In this guide, you will learn how to set up AI teammates that are actually useful in ChatGPT’s new Workspace Agents tool. The goal is one daily agent that handles a recurring morning task for you, instead of one more prompt you have to remember to run yourself.

You will build a daily agent that owns one recurring workflow and runs it for you each morning.

In our demo, that agent reviewed a Notion database of published guides, looked for useful patterns, and generated three new guide ideas every day. — Read More

Three-quarters of new code created inside Google is now generated by AI and reviewed by human engineers, the company said Wednesday.

That number has been notching up in recent years. As of October 2024, around a quarter of the company’s code was AI-generated, Google said at the time. Last fall, it said the number had risen to 50%.

The company has been pushing employees to use AI both for coding and other tasks. Google CEO Sundar Pichai said in a blog post on Wednesday that the company was shifting to “truly agentic workflows” with its engineers running more autonomous tasks — Read More

For thirty years, the central obsession of product design has been a single question: how do we make it easier for a human to click the right button? We built funnels. We A/B tested button colors. We agonized over empty states and loading spinners.

That era is ending — not gradually, but structurally.

… Agents don’t navigate UIs. They negotiate with systems. And when the agent is the primary “user” of software, the human behind it occupies an entirely different role — one for which we have almost no design vocabulary. Until now.

HX — Harness Experience — is the design discipline governing the interface between a human and their agentic fleet. — Read More

We pulled dozens of AGENTS.md files from across our monorepo and measured their effect on code generation. The best ones gave our coding agent a quality jump equivalent to upgrading from Haiku to Opus. The worst ones made the output worse than having no AGENTS.md at all.

That gap was surprising enough that we built a systematic study around it.

What we found: most of what people put in AGENTS.md either doesn’t help or actively hurts, and the patterns that work are specific and learnable. — Read More

MCP servers are becoming the core focus of production agentic systems because they are where all the hard problems actually live: multi-tenant isolation, auth, rate limits, audit trails, and approval gates for destructive operations. Without them, agents leak data across tenants, burn budgets in runaway loops, and commit to refunds no human approved. An MCP server solves this by sitting between the agents and the data layer as a single secure tool surface, turning every agent call into an authenticated, policy-checked, rate-limited, audited operation before it touches a single row …

In this blog, we are going to build Atlas-MCP, a production-grade MCP server organized around twelve components that keep showing up on the 3 AM pager when teams skip them. On top of the server, we are also going to build a four-agent support copilot (Planner, Retriever, Synthesizer, Critic) that uses the server’s tools to answer real customer support tickets end to end. — Read More

In the last 30 days, 93% of Cloudflare’s R&D organization used AI coding tools powered by infrastructure we built on our own platform.

Eleven months ago, we undertook a major project: to truly integrate AI into our engineering stack. We needed to build the internal MCP servers, access layer, and AI tooling necessary for agents to be useful at Cloudflare. We pulled together engineers from across the company to form a tiger team called iMARS (Internal MCP Agent/Server Rollout Squad). The sustained work landed with the Dev Productivity team, who also own much of our internal tooling including CI/CD, build systems, and automation..

… MCP servers were the starting point, but the team quickly realized we needed to go further: rethink how standards are codified, how code gets reviewed, how engineers onboard, and how changes propagate across thousands of repos..

This post dives deep into what that looked like over the past eleven months and where we ended up.  — Read More

Agentic AI has emerged as the software industry’s latest shiny thing. Beyond smarter chatbots, AI agents operate with increasing autonomy, making them poised to drive efficiency gains across enterprises.

“Agentic refers to AI systems that can take actions on behalf of users, not just generate text or answer questions,” says Andrew McNamara, director of applied machine learning at Shopify. Agentic systems run continuously until a task is complete, he adds, citing Shopify’s Sidekick, a proactive agent for merchants.

Development of agentic AI now spans many business domains. According to Anthropic, a provider of large language models (LLMs), AI agents are most commonly deployed in software engineering, accounting for roughly half of use cases, followed by back-office automation, marketing, sales, finance, and data analysis. — Read More

Wardgate is a security gateway that sits between AI agents and the outside world — isolating credentials for API calls, isolating SSH keys for remote command execution, and gating command execution in remote environments (conclaves).

Give your AI agents access to APIs, SSH keys, and shell tools – without giving them your credentials or trusting them with direct execution. — Read More

Salesforce is packaging its developer and AI tooling, including its vibe coding environment Agentforce Vibes, into a new platform named Headless 360, designed to help enterprise teams build agent-first workflows.

The CRM software provider defines agent-first workflows as enterprise processes in which software agents, rather than human users, carry out tasks by directly invoking APIs, tools, and predefined business logic.

To support this approach, Headless 360 exposes Salesforce’s underlying data, workflows, and governance controls as APIs, MCP tools, and CLI commands, via its existing offerings, such as Data 360, Customer 360, and Agentforce, Joe Inzerillo, president of AI technology at Salesforce, said during a press briefing. — Read More

I’m not here to tell you AI is coming for your job. You’ve heard that a hundred times already, and frankly, nobody wants to here the same thing again.

You’ve also probably read the top skills to learn in 2026. Learn Python. Learn AI. Learn prompt engineering. Sure all those are valid. But here’s the thing: everyone is saying that. And when everyone is saying the same thing, the real opportunity is usually one step ahead.

So what’s that step?

Agentic AI. And hang on, it’s not some buzzword to add to your LinkedIn bio. It’s a fundamental shift in what AI does, how it thinks, how it works, and what it’s capable of. Right now, very few people understand it deeply enough to actually build with it.

That gap is exactly where opportunity lives. — Read More