Agno AI (formerly Phidata) launched in early 2025 as a fully open-source platform for building autonomous AI agents, no PhD required. It provides the building blocks to turn any language model into a reasoning, memory-enabled assistant that can use external tools. What Distinguishes Agno AI? * Model-Agnostic Flexibility: Plug in OpenAI
As of May 2, 2025, leading coding LLMs include OpenAI’s o3/o4-Mini series (≈80–90% Pass@1, 128–200 K context, balanced speed/cost), Anthropic’s Claude 3.7 Sonnet (≈86% HumanEval, 200 K context, top real-world task performance), Google’s Gemini 2.5 Pro (≈99% HumanEval, 1 M+
Enterprise AI prompts are essential tools for organizations seeking to unlock the full potential of artificial intelligence in business. If you’re searching for ways to maximize the value of enterprise AI prompts, understanding their role in customization, security, and ROI is crucial. These prompts aren't just simple
Artificial intelligence is changing the way businesses automate tasks, interact with customers, and accelerate growth. If you're searching for a straightforward way to leverage make.com AI agents for smarter automation, this guide will help you understand your options and get started quickly. We’ll explore the strengths
OpenAI function calling provides developers with a new level of precision and control when integrating language models into real-world applications. OpenAI function calling allows AI systems to interact with APIs in a structured, reliable, and manageable way. Developers can orchestrate interactions through external functions for better results that are easier
"Prompt orchestration," refers to the structured coordination of LLM prompts to guide AI models through complex tasks with accuracy and consistency. While AI models have unlocked new levels of automation and insight, their true value depends on how effectively humans can direct them—especially when tasks require more
Setting up a mistral system prompt is essential for anyone looking to get the most accurate and relevant results from Mistral AI’s language models. Creating effective prompts requires careful attention to detail—each instruction you provide directly shapes the model’s response. Whether your goal is to generate concise
Artificial intelligence is actively shaping how we work, learn, and create every day. If you’re searching for information about Gemini 2.5, Google’s latest AI model, this guide will show you how to unlock its full potential in both the Gemini Web App and Google AI Studio. Whether
When working with AI language models, the quality of your prompts directly shapes the results you get. If you’re searching for the best prompt manager to organize, optimize, and collaborate on AI prompts, this guide will help you navigate the top solutions available. As projects expand, managing dozens of
Claude MCP (Model Context Protocol) is transforming how AI models connect with external tools and data sources. Developed by Anthropic, this open standard introduces a universal interface that enables AI systems to access real-time data, perform tasks, and interact with various APIs seamlessly. Claude MCP is a groundbreaking advancement in
Prompt chaining is a method that significantly enhances the performance of large language models (LLMs) and prompt chainers are tools that make chaining easier for you. By breaking down complex tasks into manageable prompts, this process guides models to ensure precision and reduce errors in tasks like document summarization and
The question "Is prompt engineering dead?" is on the minds of many as artificial intelligence continues its rapid advancement. Prompt engineering, the art and science of crafting effective inputs to guide AI models towards producing desired outputs, is at a crucial turning point. As AI evolves at an