Agentic AI

Most LLM brokers work nicely for brief tool-calling loops however begin to break down when the duty turns into multi-step, stateful, and artifact-heavy. LangChain’s Deep Agents is designed for that hole. The venture is described by LangChain as an ‘agent harness‘: a standalone library constructed on high of LangChain’s agent constructing blocks and powered by…

What if AI-assisted coding grew to become extra dependable by separating product planning, engineering evaluate, launch, and QA into distinct working modes? That is the thought behind Garry Tan’s gstack, an open-source toolkit that packages Claude Code into 8 opinionated workflow abilities backed by a persistent browser runtime. The tookit describes itself as ‘Eight opinionated…

In this tutorial, we build a Meta-Agent that designs other agents automatically from a simple task description. We implement a system that analyzes the task, selects tools, chooses a memory architecture, configures a planner, and then instantiates a fully working agent runtime. We go beyond static agent templates and instead build a dynamic, self-configuring architecture…

The era of the ‘Copilot’ is officially getting an upgrade. While the tech world has spent the last two years getting comfortable with AI that suggests code or drafts emails, ByteDance team is moving the goalposts. They released DeerFlow 2.0, a newly open-sourced ‘SuperAgent’ framework that doesn’t just suggest work; it executes it. DeerFlow is…