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4 Key Insights for Scaling LLM Applications (Sponsored)
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LLM workflows can be complex, opaque, and difficult to secure. Get the latest ebook from Datadog for practical strategies to monitor, troubleshoot, and protect your LLM applications in production. You’ll get key insights into how to overcome the challenges of deploying LLMs securely and at scale, from debugging multi-step workflows to detecting prompt injection attacks.
This week’s system design refresher:
How Java Works
How Gitflow Branching Works?
Become an AI Engineer | Learn by Doing | Cohort Based Course
The Life of a Redis Query
6 Steps to Create a New AI Model
How Java Works
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Ever wondered what happens behind the scenes when you run a Java program? Let’s find out:
Java (JVM Runtime):
Java source code (.java) is compiled into .class bytecode using javac.
The Class Loader loads bytecode into the Java Runtime Environment (JVM).
Bytecode is verified and executed.
JVM uses both an Interpreter and a JIT Compiler, frequently used code (hot paths) is converted into native machine code, making Java faster.
Over to you: For large-scale systems, do you still see Java as the go-to language?
CodeRabbit: Free AI Code Reviews in CLI (Sponsored)
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CodeRabbit CLI is an AI code review tool that runs directly in your terminal. It provides intelligent code analysis, catches issues early, and integrates seamlessly with AI coding agents like Claude Code, Codex CLI, Cursor CLI, and Gemini to ensure your code is production-ready before it ships.
Enables pre-commit reviews of both staged and unstaged changes, creating a multi-layered review process.
Fits into existing Git workflows. Review uncommitted changes, staged files, specific commits, or entire branches without disrupting your current development process.
Reviews specific files, directories, uncommitted changes, staged changes, or entire commits based on your needs.
Supports programming languages including JavaScript, TypeScript, Python, Java, C#, C++, Ruby, Rust, Go, PHP, and more.
Offers free AI code reviews with rate limits so developers can experience senior-level reviews at no cost.
Flags hallucinations, code smells, security issues, and performance problems.
Supports guidelines for other AI generators, AST Grep rules, and path-based instructions.
How Gitflow Branching Works?
Gitflow branching strategy is a Git workflow that organizes development into dedicated branches for features, releases, hotfixes, and the main production line. It is an ideal Git branching strategy for projects with regular versioned deployments.
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