AI Engineering for Frontend Developers
Build, ship, and defend AI features in production frontend apps, and talk about them confidently in senior and architect interviews.
Early access waitlist members receive 48-hour advance access and Module 1 free.
What You Will Build and Defend
No toy chatbots or throwaway API wrappers. You will engineer production-grade systems ready for live users and system design whiteboards.
Production Streaming Chat UI
Handle SSE token streams, backpressure, scroll anchoring, and mid-stream markdown rendering without dropped tags or frame lag.
Documentation Q&A Bot with Citations (RAG)
Build an end-to-end RAG pipeline from chunking and embeddings to vector retrieval with pgvector, strict citation linking, and 'I do not know' fallbacks.
Autonomous Agent with Approval Checkpoints
Implement a multi-turn tool-calling loop where models execute APIs safely, with interactive step timelines and human confirmation dialogs for risky actions.
Generative UI with React Component Registry
Allow models to dynamically choose and render rich React charts, forms, and cards within the stream without risking XSS or arbitrary HTML execution.
On-Device WebGPU Inference & Local Fallback
Run quantized neural models directly in the user's browser using WebGPU and WASM, with seamless fallback to cloud APIs when offline or on low-end hardware.
13 Modules across 4 Levels
Every module builds on the previous one, culminating in production deliverables you can show in your portfolio and defend in interviews.
Level 1: Foundations
Understand model mechanics, tokens, sampling controls, and talk to models safely from Next.js.
Level 2: Build Core Experiences
Build streaming chat, vector embeddings, and full RAG pipelines over private docs.
Level 3: Advanced Interactions
Autonomous tool-calling loops, generative UI registries, and in-browser WebGPU inference.
Level 4: Production & Interviews
CI eval gates, prompt injection defense, cost quotas, and whiteboard system design.
Tailored for Your Timeline
Pick the track that matches your goals. The placement quiz will help you select on launch day.
Interview Sprint
Core mental models, streaming, RAG, tool calling, security, and system design whiteboards.
Builder Path
Hands-on build track through all major user-facing AI features from chat to generative UI.
Architect Path
Strategic decision-making, caching layers, micro-frontends, security threat models, and cost.
Full Path
All 13 modules, 52 graded coding challenges, 5 capstones, and 104 interview walkthroughs.
Built Specifically for Frontend & Fullstack Engineers
Most AI tutorials are written for Python data scientists. This course teaches frontend engineers how to integrate, stream, and defend AI features directly in React, Next.js, and TypeScript.
Engineers with 2+ Years of React & TypeScript
You already know hooks, component state, and async data. We teach you how to handle high-velocity token streams, backpressure, and schema-constrained models.
Engineers Preparing for Senior, Lead & Architect Interviews
Modern frontend system design rounds now routinely ask how to architect a 100k-stream chat app, design a Copilot autocomplete engine, or embed an AI widget via micro-frontends.
Engineers Moving from Services to Product Companies
Product companies demand engineers who can design features with strict cost budgets, PII redaction, prompt injection defense, and automated CI eval gates.
What You Need Before Starting
What You Get on the Early Access List
We only promise what we actually ship. As an early access subscriber, you will receive:
Start working through the course materials, interactive labs, and coding challenges 48 hours before the public launch.
Access all 7 lessons and interactive labs of Module 1 ("How LLMs Work for Frontend Engineers") 100% free with no credit card required.
Lock in the lowest launch rate for the full course and all future modules, capstones, and updates added throughout 2026.
Shape which specialized capstones and interview walkthroughs get prioritized through direct community feedback channels.
Frequently Asked Questions
Everything you need to know about the curriculum, prerequisites, and launch plan.
When does the course officially launch?
The course launches on November 2, 2026. Waitlist members get early access 48 hours in advance, along with immediate access to Module 1 for free.
What is the course format?
It is an interactive, text-and-lab-based course with runnable TypeScript code, live token and latency widgets, interactive visualizers, 52 graded challenges, and 5 production capstones.
Will I need to pay for OpenAI or Anthropic API keys to take this course?
No. Every lesson and graded challenge includes a free, deterministic local mock provider so you can complete 100% of the course without spending a penny on LLM API tokens. An optional live API toggle is available if you wish to run against your own keys.
How does this relate to existing DeepFrontend topics?
This is a standalone, structured 13-module certification course. Existing deepfrontend.net topics, challenges, and the Interview Simulator remain available as they are today. This course adds comprehensive end-to-end AI system architecture and implementation skills.
Do I need Python or machine learning experience?
None at all. This course is built specifically for TypeScript, React, and Next.js engineers. You will learn to integrate models via HTTP streams, route handlers, Server Actions, and in the browser via WebGPU.
What is the update and freshness policy?
AI APIs and model pricing evolve rapidly. Every lesson displays a 'Last Verified' timestamp and undergoes quarterly audits to keep model names, token pricing, and SDK versions up to date.
Reserve Your Early Access Spot
Be the first to build production AI features. Includes 48-hour early access, Module 1 free, and founding member pricing.