Google introduces Gemini 3, its most intelligent AI model, enhancing reasoning and multimodal capabilities. It outperforms previous models in benchmarks and is available across Google products like the Gemini app, AI Studio, and Vertex AI.
Grammarly rebrands as Superhuman, unveiling a suite of AI‑powered products—including Superhuman Go, Coda, and Superhuman Mail—that work everywhere you type, proactively assist with writing, research, scheduling, and more.
**Summary of “Becoming Superhuman” (Grammarly → Superhuman announcement)**
- **Rebranding:** Grammarly is changing its corporate name to **Superhuman** while the Grammarly product will continue to exist under the new umbrella.
- **New product suite:** The Superhuman suite now bundles four offerings:
1. **Grammarly** (the trusted writing assistant)
2. **Coda** (an all‑in‑one collaborative workspace)
3. **Superhuman Mail** (an AI‑native email inbox)
4. **Superhuman Go** (the flagship AI layer that works everywhere).
- **Superhuman Go:**
- Functions in any app or web tab, not just a single interface.
- Proactively surfaces information, drafts replies, schedules meetings, and pulls data from CRMs, calendars, etc., **without the user having to ask**.
- Allows third‑party agents via the **Superhuman Agents SDK**, so companies can embed their own chatbots or tools directly into the Go experience.
- Early partner agents include Common Room, Radical Candor, Fireflies, Parallel, Speechify, Quizlet, and more are incoming.
- **Coda + Superhuman Mail integration:**
- Coda will turn meeting notes into action items and auto‑generate drafts/briefs.
- Superhuman Mail will auto‑draft context‑rich replies that reflect the user’s voice and pull in data from other tools.
- **Strategic vision:** By embedding AI into the exact places users work, Superhuman aims to make AI feel “ordinary” – no separate windows, prompts, or copy‑pastes. The goal is to let people think and create while the AI handles routine, repetitive tasks.
- **Leadership quote:** Shishir Mehrotra, formerly CEO of Grammarly, now CEO of Superhuman, frames the shift as moving from a single‑product AI helper to a proactive, ubiquitous AI platform that “fits where you work.”
Overall, the article announces Grammarly’s rebrand to Superhuman and introduces a broader, proactive AI ecosystem that extends beyond writing into task automation, research, scheduling, and collaboration across all user workflows.
**Summary of “Becoming Superhuman” (Grammarly → Superhuman announcement)**
- **Rebranding:** Grammarly is changing its corporate name to **Superhuman** while the Grammarly product will continue to exist under the new umbrella.
- **New product suite:** The Superhuman suite now bundles four offerings:
1. **Grammarly** (the trusted writing assistant)
2. **Coda** (an all‑in‑one collaborative workspace)
3. **Superhuman Mail** (an AI‑native email inbox)
4. **Superhuman Go** (the flagship AI layer that works everywhere).
- **Superhuman Go:**
- Functions in any app or web tab, not just a single interface.
- Proactively surfaces information, drafts replies, schedules meetings, and pulls data from CRMs, calendars, etc., **without the user having to ask**.
- Allows third‑party agents via the **Superhuman Agents SDK**, so companies can embed their own chatbots or tools directly into the Go experience.
- Early partner agents include Common Room, Radical Candor, Fireflies, Parallel, Speechify, Quizlet, and more are incoming.
- **Coda + Superhuman Mail integration:**
- Coda will turn meeting notes into action items and auto‑generate drafts/briefs.
- Superhuman Mail will auto‑draft context‑rich replies that reflect the user’s voice and pull in data from other tools.
- **Strategic vision:** By embedding AI into the exact places users work, Superhuman aims to make AI feel “ordinary” – no separate windows, prompts, or copy‑pastes. The goal is to let people think and create while the AI handles routine, repetitive tasks.
- **Leadership quote:** Shishir Mehrotra, formerly CEO of Grammarly, now CEO of Superhuman, frames the shift as moving from a single‑product AI helper to a proactive, ubiquitous AI platform that “fits where you work.”
Overall, the article announces Grammarly’s rebrand to Superhuman and introduces a broader, proactive AI ecosystem that extends beyond writing into task automation, research, scheduling, and collaboration across all user workflows.
This blog post details how to build a natural language Bash agent using NVIDIA Nemotron Nano v2, requiring roughly 200 lines of Python code. It covers the core components, safety considerations, and offers both a from-scratch implementation and a simplified approach using LangGraph.
As LLM-powered fraud becomes more sophisticated, i2c is combining machine intelligence with human oversight to reduce false positives, shorten investigation cycles, and improve customer experience while meeting regulatory requirements.
This article compares Model Context Protocol (MCP), Function Calling, and OpenAPI Tools for integrating tools and resources with language models, outlining their strengths, limits, security considerations, and ideal use cases.
Notes and reflections from the 2025 Protocol Symposium, covering topics like protocol entrepreneurship, digital institutions, protocol art, agentic systems, and practical applications of protocol thinking.
This article explores strategies for effectively curating and managing the context that powers AI agents, discussing the shift from prompt engineering to context engineering and techniques for optimizing context usage in LLMs.
A curated collection of Awesome LLM apps built with RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more. This repository features LLM apps that use models from OpenAI, Anthropic, Google, xAI and open-source models like Qwen or Llama.
Distiller is a pocket Linux box that runs Claude Code 24/7, offering remote access via QR code. It provides a full Claude Code enabled VS Code environment and terminal session, along with hardware I/O access for developers, firmware engineers, and indie hackers.
The article explores whether combining a command-line agent (like Claude Code or Gemini CLI) with Unix-like file system tools and SemTools is sufficient for complex tasks, particularly document search. It details a benchmark testing the limits of coding agents with and without SemTools, focusing on search, cross-referencing, and temporal analysis. The conclusion is that CLI access is powerful and SemTools enhances agent capabilities for document search and RAG.
