Erich H.

113 posts

What is Anthropic's Model Context Protocol (MCP)?

One persistent challenge in AI has been connecting powerful LLMs to the vast array of external data sources and tools necessary for real-world applications. Anthropic's Model Context Protocol (MCP), introduced in late November 2024, offers a promising solution. In short, MCP is an open, standardized client-server architecture designed

LLM Agents vs. Function Calling: An Analysis of Techniques

As LLMs find applications in different sectors, it's become crucial to enable them to interact with the real world and perform tasks beyond simple text generation. Two primary methods have emerged to address this need: LLM Agents and Function Calling. In short, LLM Agents are modular AI systems

OpenAI API Playground: Explore & Test AI Models

The OpenAI API Playground is a fantastic tool for initial experimentation with OpenAI's models. It allows developers to quickly test prompts, adjust parameters, and see immediate results without writing code. However, for serious application development, the Playground has limitations in prompt management, experiment tracking, and team collaboration. This

Building Your First AI Agent: A Beginner's Guide

AI agents are programs that can perform tasks, make decisions, and even learn, all with a degree of autonomy. This guide provides a beginner-friendly introduction to the world of AI agents, explaining core concepts and walking you through building your first agent using Python. Table of Contents * Introduction * Basic AI

AutoGen vs. LangChain: Choose the Right Framework

Developing applications powered by LLMs presents unique challenges: managing context, integrating external data, orchestrating multi-step reasoning, and ensuring scalability. This is where frameworks like AutoGen and LangChain come in. AutoGen (developed by Microsoft) and LangChain are two popular open-source frameworks designed to simplify the development of LLM-powered applications. While both

Claude 3.7 Sonnet vs OpenAI O1: An In-Depth Comparison

Anthropic’s Claude 3.7 Sonnet and OpenAI’s O1 represent the latest advancements in AI reasoning, pushing the boundaries of mathematical logic, coding proficiency, and scientific analysis. While Claude 3.7 Sonnet boasts an adaptive reasoning approach optimized for real-world applications, OpenAI O1 is engineered for rigorous multi-step problem-solving

Model-Agnostic Prompts: What they are and how to use them

New LLMs emerge frequently, each boasting improvements in performance, cost-effectiveness, or specialized capabilities. As a prompt engineer, how can you harness the power of these advancements without being locked into a single model or constantly rewriting your prompts? The answer lies in model-agnostic prompts. Model-agnostic prompts are versatile instructions designed

From Beginner to Advanced: AI Prompt Engineering Best Practices

Artificial intelligence has rapidly evolved, with large language models (LLMs) and other generative AI tools becoming increasingly accessible. But to truly harness the power of these models, from ChatGPT to image generators, you need to master the art of the prompt. This guide provides a comprehensive overview of prompt engineering,

Grok 3 vs o3 Comparison

On February 17th, xAI’s Grok 3 made its debut into the world, to much fanfare. In a livestream demo, it was revealed that Grok 3 is being deployed with a reasoning model. So, it’s natural to want to compare it with other, similar reasoning models such as OpenAI’

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