Anthropic announces Claude Mods for Claude Code

#1 𝕏

Boris Cherny announced that Anthropic’s Claude Mods are landing now, highlighting a Tetris-in-Claude mod. The linked anthropics/claude-code issue includes the latest community update, technical details, and additional demos.

#2 𝕏

Google DeepMind shared a Google Blog link about WeatherNext 3, noting that advance visibility into rapidly changing weather helps teams balance power grids and match clean energy to everyday consumer demand.

Also covered by: @Google DeepMind

#3 𝕏

Google AI shared Dreambeans from Google Labs, an opt-in experience that connects information across Gmail, Calendar, Search, Gemini, and Google Photos face grouping to generate customized illustrated stories and relevant next steps. Daily in-app notifications surface new stories, while privacy filters and thumbs-down feedback give users control over personalization.

#4 𝕏

NVIDIA announced new SDKs, NIM microservices, playbooks and blueprints for its AI for Media collection at IBC2026. The tools can help verify potentially AI-generated footage, create smoother slow-motion sports replays and translate programming with lip-synced dubbing.

#5 𝕏

Aravind Srinivas announced expanded work with NVIDIA to bring fully local, unmetered AI to Microsoft Windows PCs with RTX GPUs using NVIDIA hardware and a Perplexity harness.

#6 𝕏

DeepLearning.AI recapped GPT-6 Astra, reporting that it tops the ARC-AGI-3 leaderboard while cutting token costs and ties Claude Fable 5.1 on Artificial Analysis’ Intelligence Index. For builders, it highlights asynchronous tool calls, retained reasoning memory across API calls, and efficient context management for scaling agents.

#7 𝕏

NVIDIA AI shared an engineering deep dive on tuning caching, memory, parallelism, decoding and more for the Nemotron 3 Ultra NIM. On four B200 GPUs, these optimizations supported up to 2.5x more concurrent users while maintaining 50 TPS/user.

#8 ▶️

Building a Software Factory that actually works (Full Course)

Greg Isenberg

#9 𝕏

LlamaIndex 🦙 shared a two-pass, just-in-time OCR workflow for ad-hoc data rooms: LiteParse provides a layout-aware first pass across 50+ formats—reportedly processing a full data room in 32 seconds—while LlamaParse handles only pages needing deeper extraction. The approach aims to avoid the cost and latency of parsing every page upfront.

#10 𝕏

Radio lets agents in Claude Code, Codex, or Cursor communicate in real time across machines by pasting one link. Agents get their own channel, where humans can answer questions or redirect work.

#11 𝕏

Harrison Chase said Slack is where agents are doing work and that Managed Deep Agents has a tight Slack integration. He shared a tutorial about the integration.

#12 𝕏

Guillermo Rauch said agents are only as effective as their proof-checkers, compilers, type systems, and linters, highlighting shadcn/lint as a way to keep agents aligned with design-system rules. He characterized verifiers and skills as the new “frameworks.”

#13 𝕏

Santiago said the Cline desktop app is available, open-source, and usable with open-weight models. He argued that agentic coding tools are shifting from terminal interfaces to desktop apps with better affordances.

#14 in

Peter Yang shared a video showing how to set up the 11 Grok Bots he currently uses: 3 for orchestration, long-term planning, and bot maintenance; 3 for growing his business; and 5 for saving time and money and improving his life. The video also shows the bots talking to one another.

#15 𝕏

claire vo 🖤 shared a link to a clairevo.com page about building a cursor-following portrait with Flora and Codex.

#16 𝕏

Thariq shared a conversation with Sid and Robert about building Claude Code, covering how much things have changed, the challenge of keeping up with model capabilities, and what they miss about software engineering before AI.

#17 in

Claire Vo recapped a How I AI episode with John Bai and Peng Zheng about the GrokBot design team’s use of AI agents. Demonstrations include a hyper-personal homepage maintained by Grok Bot, Figma Bro handling design production, and voice memos turned into production code.

#18 in

Greg Isenberg commented that agent harnesses loop models, provide tool and file access, manage memory, enforce rules, and retain job knowledge so builders can switch models and improve workflows through human corrections. He argues they could support outcome-based pricing across many of 800+ occupations, with OpenAI’s Agents API, Claude’s managed agents, Vercel’s eve, and LangChain making them easier to build.

#19 𝕏

Peter Yang recapped Brex CEO Pedro’s view that good AI products pair an agentic loop with tools exposed to a model. As an example, Brex built Jim, an AI recruiter that uses Greenhouse, LinkedIn, and other software to automatically deliver qualified candidates.

#20 𝕏

Sam Altman commented that American companies developing increasingly capable AI must act responsibly and that every frontier lab should provide confidence in its conduct. He discussed federal frameworks, Responsible Scaling Policies, safety cases for frontier reinforcement-learning runs, pacing progress, alignment and monitoring, and international coordination.