2026

Feb 28

Microsoft Agent Framework - Agent Skills

Microsoft Agent Framework Workflows Agents Skills 📚 Microsoft Agent Framework

Latest release of Microsoft Agent Framework offers support for Agent Skills. We will explore implementing a practical use case for Skills with MAF.

Feb 28

Google ADK - Agent Skills

Google Agent Development Kit Agents Skills 📚 Google ADK

Dive into a powerful new feature in Google ADK: Agent Skills. We will explore what Agent Skills are, why they matter, and how to implement a practical use case.

Feb 15

GitHub Agentic Workflows

GitHub Agentic Workflows Agents 📚 GitHub Agentic Workflows

GitHub Agentic Workflows let you write automation in natural language. Instead of stitching together YAML steps, shell scripts, and third-party Actions, you describe what you want an AI agent to accomplish and give it the tools to do it.

Feb 6

Agent skills vs Model Context Protocol - [How] do you choose?

Agent Skills MCP 📚 Agents

Agent Skills and MCP are a hot topic. Understanding these standards genuinely overlap, where they serve fundamentally different purposes, and where each falls short, is essential for anyone building agent-powered systems.

2025

Dec 23

Google ADK - OpenAPI tools, agents-as-tools, authentication, and long-running operations

Google Agent Development Kit Agents 📚 Google ADK

Your agent needs to talk to the outside world. It needs to call REST APIs, delegate complex work to specialized agents, authenticate with protected services, and kick off operations that take minutes instead of milliseconds. Google ADK provides four powerful patterns to make all of this possible.

Dec 20

Google ADK - MCP tools

Google Agent Development Kit Agents 📚 Google ADK

An agent that can only use the tools you hard-code into it has a ceiling. The Model Context Protocol (MCP) shatters that ceiling by giving your ADK agents a standardized way to discover and use tools hosted anywhere — local processes, remote servers, or cloud services.

Dec 18

Google ADK - Runner and execution architecture

Google Agent Development Kit Agents 📚 Google ADK

You have agents, tools, callbacks, and sessions. But what actually runs them? The Runner is the central orchestrator that powers every agent interaction in Google ADK, driving the event loop that connects all these pieces together.

Dec 12

Google ADK - Callbacks

Google Agent Development Kit Agents 📚 Google ADK

Callbacks are user-defined functions that hook into an agent's execution pipeline at predefined checkpoints. They let you observe, customize, and control agent behavior without modifying the ADK framework code.

Dec 5

Google ADK - Sessions, state, and memory

Google Agent Development Kit Agents 📚 Google ADK

LLMs are stateless. Every API call to an LLM is independent. The model does not inherently remember what was said before. Yet meaningful conversations are inherently multi-turn, contextual, and stateful.

Dec 3

Google ADK - types of agents

Google Agent Development Kit Agents 📚 Google ADK

Google Agent Development Kit (ADK) is a flexible and modular framework for developing and deploying AI agents. It offers different types agents.

Oct 20

Magentic workflows in Microsoft Agent Framework

Microsoft Agent Framework Workflows Agents 📚 Microsoft Agent Framework

If you need a workflow that can adapt its routing decisions based on what agents discover during execution, look no further. Magentic is for you!

Oct 18

Group chat workflows in Microsoft Agent Framework

Microsoft Agent Framework Workflows Agents 📚 Microsoft Agent Framework

Building dynamic multi-agent discussions where AI agents collaborate, debate, and converge on solutions with GroupChatBuilder

Oct 16

Handoff workflows in Microsoft Agent Framework

Microsoft Agent Framework Workflows Agents 📚 Microsoft Agent Framework

Learn how to orchestrate AI agents in a concurrent workflow using Microsoft Agent Framework's HandoffBuilder

Oct 16

Docker cagent - An introduction

Docker cagent Agents 📚 Docker cagent

Docker cagent is an open-source, multi-agent AI runtime that lets you build, orchestrate, and share teams of specialized AI agents — all defined declaratively in YAML.

Oct 10

Building persistent AI Agents with Microsoft Agent Framework and Microsoft Foundry

Microsoft Agent Framework Foundry Agents 📚 Microsoft Agent Framework

The Microsoft Agent Framework represents a significant improvement in developer experience over the raw Foundry SDK. While the native SDK gives you complete control, the Agent Framework provides less boilerplate, type-safe tools, consistent patterns, and resource safety.

Oct 4

Building AI Agents with Microsoft Agent Framework

Microsoft Agent Framework Agents 📚 Microsoft Agent Framework

The world of AI agents is evolving rapidly, and Microsoft's Agent Framework provides a powerful, unified foundation for building intelligent agents that can reason, take actions, and interact with users naturally. In this blog post, I'll walk you through a series of practical examples that demonstrate how to create and use Azure AI agents using MAF and Python.

Oct 3

Getting Started with Foundry Agents

Microsoft Foundry Agents 📚 Microsoft Foundry

Microsoft Foundry (formerly Azure AI Foundry) is a unified system for building intelligent agents. It is a platform that provides models, tools, frameworks, and other aspects such as observability, guardrails, and enterprise-ready governance for creating AI agents.

Oct 2

Introduction to Microsoft Agent Framework

Microsoft Agent Framework Agents 📚 Microsoft Agent Framework

Microsoft Agent Framework is an open-source development kit for building AI agents and multi-agent workflows.

Sep 8

Azure AI Search - Vectorization, Custom Skills, and RAG

Azure AI Search 📚 Azure AI Search

In this article, we cross into vector territory. We will chunk documents using the Text Split skill, generate embeddings with Azure OpenAI, store them in a vector-enabled index, and run both vector and hybrid queries.

Sep 2

Azure AI Search - Getting Started

Azure AI Search 📚 Azure AI Search

Creating an enterprise AI application? Does your application need access to enterprise data and web content? Azure AI Search is the answer.

Jul 17

Local model serving - Using Foundry Local

inferencing local serving 📚 Local LLM Serving

There are several options available for running Large Language Model (LLM) inference locally. Foundry Local by Microsoft is a new entrant.

Jul 16

Local model serving - Using Docker model runner

inferencing local serving 📚 Local LLM Serving

Docker Model Runner — a faster, simpler way to run and test AI models locally, right from your existing workflow. Whether you’re experimenting with the latest LLMs or deploying to production, Model Runner brings the performance and control you need, without the friction.

Jul 15

Local model serving - Using LM Studio

inferencing local serving 📚 Local LLM Serving

There are several options available for running Large Language Model (LLM) inference locally. LM Studio is one such option. It is more comprehensive and offers some great features.

Jul 14

Local model serving - Using Ollama

inferencing local serving 📚 Local LLM Serving

There are several options available for running Large Language Model (LLM) inference locally. Ollama is one such option and my favorite among all. Ollama offers access to a wide range of models and has recently enabled cloud-hosted models as well. It offers both CLI and GUI (chat interface) to interact with the loaded models.

Apr 6

Changes in Autogen release 0.5.1

autogen azure-openai python 📚 AutoGen

Know what went into AutoGen 0.5.1 -- the open framework for creating multi-agent systems.

2024

Feb 3

Devcontainers for cloud-native application development

📚 Containers

Development containers are a great way to develop modern applications. Cloud-native applications usually implement more than one service to provide the application functionality. Using dev containers for microservices-based application development requires more than one container. This is where using Docker Compose with dev containers is useful. This article explores creating a multi-container development environment using VS Code dev containers and Docker Compose.

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