Daniel Walsh

In this blog, I explore the ‘Lost Context Problem’ that often plagues RAG systems and present two innovative techniques: Late Chunking and Contextual Retrieval. These methods can significantly enhance the accuracy of your retrieval systems and minimize frustrating hallucinations. The Lost Context Problem The lost context problem is a significant challenge in retrieval-augmented generation (RAG) … Read more

Last Thursday, Make.com announced it would remove its Twitter/X integration due to new API pricing changes, leaving many users scrambling for alternatives. In this blog, I’ll walk you through three effective methods to keep your X scenarios operational even after the hard deadline of May 30th. The Announcement and Its Impact Make.com announced the removal … Read more

In this blog, I dive into the recently launched AI agent system from Make.com and compare it against the established AI agents from n8n. By breaking down their features, usability, and overall performance, I aim to help you choose the best platform for your automation needs. User Experience (UX) Creating AI agents in n8n is … Read more

Last week, Make.com announced the removal of its Twitter integration due to new API pricing changes, leaving many users in a bind. In this post, I’ll share three effective methods to keep your X scenarios running smoothly, even after the May 30th deadline. Introduction to the Change Make.com recently announced the removal of the Twitter … Read more

In this blog, I explore the revolutionary Agentic RAG blogging system I developed using N8N. This approach overcomes traditional limitations, enabling AI agents to seamlessly gather and synthesize information from multiple data sources, resulting in more accurate and engaging content. Demo of Agentic RAG In this section, I’ll walk you through a live demo of … Read more

In this blog, I explore Cache-Augmented Generation (CAG), a groundbreaking retrieval method that taps into server-side memory from OpenAI, Anthropic, and Google Gemini. I compare it with traditional Retrieval-Augmented Generation (RAG) to determine which method is more efficient and effective for various applications. Introduction to CAG and RAG Cache-Augmented Generation (CAG) and Retrieval-Augmented Generation (RAG) … Read more

MCP, or Model Context Protocol, promises to revolutionize how AI agents interact with various software tools. In this blog, I’ll take you through the capabilities of MCP, how it differs from traditional approaches, and how to set it up within N8N for seamless automation. Introduction to MCP MCP, or Model Context Protocol, is a groundbreaking … Read more

In this guide, I’ll walk you through the essential process of polling APIs in Make.com. Polling is a critical technique when webhooks aren’t an option, helping you avoid common pitfalls like API overload and wasted operations. Understanding Polling vs. Webhooks Polling and webhooks are two methods for receiving updates from a service. Webhooks are like … Read more

In this blog, I’ll walk you through how to harness the power of MidJourney for automated image generation using Go API and Make.com. Even though MidJourney lacks an official API, there’s a way to streamline your creative process like never before. Introduction to MidJourney and Go API MidJourney is a powerful tool for generating images … Read more

In this blog post, I’ll guide you through the integration of AI-powered browser agents into your workflows using N8N and Make.com. We’ll explore the capabilities of Browser Use, an open-source alternative, and how to effectively utilize it for automation tasks. Introduction to AI Browser Agents AI browser agents represent a significant advancement in automation technology. … Read more