AI and programming enthusiast, scratching the surface of emerging tech trends through tutorials, blog posts and analysis, all centered on the intersection of AI, machine learning and cloud.
I frequently discuss emerging trends in AI here on my blog, and one that's truly transforming the AI economy is Model-Context Protocol, or MCP. This isn't just another buzzword; imagine an AI that can orchestrate almost every digital service you use daily – think your email, cloud
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.
Recently, I came across an intriguing post from an influencer demonstrating how to generate n8n workflows using Claude. This method involved creating and saving various files within Claude projects. While the idea of using AI to generate n8n workflows is certainly appealing, this particular approach has a significant drawback: the
When you're writing a blog post with a lot of text, adding variety can make it much more engaging for your readers. While Artificial Intelligence (AI) can certainly help with many aspects – like structuring your content, doing research, or even creating diagrams right within your prompt – there'
I've spoken a lot in the past about open-source chatbots like OpenWebUI, with their rich feature set and powerful capabilities like prompt libraries, multi-user support, artifacts, and many more incredible features one can only dream of compared to ChatGPT or Claude.ai. However, another big player that has