Philipp Schmid

Highlights: NVIDIA's curated collection of reusable AI agent skills, designed to accelerate development of agentic workflows. Provides modular, production-ready building blocks for common agent tasks.

Worth reading: Offers a practical, vendor-backed library of agent skills that can be directly integrated into projects, saving development time and leveraging NVIDIA's expertise.

Highlights: Playwriter is a Chrome extension and CLI that enables AI agents to control your browser by executing Playwright snippets in a stateful sandbox. It supports both CLI and MCP (Model Context Protocol) interfaces, making it easy to integrate with various agent frameworks.

Worth reading: It bridges the gap between AI agents and browser automation, offering a practical tool for testing and deploying agent-based workflows. The MCP support aligns with emerging standards for agent-tool interaction.

Highlights: Philipp Schmid read three technical reports: Kimi K2.5, Cursor Composer 2, and Chroma Context-1.

Worth reading: Shows what a leading AI developer is studying for state-of-the-art insights.

Highlights: Philipp Schmid predicts accelerated creation and building speed.

Worth reading: Reflects optimism about AI-driven productivity gains.

Highlights: Announcement of partnership between Google DeepMind and Korea to accelerate scientific discovery.

Worth reading: Shows Philipp Schmid's involvement in AI for science collaborations.

Highlights: Philipp Schmid reviews three technical reports: Moonshot AI's Kimi K2.5, Cursor's Composer 2, and Chroma's Context-1.

Worth reading: Shows his engagement with cutting-edge AI research and tools.

Highlights: He automated model creation using an AI agent, resulting in a 0.8B model overnight.

Worth reading: Demonstrates practical use of AI agents for rapid prototyping.

Highlights: A curated list of add-ons, hooks, tools, and skills for the pi coding agent, enabling users to extend its capabilities. It serves as a central resource for the pi-agent ecosystem, similar to awesome lists for other frameworks.

Worth reading: For developers using or evaluating the pi coding agent, this list provides a quick overview of available extensions and community resources, saving time in discovering integrations.

Highlights: Philipp Schmid read and shared three technical reports: Moonshot AI's Kimi K2.5, Cursor's Composer 2, and Chroma's Context-1.

Worth reading: Shows what a technical leader in AI is reading and learning about.

Highlights: Philipp Schmid expresses optimism about increased speed in creation and building.

Worth reading: Reflects his perspective on the accelerating pace of AI development.

Highlights: This post has engagement but the content is not fully captured.

Worth reading: Indicates active engagement with his audience.

Highlights: This post has high views but low likes.

Worth reading: Shows reach of his content.

Highlights: Philipp Schmid highlights a partnership between Google DeepMind and Korea to speed up scientific research.

Worth reading: Shows real-world application of AI in scientific discovery and international collaboration.

Highlights: Howcode is a desktop application for interacting with Pi, likely an AI assistant or coding tool. It provides a native UI for leveraging AI capabilities on the desktop, built with TypeScript for performance and reliability.

Worth reading: It offers a polished desktop experience for AI interaction, which could be useful for developers looking for a dedicated app to streamline their workflow with AI models.

Highlights: Philipp Schmid shares his reading of three recent technical reports: Moonshot AI's Kimi K2.5, Cursor's Composer 2, and Chroma's Context-1.

Worth reading: Provides insight into what a leading AI developer is studying to stay current.

Highlights: Philipp Schmid describes an experiment where an AI agent autonomously built a 0.8B model overnight by reading a repo and fetching training data.

Worth reading: Demonstrates the power of AI agents in automating model development.

Highlights: Philipp Schmid reflects on the accelerating pace of creation and building enabled by AI.

Worth reading: Captures the optimistic sentiment about AI's impact on productivity.

Highlights: Philipp Schmid read three technical reports: Kimi K2.5, Cursor Composer 2, and Chroma Context-1.

Worth reading: Shows his interest in cutting-edge AI developments from Moonshot AI, Cursor, and Chroma.

Highlights: He automated model building by instructing an AI agent to clone a repo and train a 0.8B model overnight.

Worth reading: Demonstrates practical agent-driven ML workflow automation.

Highlights: He believes AI will drastically accelerate creation and building processes.

Worth reading: Reflects his optimistic view on AI's impact on productivity.

Highlights: Philipp Schmid shares his reading of three recent technical reports from Moonshot AI, Cursor, and Chroma.

Worth reading: Provides insight into what an AI developer at Google DeepMind finds noteworthy in current AI research.

Highlights: Philipp Schmid expresses optimism about increased speed in creation and building due to AI.

Worth reading: Reflects a common sentiment in the AI community about accelerated development.

Highlights: Philipp Schmid highlights the importance of skills as extension points in AI agents.

Worth reading: Key insight for agent developers on building modular and distributable agent capabilities.

Highlights: Philipp Schmid read technical reports on Kimi K2.5, Cursor Composer 2, and Chroma Context-1.

Worth reading: Shows his interest in cutting-edge AI research and tools.

Highlights: Philipp Schmid believes AI will accelerate creation and building.

Worth reading: Reflects optimism about AI's impact on productivity.

Highlights: Skills are key extension points in agents due to flexibility and ease of use.

Worth reading: Insight into agent development trends.

Highlights: Philipp Schmid discusses how isolating tasks into focused agents improves reliability, with advances in planning and tool use.

Worth reading: Highlights evolution of agent architectures.

Highlights: Philipp describes an experiment where an AI agent autonomously built a 0.8B parameter model overnight.

Worth reading: Demonstrates the power of autonomous AI agents in model development.

Highlights: Philipp Schmid read three technical reports on AI topics.

Worth reading: Shows his engagement with recent AI research and tools.

Highlights: He reflects on the accelerating pace of creation and building.

Worth reading: Captures a sentiment about AI-driven productivity.

Highlights: He notes that Skills are a key extension point for agents.

Worth reading: Highlights a practical insight for agent development.

Highlights: Philipp Schmid reads and shares technical reports from Moonshot AI, Cursor, and Chroma.

Worth reading: Shows his interest in staying updated with latest AI research and tools.

Highlights: Philipp Schmid automated model training using an AI agent, resulting in a 0.8B model overnight.

Worth reading: Demonstrates practical use of AI agents for automating ML workflows.

Highlights: Philipp Schmid reflects on the accelerating pace of creation and building with AI.

Worth reading: Captures the sentiment of increased productivity in AI development.

Highlights: Philipp Schmid shares a guide on using Deep Research with the Gemini API.

Worth reading: Provides practical insights on leveraging Gemini's Deep Research capabilities via API.

Highlights: Philipp Schmid tweets about a partnership between Google DeepMind and Korea for scientific discovery.

Worth reading: Highlights a significant collaboration in AI-driven scientific research.

Highlights: Introducing the Gemini Interactions API, a unified RESTful endpoint for models and agents, starting with the Gemini Deep Research Agent.

Worth reading: This API simplifies access to multiple Gemini capabilities through a single interface.

Highlights: Philipp posted about using Deep Research with the Gemini API, linking to his blog.

Worth reading: Explains how to leverage Gemini's Deep Research capability programmatically.

Highlights: Philipp shares a guide on using Deep Research with the Gemini API.

Worth reading: Useful for developers looking to integrate Gemini's Deep Research capabilities via API.

Highlights: Philipp Schmid shares a guide on running a local coding agent using Gemma 4 and Pi.

Worth reading: Provides practical steps for deploying a local coding agent, relevant for developers interested in on-device AI.

Highlights: Announces the Gemini Interactions API, providing a unified RESTful interface for Gemini models and agents, starting with the Deep Research Agent.

Worth reading: Highlights a new API that simplifies access to Gemini models and agents, useful for developers integrating AI capabilities.

Highlights: Philipp Schmid reads technical reports from Moonshot AI, Cursor, and Chroma, indicating interest in AI research and tools.

Worth reading: Shows his engagement with cutting-edge AI developments.

Highlights: He shares a Spotify Engineering article on coding agents and context engineering.

Worth reading: Relevant for those interested in AI-assisted coding and context engineering.

Highlights: Philipp Schmid published a guide on building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Shows practical implementation of agentic workflows with Gemini API.

Highlights: Philipp shared a guide on building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Useful for developers wanting to implement agentic workflows with Gemini and LangGraph.

Highlights: Philipp Schmid publishes a guide on building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Hands-on tutorial for implementing agent reasoning and action patterns with Gemini.

Highlights: Philipp shared a guide on building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Provides a practical tutorial for implementing agent architectures with Google's Gemini API.

Highlights: Philipp Schmid published a guide on building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Essential reading for developers wanting to implement ReAct agents with Gemini and LangGraph.

Highlights: Philipp shares a guide on building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Provides a practical tutorial for implementing ReAct agents with the latest Gemini model.

Highlights: Philipp Schmid provides a guide to building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Essential for developers looking to implement agentic workflows with Gemini.

Highlights: Philipp Schmid shares a guide on using Deep Research with the Gemini API.

Worth reading: Provides practical steps for leveraging Gemini's Deep Research capabilities via API.

Highlights: Philipp posted about using Deep Research capabilities with the Gemini API, linking to his blog.

Worth reading: Shows how to leverage Gemini's deep research features programmatically.

Highlights: Philipp explains how to use the Deep Research feature with the Gemini API.

Worth reading: Offers insights into leveraging Gemini's Deep Research capabilities via API.

Highlights: Philipp Schmid shares a guide on using Deep Research with the Gemini API.

Worth reading: Provides practical insights on leveraging Gemini API for deep research tasks.

Highlights: Gemini Embedding 2 is now generally available, supporting text, image, video, audio, and PDF embeddings in a single model.

Worth reading: This unified embedding model simplifies multi-modal retrieval and reduces pipeline complexity.

Highlights: Philipp Schmid announces departure from Hugging Face after 4 years, reflecting on the platform's growth from 20 people and 5,000 models to millions of developers and thousands of daily model releases.

Worth reading: Shows a key milestone in the career of a prominent AI/ML figure and the explosive growth of Hugging Face.

Highlights: Philipp Schmid announces the Gemini Interactions API, a unified RESTful interface for Gemini models and agents, starting with the Deep Research Agent.

Worth reading: This post highlights Google's push towards simplifying agent and model access through a single API endpoint.

Highlights: Philipp Schmid shares a guide on building a ReAct agent from scratch using Gemini 2.5 and LangGraph.

Worth reading: Provides a hands-on tutorial for implementing agents with Google's latest Gemini model.