World Wire

Research agents already handle real knowledge work today. Teams delegate competitive mapping, due diligence, and literature review to them. However, most benchmarks test a single answer, not large evidence-backed collections. Perplexity targets that gap with a new open benchmark. Perplexity released WANDR (Wide ANd Deep Research) . It is an open benchmark and evaluation harness. It is built around 500 realistic, challenging data-collection tasks for knowledge work. WANDR is the wide sibling of Perplexity’s DRACO benchmark for deep research. DRACO asks whether an agent produces an accurate, complete, objective long-form report. WANDR instead asks whether it can build a large collection with evidence. What is WANDR At its core, WANDR tests two demands together. Wide means discovering a large, often open-ended set of qualifying entities. Deep means investigating every entity enough to support each claim with evidence. Combining both changes the problem for agents. A f...

Introduction Building an LLM application no longer requires wiring orchestration code by hand. A class of open-source platforms now exposes retrieval, agents, and workflows through visual canvases, web UIs, and plain-English prompts. These tools let developers prototype in minutes and self-host for data control. This article reviews ten open-source projects across three jobs: building LLM apps, building RAG systems, and building AI agents. Each entry covers what the tool does, its core capabilities, who it suits, and its verified license and repository. HKUDS AutoAgent Repository: github.com/HKUDS/AutoAgent · License: MIT · Paper: arXiv:2502.05957 AutoAgent is a zero-code agent framework from the University of Hong Kong Data Intelligence Lab . You describe a goal in natural language. The system then constructs tools, agents, and multi-agent workflows without manual coding. It ships an agent editor, a workflow editor, and a ready-to-use research...