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Prompt Engineering

System Prompts: How to Write Effective LLM Instructions

System prompts define how your LLM behaves. Here's how to structure them, what mistakes to avoid, and how provider-specific behavior affects your prompt strategy.

System Prompts · Prompt Engineering · Llms

Prompt Engineering

Chain of Thought Prompting: A Developer Guide

Chain of thought prompting makes LLMs reason through problems step by step. Here's when it works, when it doesn't, and how to implement it with practical patterns.

Chain Of Thought · Prompt Engineering · Reasoning

Prompt Engineering

Few-Shot Prompting: How to Guide LLMs with Examples

Few-shot prompting teaches LLMs by example instead of instruction. Here's how to choose examples, format them, and know when few-shot is the right approach vs. fine-tuning.

Few Shot Prompting · Prompt Engineering · Llms

Ai Engineering

How to Use Claude Across Excel and PowerPoint with Shared Context and Skills

Learn how to use Claude's shared Excel and PowerPoint context, Skills, and enterprise gateways for faster analyst workflows.

Anthropic · Claude · Excel

Ai Coding

Agent Skills vs Cursor Rules: When to Use Each

Cursor has both rules and skills for customizing the AI agent. They overlap, but they're not the same. Here's when to use each and how they interact.

Agent Skills · Cursor Rules · Cursor

Ai Agents

How to Add Memory to AI Agents

AI agents without memory forget everything between turns. Here's how to implement conversation buffers, sliding windows, summary memory, and vector-backed long-term recall.

Ai Agents · Memory · Conversation History

Ai Coding

How to Create Your First Agent Skill

A step-by-step guide to writing an agent skill from scratch: directory structure, SKILL.md format, effective descriptions, common patterns, and a complete working example.

Agent Skills · Cursor · Claude Code

Ai Agents

How to Evaluate and Test AI Agents

Evaluating AI agents requires different metrics than evaluating LLMs. Here's how to measure task completion, trajectory quality, tool-use accuracy, and regression across agent systems.

Ai Agents · Evaluation · Testing

Ai Coding

What Are Agent Skills and Why They Matter

Agent skills are portable packages of instructions that extend AI coding agents. Here's what they are, how they work, and why the open standard changes how developers work with AI tools.

Agent Skills · Cursor · Ai Coding

Ai Engineering

How to Reduce LLM API Costs in Production

LLM API costs add up fast in production. Here are the practical strategies that work: prompt caching, model routing, batching, output limits, and cost-per-task tracking.

Llm Costs · Prompt Caching · Ai Engineering

Ai Engineering

LLM Observability: How to Monitor AI Applications

Traditional monitoring doesn't cover LLM applications. Here's what to log, how to trace multi-step chains, and how to detect quality regressions before users do.

Observability · Monitoring · Llm Ops

Ai Engineering

How Function Calling Works in LLMs

Function calling lets LLMs interact with external systems by requesting structured tool executions. Here's how the loop works, how to define tools, and what to watch for across providers.

Function Calling · Tool Use · Llms

Ai Agents

How to Build Stateful AI Agents with OpenAI's Responses API Containers, Skills, and Shell

Learn how to use OpenAI's Responses API with hosted containers, shell, skills, and compaction to build long-running AI agents.

Openai · Responses Api · Ai Agents

Ai Engineering

How to Stream LLM Responses in Your Application

Streaming LLM responses reduces perceived latency and improves UX. Here's how server-sent events work, how to implement streaming with OpenAI and Anthropic, and what to watch for in production.

Streaming · Llms · Server Sent Events

Ai Agents

Multi-Agent Systems Explained: When One Agent Isn't Enough

Multi-agent systems use specialized AI agents working together on complex tasks. Here's how they work, the main architecture patterns, and when they're worth the complexity.

Multi Agent · Ai Agents · Crewai

Prompt Engineering

Prompt Engineering Complete Guide

A complete guide to prompting. Why it's structured thinking, the three components of a good prompt, common mistakes, and advanced techniques like chain of thought and few-shot learning.

Prompt Engineering · Ai · Productivity

Ai Engineering

How to Evaluate AI Output (LLM-as-Judge Explained)

Traditional tests don't work for AI output. Here's how to evaluate quality using LLM-as-judge, automated checks, human review, and continuous evaluation frameworks.

Evaluation · Llm As Judge · Ai Engineering

Ai Engineering

How to Run IBM Granite 4.0 1B Speech for Multilingual Edge ASR and Translation

Learn how to deploy IBM Granite 4.0 1B Speech for fast multilingual ASR and translation on edge devices.

Speech Models · Edge Ai · Multilingual Asr

Ai Agents

AI Agents vs Chatbots: What's the Difference?

Not every AI chatbot is an agent, and not every task needs one. Here's the real distinction between agents and chatbots, the spectrum between them, and when each makes sense.

Ai Agents · Chatbots · Ai Engineering

Ai Engineering

Context Engineering: The Most Important AI Skill in 2026

Context engineering is replacing prompt engineering as the critical AI skill. Learn what it is, why it matters more than prompting, and how to manage state, memory, and information flow in AI systems.

Context Engineering · Prompt Engineering · Rag