Explore AI-assisted techniques for understanding production code, identifying bottlenecks, and optimizing data structures for better performance.

Analyzing production code with AI

Options

Task context

Clear goal

Expected output

Structuring your AI prompt

Building effective prompts for code analysis

Profiling time performance with AI

Working with AI to Optimize Performance

The AI-assisted optimization cycle

Interpreting profiler output

Before

After

Validating AI-suggested changes

Optimizing memory usage with AI

Working with AI to Fix Memory Issues

From symptoms to solutions

Exploring memory allocations

Evaluating AI optimization suggestions

Analyzing and Optimizing Code

Learn to use AI for building test suites, conducting security reviews, and managing dependencies in production codebases.

AI-assisted testing

Working with AI to build a test suite

Analyzing coverage with AI

Security-first development with AI

Crafting secure prompts

Matching security concerns to AI prompts

Analyzing security findings with AI

AI-assisted dependency management

Matching dependency issues to AI approaches

Prioritizing dependency upgrades with AI

Testing, Security, and Dependencies

Apply AI to configuration-driven design, database schema mapping and query optimization, and collaborative development workflows.

Configuration-driven development with AI

Delegating config migration tasks

Reviewing AI's config architecture proposal

Catching config drift with AI

Database design and optimization with AI

Effective prompting for query optimization

Detecting duplicates in sensor data

AI as a development collaborator

AI-assisted code review

When to challenge AI's suggestion

Congratulations and next steps

Architecture, Databases, and Collaboration

AI coding assistants can do far more than write code. In this course, you'll learn to use them for the full spectrum of software engineering work. Starting with production code analysis and performance optimization, you'll move on to AI-assisted testing, security vulnerability detection, and dependency management. Then you'll apply AI to higher-level challenges: designing configuration-driven architectures, optimizing database schemas and queries, and building effective human-AI collaboration workflows. The course focuses on tool-agnostic principles and prompting strategies that work across any AI assistant, so the skills you gain apply no matter which tools you use.

AI-Assisted Coding for Developers

Learn to use AI as a senior engineering partner for code analysis, performance optimization, security, and software architecture decisions.

Advanced AI-Assisted Coding for Developers

Review the suggested code for correctness and edge cases

Check that the new implementation handles thread safety

Run benchmarks comparing the old and new implementations

Re-run the profiler to confirm the bottleneck is resolved

Validating AI-suggested changes

Advanced AI-Assisted Coding for Developers

Latihan interaktif praktis