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Many of us — accountants and business owners alike — are familiar with the process of collecting invoices for every expense in order to maintain clean and complete bookkeeping records. Frankly, it's a task I hate. Sometimes, this process is simple. You might forward an invoice email, and your bookkeeping

You may have heard a lot about something called Model Context Protocol (MCP) in recent days and weeks, both in the news and here on Medium. This technology is becoming so widespread that it feels like almost every company with a digital product is getting worried about missing out and

Over the past couple of years, there has been an explosion in AI, particularly in the form of LLMs such as GPT and Gemini, which have spread to nearly every aspect of our digital lives. However, as these applications multiply, so does an underlying concern: the increasing risk of copyright

Model-Context Protocol (MCP) is a game-changing technology that's transforming how AI agents interact with information. It allows AI agents to communicate with various systems and analyze data from different sources on the fly, even without the user knowing their exact structure beforehand. When dealing with large datasets, we

In today's world, many of us frequently interact with AI models like GPT, spending significant time prompting, reading responses, and refining our queries. Through this process, we gain valuable experience and start to understand how "our" AI works, learning the best ways to phrase our requests

In a previous post, we discussed how to build an MCP-powered voice agent with real-time capabilities. This allowed you to use your own data, applications, and services to create an AI assistant for yourself or your customers, all using LiveKit in a local environment with OpenAI and Deepgram. In this

AI agents and their supporting technologies (RAG, MCP, Long Term Memory and many more) are becoming the foundation of AI-powered systems across all industries. Equipped with advanced AI language models (LLMs) and vast amounts of data, these agents can handle many tasks much faster and more affordably than human labor.