Most AI projects stall somewhere between "it works on my laptop" and production. The skills that close that gap — versioning models, operating LLM applications at scale, running agents that don't fail silently — are what the new AI Ops Engineer Nanodegree program helps you build. Three months. Three projects. A full production stack from MLOps through LLM Ops to agent operations. Explore the program today → bit.ly/4d8DxMK

Security engineers know how to assess a web app. Most don't know how to assess an AI system. ML engineers understand the model. Most can't tell you where the attack surface is. That gap is where production AI gets compromised. We built a Nanodegree program for the engineer who wants to close it. The new AI Security Engineer Nanodegree program covers threat modeling, red teaming, and AI governance across four real projects on AWS. Become an AI security engineer and secure AI, end to end. Learn more → bit.ly/3SP07TI

No computer science degree required. Sabrina Palis spent a decade as a teacher before enrolling in the Master of Science in AI degree program. Her capstone project: a decision support system that uses AI to detect anomalies in aerospace telemetry. Watch the full graduate panel: bit.ly/4qE0Pj0

What's your best defense against an agent inventing data? It isn't the schema: schema validation checks shape, and a hallucinated value has perfect shape. The agent needed a date, invented one, and the pipeline accepted it, which is how fabricated data spreads through systems that look well defended. The defense is layered: a schema that makes missing data representable, so the model has a legal way to say it doesn't know, plus validation that catches the internal inconsistencies a model smooths over. That extraction work is part of the evaluation coursework in the new AI Engineering with Claude Nanodegree program. Learn more about the program: bit.ly/4xttUA2 #AIEngineering #Claude #AgenticAI #StructuredOutputs

🤖 One of the cumulative projects in the new AI Engineering with Claude Nanodegree program is a claims intake agent. You start with the raw agentic loop and build up to an agent that reads an ambiguous claim and decides its own next step: clarify with the user, route it forward, or escalate to a person. By the last exercise the decision logic is yours, written and tested by hand. Explore the program: bit.ly/3RvJKuE #Claude #AIAgents #AgenticAI #AIEngineering

The best people to tell you about our master's in AI program? The ones who've been through it. Join us live this Wednesday for a Q&A with three program graduates: ✅ Nhan Le – Data Quality Analyst, Meta ✅ Sabrina Palis – AI and Data Science Specialist ✅ Christopher O'Hara – Applied AI Engineer & Researcher They'll share what the experience was really like: the challenges, the highlights, and what they'd tell someone considering the program today. Register for free here, and come with your questions ➡️ bit.ly/4qgoYvD

Multi-agent systems are having a moment, and plenty of them shouldn't exist. Every agent you add brings coordination, handoffs, and failure modes the single-agent version never had, and a lot of problems come out better with one well-engineered agent than five loosely coordinated ones. The judgment call is knowing when the added complexity pays for itself; when it does, the hard parts are the unglamorous ones: scoped roles, structured handoffs, agents you can hold accountable. You design that tradeoff, and build it with the Claude Agent SDK, in the new AI Engineering with Claude Nanodegree program. Learn More: bit.ly/4wKQ1lt #AgenticAI #Claude #MultiAgent #AIEngineering

Our take: for anything high-stakes, don't rely on a prompt at all. A prompt can ask an agent to follow the rules, but it can't guarantee it will. That is fine for low-stakes work and risky the moment an agent is moving money or touching customer data. The fix is enforcement in code: deterministic control logic that holds the line no matter what the model decides, with a human in the loop where the stakes demand it. That is how bounded autonomy gets built in the new AI Engineering with Claude Nanodegree program. Learn more: bit.ly/4xihmeq #AgenticAI #Claude #AIGovernance #AIEngineering

Watch an agent bill grow for a quarter and a pattern shows up: routing, extraction, and classification all running on the largest model available, because that was the safe pick on day one and nobody revisited it. Most of that work runs fine on a smaller, faster model at a fraction of the cost, and choosing it deliberately is an engineering call. It is one of the first calls you practice making in the new AI Engineering with Claude Nanodegree program. Explore the program: bit.ly/4pTbBRY #Claude #AIEngineering #AgenticAI #LLM

"The program's greatest value lies in its portfolio-first approach, building production-ready AI systems rather than focusing solely on theoretical exams." - Thounda Craig Jr, master’s in AI student Back to school looks a little different with our Master's in AI 🎓 This fall, skip the backpack and grab the skills that actually move your career forward: 50+ hands-on projects, a capstone, and a credential built for the future of work. The master's in AI degree is designed for people who want to build with AI, not just learn it. The back-to-school sale is ending soon. If you've been thinking about it, now's the time 👉 bit.ly/4yTYRi2 #BackToSchool #AI #MachineLearning #MastersDegree #Udacity #CareerGrowth #LearningAndDevelopment

Most agent demos die the same death: they work in the meeting and fall over in production, because the demo was the model and production is the harness. That harness is real engineering: controlling the loop, governing which tools the agent can reach, surfacing failures before customers hit them, and enforcing guardrails in code where a prompt would only ask nicely. It is also most of what you build in the new AI Engineering with Claude Nanodegree program. Learn More: bit.ly/4xhwmtd #AIEngineering #AgenticAI #Claude #ProductionAI

A crashed agent gets fixed the same afternoon. An agent that returns a confident wrong answer runs for weeks, because nothing in the stack knows it is wrong until a customer does. Catching that takes evaluation built for agents: scoring task completion, quality, tool use, and reliability at the response, step, and trajectory level. Measuring what agents actually do gets a full course in the new AI Engineering with Claude Nanodegree program. Explore the program: bit.ly/4w1Z5kt #AIEngineering #AgenticAI #Claude #AIObservability

📊 You wire an agent to custom scraper and database servers over MCP, point it at competitor pricing, and make it gather, reconcile, and reason over what comes back, including the malformed responses and misbehaving tools production data guarantees. The project is called PriceScout, and it's one of the hands-on builds in the new AI Engineering with Claude Nanodegree program. Explore this and other projects today: bit.ly/3TrsffC #Claude #MCP #AIAgents #AIEngineering

The first MCP server most teams ship takes an afternoon. The security review that follows takes a month, because the server can reach every table in the database, the API key is sitting in a config file, and nobody can say what the agent did with any of it. Scoped access, a secret-leak gate in CI, an audited loop: that layer is the actual engineering, and in the AI Engineering with Claude Nanodegree program you build it alongside the server, because in production they are the same job. Learn more: bit.ly/4vKaV2P #AIEngineering #MCP #Claude #AgenticAI

She's a healthcare data analyst, a mom to young kids, and she just got a raise 💪 Lydia didn't have time to waste, so she needed learning that worked around her life, not the other way around. After completing the Data Analysis and Visualization with Microsoft Power BI Nanodegree program, she became the go-to person on her team for building dashboards that actually tell a story. "I believe that's just the beginning." So do we, Lydia 💙 #studentstory #dataanalyst #powerbi #womenintech #raise

Where does control really live in agentic AI systems? The harness. Sufian Kaki Aslam is a Senior Cloud Architect who builds production AI systems for enterprise clients and teaches in our AI Engineering with Claude Nanodegree program. His recent blog breaks down why engineers are increasingly building their own harnesses. To preview some key insights: ✔️ Every Claude product you use — Claude for Chrome, Claude Code, Claude Cowork — is a harness Anthropic built. They're general-purpose, which means they're not optimized for your specific use case. ✔️ When you build your own with the Claude Agent SDK, you define the rules: which tools the agent can access, how it manages context, when it needs human approval before acting. ✔️ A useful way to think about API vs. SDK: contractor vs. employee. The API handles one-time tasks. The SDK is for agents with ongoing responsibilities that need to behave reliably at scale. ✔️ The learning curve isn't syntax, it's judgment: knowing when to constrain an agent, how to write guardrails that actually hold, and how to structure a loop that fails gracefully. Full breakdown here: udacity.com/blog/what-is-the…

Sofia Lemons, Senior Technical Content Developer, recently passed Anthropic's official Claude Certified Architect — Foundations exam. Here's what she learned: -"Foundations" doesn't mean beginner. This is an architect-level exam. -Multiple choice is harder than it sounds. The question is always which design is most reliable — not which one option works. -Building something real beats studying. Sofia built a tool with Claude Code during prep. It was better practice than any practice question. -The resume signal is still unproven. The skills you develop getting there are not. Read about her full experience — what the exam covers, how she prepared, and what she'd do differently — in our recent blog ➡️ bit.ly/4wIMnrU

The job market isn't waiting. Neither should you. Right now: 50% off AI and tech courses, including the new AI Engineering with Claude Nanodegree program, MS in AI, and MBA programs. Get the skills that move careers forward, at half the price ⚽ bit.ly/4fpM26v

The question for today’s engineers isn’t whether you can build an AI agent. It's whether you can build an AI agent you can put in front of a customer. That means evals, guardrails, retries, and handling the non-determinism that breaks things the moment real traffic hits. That’s the difference between a Claude prototype and a production system. The new AI Engineering with Claude Nanodegree program is built around this capability. Across four courses and 13 hands-on projects, you engineer the harness that runs an agent in production, building on the Claude Agent SDK, MCP, and Claude Code. Every project is reviewed by an experienced mentor, and you build in real industry scenarios: insurance, retail, financial services, and manufacturing. Enrollment is now open, time to start building 👉 bit.ly/3SuRltz

You're using AI every day. So why does it still feel like you're not getting the most out of it? It's not because you need to learn a new tool. Not because you haven't tried the right prompts. It's because your thinking hasn't adapted for AI. That's what our new course Agentic Thinking 101 is all about. It’s a free course from Udacity built for working professionals who use ChatGPT, Claude, Copilot, or Gemini and want to get the most out of it. No coding. No technical background required. Just a sharper way of approaching AI that most courses skip entirely. Principal Instructor Simon Allardice teaches you the mindset shift that separates people who plateau from people who excel with AI. You'll learn why giving AI a goal beats giving it a to-do list, how to define "done", and why the people who get the most from these tools are the ones who stay in the lead, not just in the loop. Available free for a limited time. Enroll now ➡️ bit.ly/3R5ooDZ