Hey Devs 👋
As full-stack developers, integrating AI into our applications has quickly shifted from a "nice-to-have feature" to a core requirement.
However, moving beyond simple API calls to building performant, real-time, and scalable AI-driven web apps comes with its own set of challenges—streaming responses, handling complex client-side state, managing token usage, and optimizing serverless setups.
To tackle these exact engineering problems, I launched AIWITHJS (@aiwithjsdev)—a channel dedicated to practical, production-grade AI engineering using the JavaScript and TypeScript ecosystem.
🛠️ What We Cover & Build
Rather than high-level overviews, the focus is strictly on actionable code, architectural patterns, and real-world implementations:
Next.js App Router & AI Integration:
Setting up efficient server-side streaming, route handlers, and server actions optimized for AI components.
Vercel AI SDK & Frameworks:
Leveraging hooks like useChat and useCompletion to handle streaming UI states seamlessly.
Local LLM Workflows:
Running and streaming local models (using tools like Ollama) inside your local Node.js environment for zero-cost dev setups and privacy-first apps.
State Management & Caching:
Optimizing database interactions, managing vector embeddings, and handling rate limits using tools like Redis and MongoDB.
Full-Stack Performance:
Structuring scalable TypeScript codebases that cleanly separate UI, API orchestration, and AI model streams.
https://youtube.com/playlist?list=PLcdYhreZu0tk&si=jgPRvBiA1DCWlSar
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