SOLID Principles for AI-Generated Code
Published by O'Reilly Media, Inc.
Bridge the gap between AI-generated code and production-ready, enterprise-grade solutions
Course outcomes
- Apply SOLID principles to ensure robust, scalable, and maintainable software designs—especially when starting from AI-generated code
- Implement key design patterns (creational, structural, and behavioral) in real-world Java scenarios
- Identify and mitigate AI-specific pitfalls, including hallucinations, insecure code snippets, and unscalable design suggestions
- Refactor AI outputs into cleaner, safer, and more maintainable code bases
Course description
Accepting code created by AI-assisted coding tools uncritically can lead to messy designs, security holes, nonscalable architectures, and prompt injection vulnerabilities.
Join expert Rohit Bhardwaj to learn how to analyze, refactor, and architect AI-generated code to ensure that your software solutions are robust, clean, and future-proof. You’ll discover how to critique AI-generated Java code, refactor it for adherence to best practices, and integrate design patterns that align with specific business and technical requirements. By the end, you’ll be equipped to guide AI outputs effectively, architect robust solutions, and confidently handle the toughest design challenges in high-stakes interviews or production environments.
What you’ll learn and how you can apply it
- Evaluate AI-generated solutions for architecture and pattern usage
- Lead code reviews that focus on design patterns and SOLID compliance
- Optimize your daily workflow by leveraging AI while avoiding common security and scalability traps
This live event is for you because...
- You want to upskill and stay relevant as AI becomes more integrated into everyday development practices.
- You need to bridge the gap between AI-generated code and production-ready, enterprise-grade solutions.
- You’re preparing for high-stakes technical interviews where design patterns and architecture decisions are scrutinized.
Prerequisites
- A computer with a Java development environment installed (e.g., IntelliJ, Eclipse, or VS Code)
- Clone the GitHub repository with preliminary exercises: GitHub: AI-Generated Code & Patterns
- A general understanding of object-oriented programming (OOP) concepts and Java
- Basic familiarity with SOLID principles and design patterns (intro-level knowledge is sufficient)
Recommended follow-up:
- Read Head First Design Patterns, second edition (book)
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
AI code analysis fundamentals (60 minutes)
- Presentation: Opportunities, pitfalls, and real-world use cases of AI-generated code; identifying common issues (hallucinations, prompt injection vulnerabilities, nonscalable architectures); review of SOLID principles and why they matter; how to spot suboptimal solutions
Break
Creational design patterns and AI-generated code (60 minutes)
- Presentation: Key creational patterns
- Hands-on exercises: Refactor an AI-generated snippet implementing faulty patterns; explore creational patterns and spot suboptimal solutions
- Group discussion: Trade-offs and best practices
Break
Structural design patterns and refactoring challenges (60 minutes)
- Presentation: Core structural patterns
- Hands-on exercises: Analyze an AI-generated patterns approach that violates the open-closed principle; refactor to comply with SOLID; explore common pitfalls in structural patterns and how to justify design trade-offs
Break
Behavioral design patterns—Part I (60 minutes)
- Presentation: Focus patterns
- Hands-on exercises: Incorporate an AI-generated pattern snippet into a real-world scenario; evaluate and refactor for maintainability and testability; spot potential prompt injection or security flaws in AI-suggested solutions
Break
Behavioral design patterns—Part II (50 minutes)
- Presentation: Focus patterns
- Hands-on exercises: Live code to integrate AI-generated patterns into a distributed system; identify concurrency and scalability issues; refactor
- Group discussion: How to effectively articulate design decisions
Wrap-up and Q&A (10 minutes)
Your Instructor
Rohit Bhardwaj
Rohit Bhardwaj is the CTO and director of AI architecture at Salesforce, where he leads strategy and design for enterprise-scale AI systems, multi-agent platforms, and data cloud integrations. He has extensive experience architecting multitenant, cloud native solutions using resilient microservices, service-oriented architectures, and the AWS stack.
As an Agentforce expert, Rohit specializes in generative AI, retrieval-augmented generation (RAG), and AI-powered business transformation, with a strong focus on trust, governance, and resilience in AI system design. He conceptualizes and delivers high-value cloud solutions that reduce costs, increase efficiencies, and scale across global enterprises.
A regular speaker at No Fluff Just Stuff, UberConf, Richweb, GIDS, and international conferences, Rohit is widely recognized for his real-time analytics, system design mastery, and transformative AI insights. He’s also an accomplished author and educator.
Rohit holds an MBA in corporate entrepreneurship from Babson College and master’s degrees in computer science from both Boston University and Harvard University. As a visionary leader, he builds strategic roadmaps, mentors global architecture teams, and drives research initiatives—making him a trusted advisor at the intersection of AI, cloud platforms, and business strategy.