What AI Agent Platforms Are Available? How to Transition into an Agent Engineer?
What AI Agent platforms are available? There are two major categories: Workflow platforms (Dify — most open-source friendly; Coze — easiest to get sta…
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From Chatbots to Personal AI Agents: The Infrastructure Developers Actually Need
title: Your AI Agent Should Not Be Locked to One LLM Provider published: false description: Why serious AI agents need a provider-agnostic architectur…
Simple A2A implementation with Strands
A2A has become like a standard for enabling agent to agent communication, we could use the a2a-sdk for running and configuring the a2a server and its …
Harness: Turn a One-Line Prompt Into a Full Agent Team for Claude Code
You have Claude Code. You want to build something ambitious — a deep research pipeline, a full-stack app scaffold, a code review system. You could wir…
Moving Beyond the Context Window: The Agentic Memory Architecture
I’ve spent a lot of time lately thinking about why some LLM agents feel "intelligent" while others just feel like chatbots with a slightly better prom…
BoxAgnts Introduction (6) — Agent Multi-Turn Conversation and Tool/Skill Invocation
If you've only chatted with ChatGPT, you might think an AI Agent is simply "send a prompt to the API, display the response." The reality is far more c…
# agents.md: Teaching AI Agents How to Scrape (The Future of Web Automation)
You're building a Scrapy scraper. You ask Claude Code for help. "Add pagination to my spider." Claude reads your code. It sees scraper.py, settings.py…
Understand Anything: Turn Any Codebase Into an Interactive Knowledge Graph
You join a new team. The codebase has 200,000 lines of code, no docs worth reading, and the one engineer who knew everything just left. Where do you s…
Agentic Analytics: Architecture, Context, and Why the Semantic Layer Does the Heavy Lifting
An agentic analytics system is one where LLM-powered agents autonomously break a data question into sub-tasks, retrieve relevant context, execute quer…
Six Principles in Practice: How an Agentic E2E Found 11 Production Bugs in 8 Runs
Eight runs, eleven bugs I ran my E2E testing system on a production ecommerce platform eight times in a row – across five different business modules, …
The Missing Engineering Stack for Production AI Agents
The "build an agent in 5 minutes" tutorials get you to a demo. They don't get you to production. Here's the field guide for the four primitives that d…
Maintaining an Agent-Searchable Profile: Public Impressions, Semantic Tags, and Real-Time Refresh
AI agents are becoming a new interface not only for finding people, but also for maintaining the profile that other agents search. Instead of opening …
Modernizing Legacy Systems Using Agent Harnesses TDD and the Seam Model
Over the past few months, I’ve been investing a lot of time building agentic development workflows for real production environments. Not only prompts.…
Production-Grade Engineering Skills for AI Coding Agents
AI coding agents have revolutionized how we write software. They can implement features, fix bugs, and review code at incredible speed. But there's a …
Skill-Based Sub-Agents with LangGraph4j and Spring AI
Combine Tools & Skill to create Agent Modern agentic systems usually expose two strong but separate abstractions: Tools , which give an LLM execut…
KiroHub: Generate a Kiro Skill in 60 Seconds Built With Bedrock Registry and AgentCore Harness
I used two Amazon Bedrock AgentCore capabilities, Amazon Bedrock Registry for hybrid search over 10k+ Kiro resources, and AgentCore Harness for testin…