Matt Pocock (AIhero) – Build DeepSearch in TypeScript Download

Description

The Matt Pocock (AIhero) – Build DeepSearch in TypeScript course is a highly practical, cohort-based training program that teaches developers how to build production-grade AI-powered search applications using TypeScript, Next.js, and Large Language Models (LLMs). Led by Matt Pocock, creator of Total TypeScript and a leading TypeScript educator, this course is a deep dive into AI application engineering—combining modern front-end architecture, backend design, and intelligent agent workflows into one cohesive project called DeepSearch.

Detailed Course Description

The program takes participants through the entire process of developing an AI-integrated search engine from scratch, mirroring how real production systems are built in professional environments. It combines clean coding practices, scalable design patterns, and deep AI integration while using TypeScript as the foundation for type safety and developer productivity.

Core Modules and Lessons

1. Introduction & Setup

   • Learn how AI-assisted development fits into modern app workflows.

   • Set up PostgreSQL with Docker and integrate Drizzle ORM for a type-safe database layer.

   • Configure the environment for smooth local development.

2. Building the DeepSearch Core

   • Build the heart of the search engine by integrating OpenAI APIs for reasoning and text generation.

   • Structure your code for clarity, reliability, and future scalability using TypeScript best practices.

3. Embedding & Vector Search

   • Implement embeddings and retrieval systems with high-performance vector search pipelines.

   • Learn how to build hybrid search models that mix keyword relevance with semantic intelligence.

4. Frontend with TypeScript & React

   • Develop a responsive, interactive Next.js interface for loading and presenting DeepSearch results.

   • Apply modular, maintainable coding patterns suited for fast iterations.

5. Server Integration & Optimization

   • Manage request handling, Redis caching, and asynchronous LLM streaming for real-time responses.

   • Strengthen performance, monitor throughput, and build efficient data pipelines.

6. AI Agents & Workflow Architecture

   • Introduce the evaluator-optimizer loop, an adaptive mechanism where the AI refines its responses through self-assessment and iteration.

   • Learn the difference between Agent (dynamic decision-making entities) and Workflow (deterministic process sequences).

7. Production Hardening & Deployment

   • Add logging, security checks, and error-handling systems for production reliability.

   • Learn best practices for deploying on platforms like Vercel or custom cloud setups.

8. Launch & Scale

   • Test scalability under real-world workloads.

   • Implement observability using monitoring tools like LangFuse and evaluation systems such as Evalite.

What You Get

• Full Project Source Code: Clean, production-level DeepSearch app to use or extend.

• Video Lessons with Coding Walkthroughs: Step-by-step videos explaining both the why and how behind each concept.

• Hands-On Labs: Build components alongside Matt with guided exercises.

• Prompt Engineering & Context Management: Techniques for improving LLM response accuracy.

• Private Developer Community: Collaborate and ask questions within AIhero’s Discord.

• Lifetime Access: Includes all video lessons, cohort replays, and future updates.

Key Tools and Technologies

• TypeScript (core language)

• Next.js for frontend architecture

• Drizzle ORM and PostgreSQL for backend type-safe persistence

• Redis for caching

• OpenAI API for LLM integration

• LangFuse and Evalite for model evaluation and monitoring

Ideal For

• TypeScript developers ready to transition into AI engineering.

• Frontend or full-stack developers seeking to understand LLM-powered app design.

• Anyone wanting to build useful, real-world AI projects with maintainable codebases.

Why It Stands Out

Matt Pocock’s AIhero courses focus on applied learning — you don’t just learn AI, you build with it. This immersive, structured program allows developers to confidently create AI-enhanced systems instead of simple demos or GPT wrappers. The cohort model adds accountability, mentorship, and community-driven feedback, ensuring participants leave with fully deployable projects and professional-grade skills.

Summary

“Build DeepSearch in TypeScript” by Matt Pocock (AIhero) is a hands-on program for mastering the intersection of AI and TypeScript development. Through a real-world project, learners gain the expertise to design, code, and deploy scalable AI applications with confidence — learning everything from embeddings and caching to type-safe backend design and LLM integration. This program equips developers with the technical depth and architectural mindset required to thrive in the next wave of AI-powered software engineering.