Business AI

For Superhumans and their AI teammates to thrive, enterprises must build robust data foundations and memory systems. This means capturing and protecting an organization’s collective intelligence — not just data, but the decisions, judgment, intuition, and know-how that usually live in people’s heads. It’s a bit like creating a Pensieve for the enterprise – a living memory any AI agent can draw from. We call these context cartridges and knowledge capsules.

Agentic system with faster task completion, coding

Build AI agents that stay secure under attack, verified by Lakera’s independent red-team study.

Evaluate, Optimize, and Ship AI Agents

The race between human-centered work and infinite PowerPoints

A new generation of apps you can chat with and the tools for developers to build them.

The Rundown: In this guide you'll learn how to build a content brainstorming app using Google's Opal which can help you turn blank page syndrome into

Build, edit, and share AI mini-apps with natural language

Episode 76: What actually makes something a real "AI Agent"—and how close are we to AI handling complex work entirely on its own?*Want our guide to master AI...

Stop shipping agents like they’re apps. They’re self-governing code touching live systems. IBM × Anthropic is the signal: enterprise agents are here, and governance just became table stakes. Here’s the playbook I’m seeing (10 pieces you can ship, certify, and scale): ✅ what are ai agents? adaptive systems that reason, act, and learn with tools, not static chat apps. ✅ agentic enterprise embed agents into ops so decisions, workflows, and automations improve every run. ✅ ADLC (agent development lifecycle) devsecops for agents: design → sandbox → red-team → certify → deploy → monitor → retire. ✅ enterprise considerations tie use cases to ROI, controls, and regs; write the business case before the prompt. ✅ observability & ops beyond uptime: track behavior drift, tool errors, chain depth, reasoning quality, and rollback readiness. ✅ agent security defend against prompt injection, data leakage, privilege escalation; least-privilege tools with signed calls. ✅ governance: test, certify, catalog treat agents like services: pre-release evals, attestations, lineage, and an internal marketplace. ✅ MCP servers lifecycle model context protocol as a first-class surface: auditable, scoped, and versioned integrations. ✅ reference architecture hybrid stack that separates knowledge (RAG), capability (tools), policy (guards), and memory (state). ✅ voice of the customer & use cases ship real deployments (healthcare, telecom, finance) with before/after metrics, not vibes. If you’d word any of this differently, I’m all ears, drop your version and I’ll pin the clearest take. IBM/Anthropic folks, feel free to sharpen this for the operators in the trenches. Bottom line: this isn’t “labs” anymore. If you can’t test it, certify it, and roll it back in minutes, you shouldn’t run it in production. Follow Alex for operator-grade AI agents you can copy, and repost to put this in front of one teammate who owns your next deployment. Thanks Andreas Horn for sending this over. | 51 comments on LinkedIn

In this course taught by Andrew Ng, you'll build agentic AI systems that take action through iterative, multi-step workflows.

89% of devs use AI, but only 24% design APIs for agents. As AI agents become the new API consumers, your strategy must evolve.

: Analyst predicts over-supply will trigger a market correction in favor of deep-pocketed incumbents

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Today we are releasing the Gemini 2.5 Computer Use model via the API, which outperforms leading alternatives at browser and mobile tasks.

In these early days of agentic AI adoption, failing fast can cause disproportionate damage considering what’s still to be learned and the increasing budgets in play. Maturity can’t be rushed, but perspective can come into greater focus.

“AI agent” is a term we hear more and more in the product design community. People use this term all the time when they are talking about…

A day of AI-focused micro-workshops designed to turn you from a passive user to an active solutions architect.

Experts debate if implementing agentic AI demands new management approaches.

Relay.app is a platform to create AI agents that work for you across 100+ apps.

OpenAI quietly released a comprehensive, practical guide on how to build AI agents with a clear blueprint for the future of business automation.

When Perplexity AI unveiled its Comet browser, it was pitched as the next evolution of web navigation: an agentic browsing tool that could read, summarize, and act on information across the internet on a user’s behalf. But just weeks after launch, Brave researchers revealed a critical flaw that turned Comet into a liability. The vulnerability

Clipping Agents turn your long-form videos into ready-to-post clips, styled and branded in your voice. Just set your preferences once and let automation handle the rest.

Revolutionize your restaurant's customer service with Loman.ai: the AI-powered phone agent. Available 24/7, Loman takes orders, books reservations, and answers inquiries with unmatched efficiency and at a fraction of the cost. Elevate your customer experience today.