-generated code.
- Use Markdown for everything: Whether it's documentation, blog posts, or even generating slides, AI thrives in well-structured environments like Markdown.
- Integrate AI into workspace: Use NX generators to call LLM's and work as AI agents for you
If you are interested, I'm organizing an online in-person workshop 13th of December 2024. We will build an AI agent together that codes for us and writes directly to our codebase, we will build a RAG system with a chat assistant that can talk to our content.
You can check it out here: https://www.simplified.courses/ai-workshop
