Agentive AI

Building robust integrations between large language models (LLMs) and applications presents unique challenges. These challenges arise from the inherent unpredictability of LLMs, where their outputs can be inconsistent and prone to errors. To overcome these hurdles, developers have discovered crucial engineering patterns that enhance the reliability and effectiveness of LLM tool-calling. One such pattern is […]

The current web, designed with humans in mind, is struggling to adapt to the rapid rise of AI systems. These systems consume and act on information at a pace far exceeding human capabilities, demanding a new approach to web design. The solution lies in embracing HyperText, reimagining the web as a framework of executable semantics

The most critical initial step in any AI agent project centers around data. While it’s tempting to jump into model selection or architecture design, a well-defined, high-quality dataset is the bedrock of a successful agent. It underpins everything from product boundaries to effective training and rigorous testing. Think of the dataset as the agent’s education.

Artificial intelligence is experiencing a significant evolution, shifting from simple, reactive systems to proactive, intelligent agents. This transformation, known as Agentic AI, allows systems to act autonomously on behalf of users, making their own decisions and coordinating complex tasks across various fields. Unlike traditional AI, which primarily executes pre-programmed instructions, agentic AI demonstrates goal-driven behavior,

A lot of people are setting up their own AI servers, and with good reason. They provide a powerful, private resource for AI tasks. But after the initial setup, a common issue arises: what to *do* with it? One user, having established a llama.cpp server, is looking to maximize its potential beyond simple chatbot interactions.

The world of AI is rapidly evolving, and with it comes a need for streamlined solutions. Many developers are creating AI tools, GPT wrappers, and even fun persona agents. However, they often encounter hurdles when it comes to: securing a memorable domain name, hosting their creations without the complexities of a full development stack, and

As a Product Manager in the tech world, leveraging AI can significantly boost productivity and efficiency. Several readily available AI tools can streamline various aspects of the PM role. One useful application is using tools like v0 to quickly build a Minimum Viable Product (MVP), allowing for faster iteration and testing. For meeting management, Otter.ai

Advertisements for AI-powered agents designed to manage advertising campaigns on META platforms are increasingly common. These agents promise significant improvements in performance and return on investment (ROI) for their users. However, navigating these claims requires careful consideration. The allure of automated ad management is understandable. Business owners are often busy, and the complexities of platforms

A New AI Tool Automates Phone Outreach and Missed Calls Small businesses often depend on phone calls for their success but struggle to manage every lead and incoming call. A new tool is in development to address this problem. The tool promises to simplify the process of making initial contact, following up on leads, and

New to Multi-Agent Systems? Here’s How to Begin Building a multi-agent system (MAS) can seem daunting at first, especially for those new to the field. Several strategies can help beginners navigate the process and set themselves up for success. A key question that often arises is, where do you even begin? First, grasp the fundamentals.