Claude now offers code execution, MCP server connections, file storage, and extended prompt caching through the API—giving developers powerful tools to build agents that analyze data, connect to external systems, and maintain context for longer periods of time.
perplexityai/SPACE
Sandboxed Platform for Agentic Code Execution: pluggable-runtime sandboxes for running agent and user code in isolation.
perplexityai/SPACE
Sandboxed Platform for Agentic Code Execution: pluggable-runtime sandboxes for running agent and user code in isolation.
New data agents across the Agentic Data Cloud | Google Cloud Blog
Learn about new data agents and tools for business analysts, data scientists, and database admins to integrate with the Agentic Data Cloud.
Dive into Claude Code: The Design Space of Today's and Future AI Agent Systems
Claude Code is an agentic coding tool that can run shell commands, edit files, and call external services on behalf of the user. This study describes its comprehensive architecture by analyzing the publicly available TypeScript source code and further comparing it with OpenClaw, an independent open-source AI agent system that answers many of the same design questions from a different deployment context. Our analysis identifies five human values, philosophies, and needs that motivate the architecture (human decision authority, safety and security, reliable execution, capability amplification, and contextual adaptability) and traces them through thirteen design principles to specific implementation choices. The core of the system is a simple while-loop that calls the model, runs tools, and repeats. Most of the code, however, lives in the systems around this loop: a permission system with seven modes and an ML-based classifier, a five-layer compaction pipeline for context management, four extensibility mechanisms (MCP, plugins, skills, and hooks), a subagent delegation mechanism with worktree isolation, and append-oriented session storage. A comparison with OpenClaw, a multi-channel personal assistant gateway, shows that the same recurring design questions produce different architectural answers when the deployment context changes: from per-action safety classification to perimeter-level access control, from a single CLI loop to an embedded runtime within a gateway control plane, and from context-window extensions to gateway-wide capability registration. We finally identify six open design directions for future agent systems, grounded in recent empirical, architectural, and policy literature.
My Agentic Coding Setup, July 2026
With the right tools, coding agents can run autonomously, in parallel, and be reachable from anywhere. Here's how I've stitched them together.
openai/openai-realtime-agents
This is a simple demonstration of more advanced, agentic patterns built on top of the Realtime API.
agentOS — A faster, lighter, cheaper alternative to sandboxes
A portable open-source operating system for agents. Stateful runtime, universal agent interface, and secure code execution. One SDK, deploy anywhere.
Google for Developers Blog - News about Web, Mobile, AI and Cloud
An open specification for finding and verifying tools, skills, and agents across the web.Agents are ...
Google for Developers Blog - News about Web, Mobile, AI and Cloud
An open specification for finding and verifying tools, skills, and agents across the web.Agents are ...
Pietro on Twitter / X
Recently, Anthropic https://t.co/v9hnbaLCmG and Cloudflare https://t.co/JBb6SexF8N released two blog posts that discuss a more efficient way for agents to interact with MCP servers, called Code Mode.There are three key issues when agents interact with MCP servers traditionally:… pic.twitter.com/hfUocpe6kV— Pietro (@pietrozullo) November 20, 2025
New tools for building agents
Agent experience: How to design products that agents can actually use — WorkOS
What engineers and founders need to know about designing APIs, tools, and interfaces for agent-driven workflows
Building a PDS the Hard Way agent.io/posts/building-a-pds
Building a PDS the Hard Way
agent.io