DevTech Insights

LLM Routing and Model Selection: Smart Gateways for Cost and Quality

Learn how to implement intelligent LLM routing and model selection strategies to optimize costs and maintain high-quality outputs in production systems.
LLM AI Engineering MLOps Cost Optimization Model Routing Production AI

Building Reliable Tool Calling for LLM Agents

Learn how to build robust, production-ready tool calling for LLM agents. Covers schemas, error handling, retries, and real-world patterns.
LLM Production AI Engineering Agents Tool Calling

Prompt Caching Strategies: Reducing Token Cost and Latency in LLM Applications

Learn how to implement prompt caching strategies to significantly reduce LLM API costs and latency. Practical guide with code examples for production systems.
LLM Cost Optimization Prompt Engineering Latency Reduction AI Infrastructure

LLM Observability: Tracing, Evaluations, and Langfuse Deep Dive

Master LLM observability with Langfuse. Learn how to implement tracing, automated evaluations, and production monitoring for reliable AI applications.
Observability LLM OpenAI MLOps Langfuse Python LLM Engineering

Building Multi-Agent Systems with LangGraph and Java

Learn how to build production-ready multi-agent systems in Java using LangGraph. Covers architecture, state management, and practical code examples.
Java LLM AI Engineering LangGraph Multi-Agent Systems

Agentic RAG: Combining Retrieval with Autonomous Agents

Learn how Agentic RAG transforms static retrieval systems into dynamic, autonomous workflows using LLMs, tools, and multi-step reasoning.
RAG LLM Machine Learning Agentic AI Software Engineering

Model Context Protocol (MCP): What Backend Devs Need to Know

Explore how Model Context Protocol standardizes AI-tool integration. Learn backend implementation strategies, architecture, and practical code examples for J...
Java LLM AI OpenAI Architecture Backend MCP Claude

Self-Hosting Open-Source LLMs: A Cost-Benefit Analysis for Engineering Teams

Discover if self-hosting open-source LLMs is worth it. We analyze hardware costs, inference performance, and operational overhead to help you decide.
LLM Open Source MLOps Cost Optimization Self-Hosting Inference

Building a Semantic Cache for LLM Calls with Redis

Learn how to build a semantic cache for LLM calls using Redis and embeddings to reduce costs and latency while maintaining response quality.
LLM Embeddings AI Redis Semantic Cache

Guardrails for LLM Applications: Input and Output Validation

Learn how to implement robust input and output validation for LLM applications. Explore techniques, tools, and best practices to ensure safety and reliability.
LLM Input Validation Output Validation AI Safety Guardrails