Function Calling vs Tool Use in LLMs: Choosing the Best Approach for AI Action Execution and Orchestration Function calling and tool use are two dominant patterns for enabling large language…
“`html Streaming Responses in AI Applications: Building Real-Time User Experiences Streaming responses in AI applications represent a paradigm shift in how artificial intelligence communicates with users, delivering information incrementally rather…
AI-Powered Code Review: Automating Pull Request Analysis and Security Scanning AI-powered code review is a transformative approach to software development that leverages artificial intelligence to automate the analysis of source…
Agentic Workflows for DevOps: Automating Infrastructure Troubleshooting with AI Agentic workflows are a revolutionary approach in DevOps, leveraging autonomous AI agents to automate complex, multi-step tasks that traditionally require human…
Local vs Cloud LLMs: Performance, Privacy, and Cost Trade-offs for Enterprise AI In the rapidly evolving landscape of enterprise AI, large language models (LLMs) are transforming how businesses process natural…
Red Teaming AI Systems: Advanced Techniques for Ensuring Model Safety and Reliability Red teaming AI is a structured, adversarial testing process designed to proactively identify vulnerabilities, biases, and potential harms…
Multi-Modal AI Agents: Combining Text, Vision, and Audio Processing for Real-World Intelligence Multi-modal AI agents are systems that understand and act on information across text, images, video, and audio. Instead…
AI Testing Strategies: Unit Testing, Integration Testing, and Evaluation Metrics for LLM Applications Large Language Model (LLM) applications are revolutionizing how we interact with technology, but their complexity demands rigorous…
Context Window Management: Strategies for Handling Long Documents and Conversations In the realm of artificial intelligence and large language models (LLMs), the context window represents the finite span of text…
Cost Optimization for AI Applications: Token Management and Model Selection Strategies Cost optimization for AI applications revolves around reducing token usage, right-sizing models, and designing architectures that deliver high quality…