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Google has released a new CLI for Google Workspace, offering a unified interface for various services like Drive, Gmail, and Calendar. Built in Rust, the tool dynamically adjusts to API changes and features over 100 bundled skills. It requires Node.js and a Google Cloud project for setup. Initial co
AI Agent Guidelines for CS336 at Stanford Meta Description: Discover the official AI Agent Guidelines for CS336 at Stanford — what they cover, why they matter, and how students can navigate them effectively in 2026. Stanford's CS336 (Language Models from Scratch) has specific guidelines governing th
If Nvidia has cracked a way to bring AI agents easily, safely and usefully to the masses, it could — and should — be big.
After using Claude Code, Codex, and Pi Agent for months, I built a scanner. Here's what it found: Framework Active Archived Claude Code 192 191 Codex CLI 37 0 Pi Agent 8 sub-agents 12 scripts MCP Servers 8 - Total 448+ Duplicate calls: Same prompt → 3 agents (8-18% waste) Overqualified models: Simpl
Just about every enterprise software vendor now agrees on one thing, at least: AI agents are only as useful as The post “Blowing things up”: The one move vendors got wrong on AI agents appeared first on The New Stack.
I'm building CortexDB — an agent-native context database for AI agents Most modern RAG systems follow the same pattern: Split documents into chunks Compute embeddings Store them in a vector database Retrieve top-k similar chunks Send them to an LLM It works. But as AI agents become more autonomous,
BadHost is a high-severity authentication bypass vulnerability in the widely used Python web framework Starlette, with 325 million weekly downloads. The flaw allows attackers to use malformed HTTP Host headers to bypass path-based access controls and access sensitive AI agent infrastructure, among o
Merge API Inc., a platform provider delivering connective infrastructure for artificial intelligence to business data and tools, launched Agent Handler for Employees, easing the strain on information technology teams. With today’s release, Merge is offering a product that connects to identity provid
The Problem Nobody's Watching Background AI agents are everywhere now. You've got agents that monitor inboxes, poll APIs, summarize Slack threads, run scheduled analysis jobs — and they do all of this quietly, without a human in the loop for hours or days at a time. That "runs quietly in the backgro
A genuine note to the community — not a product review. There's a particular kind of developer frustration that doesn't have a name yet. It's not a bug. It's not a deployment failure. It's not a model hallucination or a broken API contract. It's the feeling you get when you've built something techni
Agent Skill is already one of the most widely accepted practices in AI Agent engineering: encapsulating repeatable tasks into capability packages that are discoverable, callable, and injectable into context. This is certainly valuable. Diagnosing bugs can be a skill. Reviewing code can be a skill. G
At some point when writing AI agent code, testing comes to a halt. Without an ANTHROPIC_API_KEY, the code won't even run. With one, every test run costs money. And how do you test streaming responses at all? That moment of uncertainty is exactly when most developers abandon test coverage for their a
Real data from 240 pull requests, 72 merges, 90 rejections, and $500+ earned. No theory, no hype — just numbers. TL;DR: I built an autonomous AI agent that submits pull requests to open-source repositories 24/7. After one week and 240 PRs across 30+ repos, here's what I learned: 82% of all merges ca
After 30 days of running an autonomous AI agent that hunts GitHub bounties 24/7, I've submitted 80+ pull requests, earned $500+ in bounties, and learned lessons that completely changed how I think about AI and money. Here's everything — the good, the bad, and the brutally honest. It began with a sim
AI agents will need to pay for compute, data, and API calls. The current paradigm of human-managed payment systems breaks down when thousands of autonomous agents need to transact independently. They need wallets — not custodied accounts managed by humans, but autonomous financial infrastructure the
Over the last two years, an entire industry has emerged around AI development within the PHP ecosystem. Where integrating an LLM once looked like a few lines of code calling the OpenAI API, developers today are building full-fledged agent systems: with memory, tools, workflows, observability, and ev
This is a submission for the Hermes Agent Challenge: Write About Hermes Agent The next leap in AI agents is not just better answers. It is reusable experience. When people talk about AI agents, the conversation often starts with automation. Can the agent use tools? Can it open files? Can it run comm
Every testing tool for AI agents tests individual agents. But production failures don't happen inside agents — they happen between them. I learned this the hard way. I built a 14-agent document processing system using CrewAI. Each agent worked perfectly in isolation. In production, the system failed
The current wave of AI development is undergoing a massive paradigm shift. We are rapidly moving past simple "prompt wrapper" applications and entering the era of fully autonomous, agentic systems. Yet, if you’ve tried to build an AI agent for a production environment, you’ve likely run into a frust
This is a submission for the Hermes Agent Challenge Let me tell you what broke my brain. I was reading through the Hermes Agent docs, fully expecting the usual wall of prerequisites. You know the drill — Python version must be exactly this, install Docker first, make sure your Node is on the right v
