Business AI

A step-by-step guide on how to use the new ChatGPT Agent, a newly launched AI agent by OpenAI that combines ChatGPT, deep research, and Operator.

Seven trends are discussed today from AI lesson planning, how to use AI to promote creativity and Auburn University's SOC center.

Microsoft wants Copilot to browse the web for you

: Tried by two-thirds of firms, ignored by most devs, and productivity barely moved

: AI tech shows promise writing emails or summarizing meetings. Don't bother with anything more complex

: Unavoidable AI has developers looking for alternative code hosting options

Before the system was used, dispatchers would often have to place someone who called the non-emergency line on hold to take a call for someone who called 911 with an actual emergency.

For AI agents, a knowledge base fuels fast and accurate responses and enables complex reasoning. We asked the experts how to build one.

Microsoft's platform for managing, securing, and governing AI agents, with capabilities like agent registry, performance analytics, and more.

A general agent for slides, websites, podcasts, videos—everything.

A multi-agent system to understand your codebase for senior-level code reviews.

Commentary on Agentic AI and Security by Stephen Downes. Online learning, e-learning, new media, connectivism, MOOCs, personal learning environments, new literacy, and more

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.