A year ago AIO was a niche concept. Now it is a pillar of any marketing engine. Here is the weekly job Arcade.dev runs to watch how LLMs describe and cite us, why it is not an agent, and what six months of data taught us about content.
OpenAI shipped support for Skills Over MCP while its spec, SEP-2640, is still an unmerged draft. What the extension is, how it works on the wire, what it unlocks, and where the largest implementation already diverges from the draft.
Enterprises have governed people for decades. Letting agents inherit that work unchanged doesn't work — here's why.
The MCP 2026-07-28 release drops the initialize handshake and the session ID for remote servers. Arcade.dev's Nate Barbettini and Mateo Torres sit down with core maintainers Caitie McCaffrey (Microsoft) and Sam Morrow (GitHub) on why they took a breaking change this size — and what it costs to adopt.
On July 28, the newest MCP spec lands with breaking changes you'll have to respond to. Join Arcade.dev's webinar with Mateo Torres: what's changing, why, and how to prepare.
The Arcade.dev team is always building, and now you can share the fun at Arcade Labs: our public home for research, prototypes, and experiments, launching today with Omni.
Most agents either forget everything between sessions or remember the wrong things in someone else's database. There's a third option: a memory layer you actually own.
Vercel and Context.ai disclosed a chained breach widely reported as an 'AI incident.' It wasn't. Context.ai had stored a Vercel employee's broadly-scoped Google Workspace OAuth token on its servers. When Context.ai's AWS got breached, the attacker replayed the token, logged in as the employee, pivoted into Vercel, and walked out with customer environment variables — later listed for $2M on BreachForums. No model was jailbroken. The vulnerability is a 2010s-era OAuth token hoarding pattern, and AI just made the vaults more valuable.
OpenClaw (a.k.a. Moltbot, a.k.a. ClawdBot) went viral and became one of the most popular agentic harnesses in a matter of days. Peter Steinberger had a successful exit from PSPDFKit, and felt empty until the undeniable potential of AI sparked renewed motivation to build. And he's doing it it non-stop. OpenClaw approaches the idea of an Personal AI agent as a harness that communicates with you (or multiple users) in any of the supported channels in multiple sessions connected to the underlying
Your agent needs to pull data from Google Drive, post a summary to Slack, and create a Jira ticket. Simple request. But whose credentials does it use? Should it have permission to delete your entire Drive folder? This authorization problem kills agent demos before they reach production. It's not about users logging into your agent (LangGraph Platform handles that). It's about your agent accessing other services on behalf of those users. If you're building real agents, you've hit this wall. The
Most AI agents are glorified chatbots. Chex just won a hackathon by building three specialized agents that actually book therapy appointments. Not suggest. Not recommend. Actually book — complete with calendar invites and email confirmations. Here's the pattern they discovered that you can steal for your own agent systems. Want to skip to the code? Check out our Quickstart or get your Arcade.dev API key to build authenticated agents in minutes. The Problem: Single Agents Hit Walls Traditio
In the previous post in this series, we explored Human-in-the-Loop. Here, we’re exploring Handoffs, which I prefer to call “Agentic Delegation” This post is a companion to a video, I encourage you to watch it! Here’s the experiment setup I’m using the same agentic system. I implemented the same system using three different Frameworks: * LangGraph * OpenAI’s Agents SDK * Google’s Agent Development Kit (ADK) In all cases, the agent uses a “supervisor” architecture, where a single agent re
As I build agents every day, I get to see Agentic Frameworks evolve different approaches to solve the same core issues of agentic orchestration. Fundamentally, the differences come down to how the framework designers think about the common building blocks of an agentic system. Unfortunately, they all come with disparate terminology and adopt jargon that makes this seem more complicated than it really is. I feel this is creating a bit of a decision block, especially in beginners. This series of b
As the world becomes more and more agentic, it’s important to meet your users where they are, and this usually means providing them with polished UX in whatever communication platforms they use on a daily basis: * WhatsApp * Email * Telegram * Discord * Slack Adding a chatbot experience to chat-like interfaces is usually pretty easy. I just pick one of the existing LLM clients, add my API Key, a nice system prompt, and let users chat away. However, things quickly become complex if the age
LangChain's Social Media Agent is a fantastic tool. It allows you to take a list of links – maybe articles you've read, interesting projects, or company blog posts – and automatically generate engaging social media updates. Imagine processing 50 links and scheduling them out over the next few weeks. You could go on vacation knowing your social media feed remains active and consistent with content you've already approved. That's powerful automation! The Challenge: The Terminal Barrier While po
Multi-agent AI systems represent one of the most significant advances in practical AI applications today. Unlike traditional single-agent approaches, multi-agent systems distribute complex tasks across specialized agents, each handling what they do best. In this article, we'll explore a practical example that uses specialized agents with access to Gmail and Slack tools. This involves the integration of two frameworks. The OpenAI Agents SDK will run and orchestrate the agents, and Arcade will
How to use AI to query a customer database without writing SQL You've finally made it to Data Analyst at your dream company (yay!). You're excited to finally put all those hardcore SQL skills you've acquired over the years, maybe even use some of the new and shiny dataframe frameworks. You get to your desk with a freshly brewed cup of coffee, ready to dive deep into the latest of the latest. But the top urgent requests are the usual, "Hey! Could you give me a list of our customers in New York w
