Tier 1: Hands-On AI Development
Transform from AI consumer to AI builder. Learn to integrate LLMs into applications, master developer productivity tools, and ship production-ready AI features.
What You'll Learn
This tier bridges conceptual understanding and production deployment. You'll write code that calls LLM APIs, build streaming chat interfaces, extract structured data from documents, and use AI to accelerate your own development workflow. By the end, you'll have production-ready code patterns and a supercharged development environment powered by Claude Code.
Part 1: Foundations
Master the core mechanics of working with LLMs: Tokens, Context Windows, and Prompting Techniques.
Before building production AI features, you need to understand how LLMs actually process text, how to communicate with them effectively, and how to control their behavior. This section covers the essential building blocks.
Lesson 1: Tokens & Context — Stop thinking in words and start thinking in tokens. You'll use tiktoken to calculate exact costs before sending requests, understand context window limits, and avoid "context length exceeded" errors that break production systems.
Lesson 2: Crafting Prompts That Actually Work — Transform prompts from vague wishes into engineered code. Master Zero-Shot, Few-Shot, and Chain-of-Thought patterns. Learn delimiters that prevent prompt injection attacks and keep user data separate from instructions.
Lesson 3: System Prompts — Program AI behavior at the architectural level. System prompts define persistent behavior across entire conversations—the employee handbook that shapes every interaction. Structure them with identity, context, rules, format, and guidance sections.
Lesson 4: Generation Parameters — Master the knobs that control creativity versus precision. Understand temperature, Top-p, Top-k sampling, and frequency/presence penalties. Configure models for creative settings (marketing copy) versus deterministic ones (JSON extraction).
Part 2: API Integration
Build real AI applications by mastering streaming chat, structured data extraction, and multimodal vision APIs.
This section moves from theory to practice. You'll integrate with OpenAI, Claude, and Gemini APIs to build production-ready features with working code for the most common AI integration patterns.
Lesson 5: Text Generation & Streaming UIs — Build a streaming chat interface that works across multiple providers. Implement Server-Sent Events for token-by-token streaming, create a FastAPI backend, handle errors with retry logic, and abstract away vendor lock-in.
Lesson 6: Structured Data Extraction — Transform messy documents into typed objects your code can trust. Use MarkItDown to convert PDFs and Word docs into Markdown, then leverage JSON mode and Pydantic schemas to extract structured entities with validation.
Lesson 7: Vision & Multimodal Inputs — Teach your LLM to see. Modern models process images alongside text—enabling screenshot analysis, document OCR, and diagram understanding. Build screenshot-to-code generators, receipt scanners, and UI analyzers.
Part 3: Developer Productivity with Claude Code
Transform your development workflow with Claude Code—an AI pair programmer that reads, edits, and executes across your entire codebase.
This section focuses on using AI to make you faster. You'll master Claude Code, a CLI tool that brings Claude directly into your development workflow as an autonomous coding partner. Deploy it across your team with monitoring, conventions, and security.
Lesson 8: Claude Code Fundamentals — Get productive in minutes. Install and authenticate, understand core tools (Read, Edit, Write, Bash, Glob, Grep), learn when to use CLI versus IDE integration. Track usage limits and build real workflows for code review, refactoring, and debugging.
Lesson 9: Autonomous Agents — Scale beyond individual commands by spawning specialized agents for complex tasks. Learn when to delegate versus when to direct, master agent types (Explore, Plan, general-purpose), orchestrate multi-agent workflows, and execute parallel tasks.
Lesson 10: Customization & Extensions — Extend Claude Code to fit your exact workflow. Create Skills (personal commands via markdown), install Plugins (shareable npm packages), and connect MCP servers (external data sources). Understand when to use each extension mechanism.
Lesson 11: Production & Team Workflows — Deploy Claude Code across your organization while maintaining control. Monitor usage and costs, establish team conventions with shared skills and hooks, integrate with git using /commit and /review-pr, and implement security best practices.
Why This Matters
These fourteen lessons transform how you build software. Part 1 gives you the foundations to work with any LLM API. Part 2 provides production-ready code for streaming chat, data extraction, and vision—the building blocks of modern AI products. Part 3 supercharges your own development workflow with autonomous agents that handle hours of work in minutes.
Master Tier 1 and you'll ship AI features faster, write code more efficiently, and understand the engineering constraints that separate prototypes from production systems.
Complete these lessons before moving to Tier 2's advanced patterns.