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You Know the Craft. Now Add the Accelerant.

You've shipped production code. You understand architecture. You don't need tutorials on for loops. What you need: how to leverage AI tools effectively and integrate AI into your existing skills.

Two Things to Learn

As an experienced developer, there are two distinct skills that will multiply everything you already know.

1

AI-Assisted Development

Using AI tools to code faster. Scaffold projects in minutes. Generate boilerplate instantly. Debug with context-aware assistance.

Multiplies your speed
2

AI as a Feature

Adding AI capabilities to products. Integrate LLMs, build intelligent features, handle production concerns like cost and latency.

Multiplies your product value

Both multiply your existing skills. Your architecture knowledge, your debugging instincts, your production experience—AI amplifies all of it.

Your Fast Track

You don't need hand-holding. Here's the efficient path to mastery.

1

Master Your New Pair Programmer

45 minutes

This is the deep-dive, not basics. Learn effective prompting strategies, context management techniques, and when to trust vs. verify AI output.

Start Here
What you'll learn

Effective prompting, context management, when to trust/verify AI output

2

See AI Integration Patterns

2 hours

These are the production patterns you'll use everywhere. Streaming responses, rate limiting, caching strategies, and cost management—the real concerns when shipping AI features.

Learn Patterns
Focus on

Streaming, rate limiting, caching, cost management

3

Build Something Complex

4-6 hours

Pick based on your interest—all are production-level complexity that will stretch your AI integration skills.

Logistics Route Optimizer
Or choose an alternative:
HealthTech Patient Portal Legal Contract Analyzer
Project focuses

Geospatial + AI reasoning | Security + AI | Document processing + AI

4

Apply to Your Stack

Your pace

This is where the rubber meets the road. Take one of your existing projects and add an AI feature using the patterns you've learned.

🎯 Your Challenge

You'll move fast because you already know the foundation. The patterns will feel natural because you understand the underlying architecture concerns.

1 Pick an existing project you maintain
2 Identify where AI could add value
3 Apply the patterns from Step 2
4 Ship it to production

Patterns That Transfer

These patterns work across languages, frameworks, and AI providers. Learn them once, apply them everywhere.

Streaming responses (SSE, WebSockets)
Token management and cost optimization
Prompt engineering for specific domains
Caching strategies for AI responses
Error handling and fallbacks
Rate limiting and usage tracking

What Changes, What Doesn't

AI tools shift some things dramatically while others remain exactly as important as they've always been.

What Changes

  • How fast you scaffold projects
  • How you approach boilerplate
  • What's possible in a weekend

What Doesn't Change

  • Need for clean architecture
  • Importance of testing
  • Security fundamentals
  • Your judgment on code quality

The Meta Skill

Learning to Learn with AI

1 AI tools are evolving fast—what works today will be different in 6 months
2 The skill is learning to learn with AI, not memorizing specific tool features
3 These guides teach patterns, not just implementations—patterns that transfer as tools evolve