engineering ai agents

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Build AI Agents With Langchain, Crewai & Openai: A Practical Systems Engineering Guide to Real-World LLMs, Tools, and Scalable AI Solutions for Beginners
Build AI Agents With Langchain, Crewai & Openai: A Practical Systems Engineering Guide to Real-World LLMs, Tools, and Scalable AI Solutions for Beginners
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Context Engineering in AI Agents: Techniques and Frameworks for Building Contextually Intelligent AI Systems
Context Engineering in AI Agents: Techniques and Frameworks for Building Contextually Intelligent AI Systems
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Mastering Context Engineering for AI Agents: A Complete Guide to Designing Reliable, Context-Aware, Multi-Agent AI Systems with GPT-4, Claude, ... LangGraph Integration and Python Automation)
Mastering Context Engineering for AI Agents: A Complete Guide to Designing Reliable, Context-Aware, Multi-Agent AI Systems with GPT-4, Claude, ... LangGraph Integration and Python Automation)
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Building Better AI Conversations with LLMs and Agents: A Developer’s Handbook for UX Patterns, Real-Time Interactions, and Scalable Prompt Engineering: 5 (Intelligent Systems Engineering)
Building Better AI Conversations with LLMs and Agents: A Developer’s Handbook for UX Patterns, Real-Time Interactions, and Scalable Prompt Engineering: 5 (Intelligent Systems Engineering)
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AI Agent’s Memory & Context Engineering: Empower Your AI Agents to Deliver Accurate, Consistent, and Personalized Interactions
AI Agent’s Memory & Context Engineering: Empower Your AI Agents to Deliver Accurate, Consistent, and Personalized Interactions
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BUILDING AGENTIC AI SYSTEM WITH RAG 2.0: A Practical Guide to Engineering RAG-Based AI Agents with Long-Term Memory and Tool Use
BUILDING AGENTIC AI SYSTEM WITH RAG 2.0: A Practical Guide to Engineering RAG-Based AI Agents with Long-Term Memory and Tool Use
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Production-Ready Voice AI: Engineering Conversational Agents That Are Fast, Scalable, and Human-Like for Real-World Applications
Production-Ready Voice AI: Engineering Conversational Agents That Are Fast, Scalable, and Human-Like for Real-World Applications
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AI Engineering: Building Multi-Modal Intelligent Systems with Vision, Language, and Audio From LLM Fine-Tuning to Voice Agents, AR Interfaces, and Real-World Deployment
AI Engineering: Building Multi-Modal Intelligent Systems with Vision, Language, and Audio From LLM Fine-Tuning to Voice Agents, AR Interfaces, and Real-World Deployment
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PyTorch AI Agent Engineering: Build Intelligent, Scalable Machine Learning Agents with Real-World Python Workflows and Modern Deep Learning Tools: 1 (The Agent Engineering Series)
PyTorch AI Agent Engineering: Build Intelligent, Scalable Machine Learning Agents with Real-World Python Workflows and Modern Deep Learning Tools: 1 (The Agent Engineering Series)
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Engineering with Manus AI: Architecting Autonomous Agents, Memory Systems, and Multi-Agent Workflows for Next-Gen LLM Applications
Engineering with Manus AI: Architecting Autonomous Agents, Memory Systems, and Multi-Agent Workflows for Next-Gen LLM Applications
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Prompt Engineering for AI Agents: The Complete System Prompt Blueprint
Prompt Engineering for AI Agents: The Complete System Prompt Blueprint
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LLM Memory Engineering: Practical Strategies for Long-Term Memory in AI Agents and LLM Workflows
LLM Memory Engineering: Practical Strategies for Long-Term Memory in AI Agents and LLM Workflows
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Agentic AI Engineering Workshop: A Complete Guide to Design, Build and Develop Autonomous Agents that can Boost Productivity and Outperform Competitors
Agentic AI Engineering Workshop: A Complete Guide to Design, Build and Develop Autonomous Agents that can Boost Productivity and Outperform Competitors
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LangChain LLM Workflows: A Developer’s Guide to Prompt Engineering, AI Agents, Autonomous Ai and Memory-Driven Scalability (LLM-Driven Autonomous Agents)
LangChain LLM Workflows: A Developer’s Guide to Prompt Engineering, AI Agents, Autonomous Ai and Memory-Driven Scalability (LLM-Driven Autonomous Agents)
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Context Engineering with LLMs and AI Agents: Design Smarter Prompts, Memory Systems, and Context Pipelines for Intelligent Applications
Context Engineering with LLMs and AI Agents: Design Smarter Prompts, Memory Systems, and Context Pipelines for Intelligent Applications
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