guide

MCP Server Architecture in Practice: Tools, Resources, Prompts, and Safe Invocation

MCP Server Architecture in Practice: Tools, Resources, Prompts, and Safe Invocation

Implement MCP servers with robust tool/resource contracts, safe invocation flows, and versioning strategies for production agent systems.

Agent Tool-Use Patterns: How LLMs Actually Wield APIs

Tool use is where agents meet the real world. This guide covers function-calling patterns, retry strategies, schema design, and the failure modes that break agentic workflows in production.

Multi-Agent Communication Protocols: How Agents Actually Talk to Each Other

When multiple agents collaborate, communication is the bottleneck. This guide compares MCP, A2A, shared-memory buses, and event-driven architectures for building reliable multi-agent systems.

The Enterprise AI Adoption Playbook: What Actually Gets Agents to Production

Enterprise AI pilots fail at alarming rates. The gap is not model quality but deployment discipline: eval loops, human-in-the-loop design, and incremental rollouts that survive contact with real users.

Inference Optimization in 2026: Where the Compute Actually Goes

Most inference costs hide in places engineers never check. This guide breaks down KV-cache management, speculative decoding, quantization trade-offs, and the batching strategies that cut serving costs in half.

AI Evaluation Frameworks 2026: Why Benchmarks Keep Lying

AI benchmarks are broken. Contaminated datasets, narrow metrics, and Goodhart's law mean top scores rarely predict real-world performance. Here is what evaluation frameworks actually need to measure in 2026.

Building RAG Systems That Actually Work

73% of enterprise RAG deployments fail, with 80% of failures traced to chunking decisions. This guide covers the implementation decisions that separate working RAG from abandoned prototypes.

Transformer Architecture Explained: The Engine Behind Every AI Model

Every frontier AI model runs on transformers. This guide explains self-attention, scaling laws, Mixture of Experts, FlashAttention, and the modern innovations that determine cost and capability.

Deploying AI Agents to Production: What Actually Works

Only 5.2% of engineering teams have AI agents live in production. This guide covers the infrastructure, reliability, and cost management patterns that separate working deployments from abandoned prototypes.