787 summarised stories about Agentic AI, each linking back to the original source. Browse all topics →
Product Hunt 2 months ago 18
TaskShell 2.0 is presented as a task management approach focused on being agent-first for more agentic productivity. The only concrete detail provided is the “2.0” version label. This indicates a new iteration of the concept, but the article text here does not include further specifics.
Sakana AI 25
Sakana AI株式会社が防衛省と「総合分析業務に必要なAI機能の調査・実証」の契約を締結した。契約日は令和8年7月29日で、防衛分野の情報分析官の業務にAIエージェント技術を適用して情報収集効率・分析能力・体系的な情報管理の3観点で実証する。これにより、防衛省の総合分析業務を強化するためのAI機能の社会実装が進む。
TechCrunch 2 months ago 48 ● 4 sources
Instinct’s private-access AI personal assistant has drawn privacy and security criticism from testers after it was found to access user devices and email and operate under terms that broadly grant the company ongoing rights to user materials and device-captured inputs. The Terms of Service include a “perpetual and irrevocable” license covering user materials, including for training the AI models. The backlash is prompting users to question whether this level of autonomy is acceptable and to push for fixes like data-deletion controls and clearer consent for actions taken on their behalf.
NVIDIA 2 months ago 44 ● 2 sources
NVIDIA announced that its Vera Rubin NVL72-based rack-scale system, NVIDIA Groq 3 LPX, is now in full production and is being adopted by multiple AI infrastructure partners for agentic inference. In an Artificial Analysis benchmark with Gemma 4 31B on 100,000-token contexts, it delivered 3,400 output tokens per second, about 4x faster than the nearest alternative platform. The update changes the inference stack by pairing long-context context processing on Rubin GPUs with LPX’s lower-latency token decode acceleration, and by extending NVIDIA’s Vera Rubin network fabric to enable larger, lower-cost agent workloads at scale.
Import AI 2 months ago 40
Import AI reports that AI’s impact on discovery is uneven across fields and highlights new methods for synthetic environment generation (SPADE) and hardware-aware GPU kernel optimization (Hawkeye). SPADE, trained from three Qwen3 backbones, reaches a suite average of 58.3 at the 30B-A3B scale. As a result, researchers get more effective ways to create training data and tune models for specific accelerators, alongside ongoing discussion about AI’s wider implications.
Product Hunt 2 months ago 9
Mossy launches as a Mac desktop plant that wilts the longer you skip breaks while an AI creates break tasks from a sentence and runs them with a timer.
Trending Topics 2 months ago 10 ● 4 sources
AI harnesses are being positioned as the software layer that turns language models into multi-step agents by providing tools, rules, state/memory, and an execution loop. One harness-effect study found Claude Opus 4.5 scored 45.9% on SWE-bench Pro inside a standardized scaffold and 55.4% with Claude Code. The result is that agent performance and cost increasingly depend on the harness (and its setup and security), creating a new competitive layer and locking in workflows and permissions beyond the base model.
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26 October 2026
Anthropic’s march toward an IPO turned into the defining AI thread of the day, not because the filing was just financial theatre, but because it laid bare the mechanics of how modern model companies intend to survive both scale and scrutiny. In its SEC S-1 for a Nasdaq debut under ticker ANT, Anthropic reported $16.3 billion in first-half revenue and an $80.7 billion net loss for the six months through June 2026, alongside a compute plan that’s hard to ignore: $542 billion to $567 billion on future infrastructure, with “Anthropic Direct” data centers aimed at reducing dependence on major clouds. The strategy is tightly coupled to product, too—Claude isn’t just a chatbot, it’s being pushed deeper into enterprises via first-party apps. More than half of the company’s $100,000-per-year customers use both the Claude platform and a first-party app, and Claude Code’s top 5% of enterprise users spend about 20× more than the average.
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