Agent Deck is a free, open-source Mac app that manages AI coding agents. It offers per-project agent customization, parallel session execution, GitHub issue integration, and a library for cherry-picking skills. Built on the Pi CLI, it provides a native UI for real-time monitoring and control.

Anthropic bans AI during job interviews and runs candidates through up to five rounds testing skills, values, and ethical thinking. Salaries go up to $850,000, and some applicants pay $4,600 for prep coaching run anonymously by current AI company employees.

At the 2026 China AIGC Industry Summit, Wang Xiaoye, Technical Director of Amazon Web Services, pointed out that 87% of enterprises claim to have deployed AI at scale, but only 10% have gained real production value. He emphasized that enterprise-grade Agent deployment must bridge four major gaps: model selection, construction complexity, usage threshold, and talent shortage. He introduced AWS's five-layer architecture—compute, model, data, harness platform, and agent applications—and products like Quick to help enterprises move from demo to production.

mitmwall is an egress WAF for Ubuntu using iptables and mitmproxy to block outbound traffic not on an allowlist, protecting against data theft by compromised packages, rogue AI agents, and malware. It features real-time monitoring, DNS filtering, credential injection, and a web interface.

Researchers with typically male names use coding agents more than twice as often as those with typically female names, even within the same discipline and career level, according to an Anthropic study. Economists lead at 39 percent, while education researchers sit at just four percent. The gender gap for coding agents is far wider than for general AI use.

Coinsignal launched a new benchmark ranking 13 AI models on cryptocurrency price prediction accuracy. OpenAI's GPT-5.4 leads with 73.8% average accuracy and 78.5% recent accuracy. The benchmark measures direction, range closeness, and range overlap.

Flathub updated its LLM policy to explicitly disallow AI for submissions and applications, aiming to maintain platform quality.

The hype around AI in biology overlooks the fundamental mismatch between software's clean APIs and drug discovery's fuzzy feedback loops, which makes machine learning uniquely challenging in this domain.

The article argues Chinese AI labs open source models not as a national strategy but as a commercial strategy to gain global attention and trust. Using DJI and Insta360 as examples, it emphasizes the importance of marketing on YouTube. Chinese labs lack international marketing capabilities, so open source is their only way into the global conversation. Future releases will include proprietary open source models and fine-tuned variants to set standards.

In this tutorial, we implement a practical use case with Loguru, a powerful, flexible, and production-ready logging library for Python. We start by building a clean, idempotent logging setup and then move step by step through structured logging, contextual logging, custom log levels, global patching, callable formatters, in-memory sinks, rich exception traces, JSON log files, custom rotation, compression, retention, async logging, threaded execution, multiprocessing-safe logging, and standard logging module interception. The tutorial includes self-verification checks and a benchmark to confirm correctness and performance.

AI's economic value remains largely invisible to GDP, creating 'Dark Output.' The article explores substitution and new dark output, and how service sector measurement flaws mask AI productivity, risking misreads of growth and bubbles.

Sales teams spend hours on repetitive tasks that can be automated. This article demonstrates how to build a multi-agent system with LangGraph to automate prospect research, lead qualification, and CRM updates, boosting speed, consistency, and scalability. The system uses three specialized agents orchestrated via a stateful graph, supporting conditional routing and parallel execution.

AI's ability to cheaply produce large code changes leads to frequent upstream refactoring, making it nearly impossible to maintain forks. Unlike human refactors, AI changes disregard downstream impact, causing quality degradation and merge conflicts.

Leading AI search agents such as GPT-5.4 and Kimi K2.6 appear to rely on memorized knowledge rather than conducting genuine web research on standard benchmarks. A study from Harbin Institute of Technology introduces LiveBrowseComp, a benchmark based on events from the last 90 days, which causes performance to collapse and reshuffles model rankings, revealing that current evaluations measure knowledge retention rather than search capability.

The τ0-World Model (τ0-WM), a 5B-parameter open-source embodied world model, is pre-trained on nearly 30,000 hours of data, including 17,800 hours of real-world teleoperation data. It incorporates test-time computation to let robots simulate and evaluate multiple action sequences before execution, achieving state-of-the-art results on long-horizon manipulation tasks.

Starting summer 2026, UC Berkeley Law bans AI use in all coursework and exams, covering conceptualization, outlining, drafting, revising, editing, and translating, to foster core cognitive skills and ethical obligations.

GoodSender is an email API for indie developers, AI startups, and small teams, emphasizing permission-based marketing, engagement tracking, and affordability. It offers a free tier of 100k emails/month, and $1 per additional 100k. Marketing emails require consent, while transactional emails are pre-cleared. Built-in engagement scoring and list hygiene are included. MCP integration coming soon.

A field-tested standard for building production-grade agentic products, featuring an autonomy ladder, five composition patterns, a 7-layer harness, and a set of Claude Code skills that put the standard into your editor. Distilled from practices of leading AI labs and practitioners.

Ghostbase is an AI agent platform that lets you describe tasks in plain English and automatically deploys agents on webhooks or cron jobs. Integrates with 300+ apps, LLM-powered, with free tier and paid plans. Currently in early access.

According to Epoch's internal capability metric (ECI), open-weight models take an average of 4 months to catch up with state-of-the-art closed models. ECI is a composite measure covering many benchmarks.

Professor Huang Chao from the University of Hong Kong proposes rebuilding digital infrastructure for the Agent era: instead of forcing AI to mimic human interfaces, make software speak AI's native language (CLI). His team's lightweight open-source Agent nanobot has surpassed 200,000 downloads, and innovations like CLI-Anything demonstrate a paradigm shift toward AI-native computer use.

OWASP Agent Memory Guard is a runtime defense layer that screens every read and write to AI agent memory, blocking prompt injection, secret leakage, and integrity tampering. It is the OWASP reference implementation for ASI06: Memory Poisoning. Supports LangChain, OpenAI Agents, AutoGen, and more. Benchmark: 92.5% recall, 0% false positive.

AI detection tool Pangram, despite high accuracy, faces reliability issues, false positives, and the risk of fueling witch hunts as reliance on it grows across education and media.

The proliferation of AI agents and bots is leading to a crisis of human agency, where people feel increasingly passive and disconnected from authentic online experiences. This article explores the cultural and psychological impacts of AI-generated content, the erosion of trust, and the unsettling shift from active participation to passive consumption.

Trajectory, working with UC Berkeley Sky Lab and Anyscale, built a concurrent multi-LoRA training stack for continual learning. It maps each RL experiment to a dedicated LoRA adapter on an always-hot engine, reporting a 2.81× end-to-end experiment-throughput gain over a single-tenant baseline with no reward regression. The code is open-sourced in NovaSky-AI/SkyRL.

A free AI-powered tool that searches over 32,000 Tenancy Tribunal decisions in New Zealand to help users understand their rental rights.

Anthropic calculates run-rate revenue by multiplying last 28 days of consumption sales by 13 and adding 12 times monthly subscription revenue, raising questions about revenue reporting practices.

This YouTube video page indicates the AI boom will affect local areas, but the provided description contains only standard YouTube metadata with no substantive information.

SnapName is a macOS app that automatically renames screenshots using a bundled local AI model (Gemma 4), ensuring privacy by not uploading images.

xAI's Grok Imagine Video 1.5 Preview leads the Image-to-Video Arena leaderboard with a score of 1473, surpassing ByteDance's Dreamina Seedance 2.0 and 40 other models. The ranking is based on over 1.15 million votes, highlighting the latest competitive landscape in AI video generation.