Monitoring AI: Prometheus and Grafana for Observability
Increase AI model reliability with Prometheus and Grafana for observability and evaluation, streamline model performance monitoring
Building MCP Server from Scratch for AI Tooling
Learn to implement an MCP server for AI tooling, enabling efficient communication between agents and tools.
Building Conversational AI with LLMs and RAG
Learn to build conversational AI systems using LLMs and RAG, with practical tips and production-ready code examples
Evaluating LLMs with Structured Output and Semantic Similarity
Evaluate LLMs with structured output and semantic similarity for production-grade AI engineering, learn how to avoid common pitfalls
Efficient Fine-Tuning with QLoRA for LLMs
QLoRA enables efficient fine-tuning of large language models, reducing computational costs and memory usage.
LoRA Fine-Tuning for LLMs: Unlock Efficient Adaptation
Discover how LoRA fine-tuning enhances LLMs with efficient adaptation, improving performance without extensive retraining.
Model-Based Reinforcement Learning for AI Agents with RAG
Master model-based reinforcement learning for AI agents using RAG, enhancing decision-making and task execution.
Reasoning and Acting with ReAct Agent Pattern and LLMs
Learn ReAct Agent Pattern for LLMs and RAG, enabling reasoning and acting in AI systems, with a focus on production-grade implementation
Building Autonomous Agents with Tool Use and Multi-Step Planning
Learn to create autonomous agents that use tools and plan multiple steps with ease. Discover how AI agents can streamline tasks and improve efficiency.
RAG-Based Text Generation with LLaMA and LangChain
Learn RAG-based text generation with LLaMA and LangChain. Discover how to build powerful AI models for text generation.
Streaming Tool Call Results in AI Agent Loops with WebSockets
Stream tool call results in AI agent loops using WebSockets for real-time communication and <a href='/blog/integrating-ai-models-with-crm-systems-using-salesforce-and-python'>integrating AI models with CRM systems</a>
Implementing AI Agent Memory with Redis and Context Management
Implement AI agent memory with Redis and context management for efficient decision-making, learn how to store and retrieve agent state