World Wire

As AI coding agents grow more capable, a structural problem has emerged: speed without clarity. Developers generate working code in minutes, only to discover days later that it doesn’t match what the system actually needed. Spec-driven development (SDD) addresses this directly — by treating a structured specification as the source of truth and code as its generated output, rather than the other way around. This list covers the 9 AI tools that developers are actually using to implement SDD workflows in 2026. AWS Kiro kiro.dev | Docs | Models Kiro is an agentic IDE built around spec-driven development, designed to take developers from concept to production with structured rigor instead of iterative prompting. Rather than writing code and asking an AI to help along the way, Kiro requires developers to formalize intent first. It guides them through a three-phase process — Requirements, Design, and Tasks — producing three structured artifacts: requirements.md, desig...

OpenAI has launched a Codex Chrome extension for Mac and PC to streamline browser-based workflows that were previously difficult to handle via APIs or plugins. This release follows a trend where most users preferred working in a browser after the launch of “Computer Use,” allowing Codex to operate more effectively across various web-based tasks. What the Extension Actually Does Before this release, Codex had access to an in-app browser — a sandboxed browser built into the Codex desktop app itself — and a growing library of dedicated plugins for services like GitHub, Slack, Figma, and Notion. The new Chrome extension fills a gap those two approaches couldn’t cover: tasks that require your real, signed-in browser state. The Codex Chrome extension lets Codex use Chrome for browser tasks that need your signed-in browser state. It is intended for use when Codex needs to read or act on sites such as LinkedIn, Salesforce, Gmail, or internal tools. For everything ...

OpenAI released three new audio models through its Realtime API, each targeting a distinct capability in live voice applications: GPT-Realtime-2 for voice agents with reasoning, GPT-Realtime-Translate for live speech translation, and GPT-Realtime-Whisper for streaming transcription. Alongside the model releases, the Realtime API officially exits beta and is now generally available — a meaningful signal for developers who held off building production systems on it. All three models are available immediately through the OpenAI API and can be tested in the Playground. Together, they push voice applications past the basic question-and-answer loop — toward systems that can listen, reason, translate, transcribe, and act within a single conversation. GPT-Realtime-2: Voice Reasoning with a 128K Context Window The flagship release is GPT-Realtime-2, which OpenAI team describes as its first voice model with GPT-5-class reasoning. GPT-Realtime-2 can process harder requests, manage in...

In this tutorial, we explore CloakBrowser , a Python-friendly browser automation tool that uses Playwright-style APIs within a stealth Chromium environment. We begin by setting up CloakBrowser, preparing the required browser binary, and resolving the common Colab asyncio loop issue by running the sync browser workflow in a separate worker thread. We then move through practical automation steps, including launching a browser, creating customized browser contexts, inspecting browser-visible signals, interacting with a local test page, saving session state, restoring localStorage, using persistent browser profiles, capturing screenshots, and extracting rendered page content for parsing. Copy Code Copied Use a different Browser import os import sys import json import time import shutil import base64 import subprocess import concurrent.futures from pathlib import Path from datetime import datetime from textwrap import dedent def run_cmd(cmd, check=True, capture=False): print(f...

Inference efficiency has quietly become one of the most consequential bottlenecks in AI deployment. As agentic coding systems such as Claude Code, Codex, and Cursor scale from developer tools to infrastructure powering software development at large, the underlying inference engines serving those requests are under increasing strain. The LightSeek Foundation researchers have released TokenSpeed , an open-source LLM inference engine released under the MIT license and designed specifically for the demands of agentic workloads. The TokenSpeed engine is currently in preview status. Why Agentic Inference is a Different Problem To understand what makes TokenSpeed’s design choices meaningful, it helps to understand what makes agentic inference hard. Coding agents don’t behave like a typical chatbot turn. Contexts routinely exceed 50K tokens, and conversations often span dozens of turns. This creates simultaneous pressure on two metrics: per-GPU TPM (tokens per minute), wh...

Evaluating AI models trained on brain signals has long been a messy, inconsistent topic. Different research groups use different preprocessing pipelines, train models on different datasets, and report results on a narrow set of tasks — making it nearly impossible to know which model actually works best, or for what. A new framework from Meta AI team is designed to fix that. Meta Researchers have released NeuralBench , a unified, open-source framework for benchmarking AI models of brain activity. Its first release, NeuralBench-EEG v1.0 , is the largest open benchmark of its kind: 36 downstream tasks, 94 datasets, 9,478 subjects, 13,603 hours of electroencephalography (EEG) data, and 14 deep learning architectures evaluated under a single standardized interface. https://ift.tt/yCqbYBP The Problem NeuralBench Solves The broader field of NeuroAI where deep learning meets neuroscience has exploded in recent years. Self-supervised learning techniques originally developed for...