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Tutorials, how-tos and deep dives on AI, .NET, C#, cloud and developer tools, written by the community.
Unlock the power of LangChain! Understand the core differences between Chains and Agents for building AI applications. Chains offer structured, predictable workflows, ideal for tasks like text summarization. Agents provide dynamic reasoning and tool selection, perfect for AI assistants and complex problem-solving. Choose the right approach for optimal results!
Build a real-time typing speed test website using HTML, CSS, JavaScript, and Make.com for backend automation. This project showcases a hybrid approach, combining front-end coding with no-code AI automation to eliminate server-side code. Measure your WPM, accuracy, and enjoy dynamic text from the Bacon Ipsum API. Explore AI-driven email notifications and workflow automation for a seamless user experience. Try it now!
Build your own personal AI agent using Zapier webhooks, Next.js, and Vercel! This project automates tasks like sending emails, scheduling calendar events, and performing web searches through simple text prompts. Learn how to integrate Gmail, Google Calendar, and more to create a powerful, no-code digital assistant that boosts productivity and saves you time. Explore the potential of prompt-based automation and API integrations.
Discover how to build a powerful Lost and Found app without writing a single line of code! This project leverages Zapier, Airtable, Gmail, and Webflow/Glide to automate the process of reporting, tracking, and matching lost items. Learn how to create automated workflows, smart matching systems, and instant notifications using no-code tools. Perfect for citizen developers!
Discover how to build a dynamic AI portfolio using Make.com for automation! This project showcases a visually engaging website with integrated no-code workflows, intelligent features, and AI-powered design. Learn how to automate contact forms, track visitor interactions, and continuously update your portfolio without backend coding. Explore the fusion of creativity, automation, and AI for a scalable online presence.
Siddhant Mohan Jha shares his automated portfolio website built with Next.js, Zapier, and Vercel. This project showcases skills, projects, and a fully automated contact form. Learn how to build modern web apps, use API routes, automate workflows, and deploy live projects. Test the live demo and see instant confirmation emails in action! Discover the power of combining development and automation for a seamless user experience. Explore the future improvements planned for this dynamic portfolio.
Gödel’s AgentOS is presented as an agentic AI architecture that combines meta-reflection, governance, memory, and validation to support accountable reasoning and decision-making.
Discover how AI agents are revolutionizing supply chains by moving beyond static algorithms to dynamic, autonomous decision-making systems. Explore frameworks, use cases, challenges, and future trends.
Build and scale AI research teams with CrewAI and FutureAGI, covering agent roles, workflow design, deployment, monitoring, code examples, and human oversight.
Learn how agentic AI in Chrome, Edge, and Firefox can summarize content, automate browser tasks, and personalize browsing, along with its privacy, accuracy, and compatibility limitations.
This 2025 comparison dives deep into Zapier, Make (Integromat), and n8n, analyzing ease of use, integrations, customization, pricing, and real-world examples. Discover which platform best suits your needs, whether you prioritize simplicity, depth, or control for streamlining tasks and boosting productivity.
Build a local action agent using Streamlit, Ollama, and Llama-3-Groq-8B for tool use. This project demonstrates how to run a fully local agent without API keys, enabling tasks like weather checks, Wikipedia summaries, currency conversion, and calculations.
This article provides a comprehensive guide on enabling APIs for AI-first systems. It begins with an API refresher, then demonstrates building a FastAPI application in Python. The article then explains how to convert the API into an MCP (Machine Communication Protocol) server using FastMCP, making it consumable by AI agents like GitHub Copilot.
This article shows you how to extend existing models like Llama2 and Gemma with custom system prompts, parameters, and domain-specific knowledge. Create specialized AI assistants and chatbots quickly and efficiently, tailoring LLMs to your exact needs. Learn best practices for optimal performance and version control.
This AI technique blends information retrieval with text generation, ensuring accurate, up-to-date, and reliable AI responses. Discover how RAG enhances chatbots, search engines, and more across healthcare, education, and business, grounding AI in factual truth for superior performance.
Learn best practices for building effective tools for LLM agents. This guide covers prototyping, evaluation, and agent collaboration for tool improvement. Discover key principles like clear namespacing, meaningful responses, and context efficiency. Optimize tool design for agent use, not just API wrapping, to enhance reliability and performance in real-world scenarios.
Unlock the power of Retrieval Augmented Generation (RAG)! This article explains why embeddings are crucial for LLMs like GPT, LLaMA, and Mistral when dealing with large datasets. Learn how RAG uses vector databases and embeddings to efficiently retrieve relevant information, grounding answers, scaling knowledge, avoiding hallucinations, and keeping data fresh.
Unlock the potential of AI Agents by setting up an MCP (Meta Context Protocol) server in Python. This guide provides a step-by-step walkthrough, demonstrating how to create an MCP server, define prompts and tools, and integrate it with VS Code Copilot. Enhance your AI agent's reasoning and orchestration capabilities, enabling it to tackle complex tasks and seamlessly connect with external systems.
Monitor Google News for specific keywords and get instant Telegram alerts using Make.com. This setup avoids scraping and proxies, delivering timely updates directly to your chat.
Learn how AI agents plan, use tools and APIs, automate workflows, and collaborate in multi-agent systems across software development, business, and personal productivity.
AI's real threat isn't job automation, but the erosion of human creativity, concentration of power, manipulation, and ethical dilemmas it poses. Act now!
Build custom AI agents in .NET using Semantic Kernel. Learn to control behavior with tools, memory, planning, and policies for predictable, repeatable results.
Strands Agents SDK with MCP enables developers to connect to AWS MCP servers for documentation, pricing, and architectural assistance. Build Python agents to automate tasks, integrate AWS tools, and deliver faster AI solutions.
This no-cost workflow delivers a clean daily RSS digest to Telegram using Make.com. It fetches, deduplicates, formats, and chunks news into one reliable message—ideal for teams, founders, and content monitors.
A clear, do-first roadmap from foundations to agentic systems and MCP/A2A interoperability.
Explore GenAI, AI Agents, & Agentic AI: from content creation to autonomous task completion & multi-step planning. Includes code, workflows, & cost models.
The Model Context Protocol (MCP) is an open standard that connects AI assistants to tools, data, and systems. Like a USB-C for AI, MCP streamlines integrations, enables workflows, and improves context-driven responses.
Compare MCP for AI agent access to tools and data with A2A for agent discovery, task management, and multi-agent collaboration.
Agent communication protocols define how autonomous components exchange intent, facts, and results.
Zapier and n8n are automation platforms: Zapier offers fast, no-code cloud workflows for non-developers, while n8n provides self-hosted, flexible, developer-friendly automation with advanced logic and API control.
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