Without proper governance, an AI agent might autonomously access sensitive data, expose personal information, or modify sensitive records. In our new short course: “Governing AI Agents,” created with Databricks and taught by Amber Roberts, you’ll design AI agents that handle data safely, securely, and transparently across their entire lifecycle.... You’ll learn to integrate governance into your agent’s workflow by controlling data access, ensuring privacy protection and implementing observability. Skills you'll gain: - Understand the four pillars of agent governance: Lifecycle management, risk management, security, and observability - Define appropriate data permissions for your agent - Create views or SQL queries that return only the data your agent should access - Anonymize and mask sensitive data like social security numbers and employee IDs - Log, evaluate, version, and deploy your agents on Databricks If you’re building or deploying AI agents, learning how to govern them is key to keeping systems safe and production-ready. Sign up here:show more

@databricks No human employee gets root access on day one. Why would an autonomous system? Start with views Start with masks. Start with logs. Build trust through constraints, not hope.

@databricks Dear Sir, you are a legend 🙏 At the cusp of every era, you take the time to be the best teacher, a whole generation can look up to. A student of your ML lectures, and a current student of your Deep Learning lectures. ❤️ 🫡

@databricks Everyone's racing to ship AI agents. Almost nobody's talking about governance until something breaks in production. This is the unsexy work that prevents the viral incident.

@databricks Solid move. Agent governance isn’t a side topic, it’s what separates real AI systems from risky prototypes.

@databricks Essential work. Governance and transparency are what make AI sustainable long term. Open models and onchain infrastructure take that even further by making every action traceable and verifiable.

@databricks Hey Mr. @AndrewYNg , can you please give me free access to your courses on Coursera, they are literally to expensive for me to afford, I'm from Nigeria and the price of the courses are way beyond my means of livelihood. I'm be eternally grateful

@databricks This is such a relevant course. These skills are not optional but must.

@databricks the governance gap is real - most people running agents locally are one bad skill install away from a problem. the tooling for this is still pretty immature

@databricks 😎😎😎

@databricks real build hours, no ghosting on data

@databricks The tension between true agent autonomy and necessary governance constraints is fascinating. What foundational guardrails are proving most effective?

@databricks AI governance isn't just a technical challenge - it's a human imperative. @AndrewYNg and @databricks show how we transform potential risks into responsible innovation. #AIEthics #ResponsibleTech

@databricks Great course on governing AI agents! Essential for data safety and transparency.

@databricks the lifecycle management piece is what most openclaw setups skip entirely. everyone focuses on building the agent, almost nobody thinks about governing it. signed up - this gap is real for anyone running persistent agents in production

@databricks 100%. Operationally: (1) tool scopes per role (least privilege), (2) approval gate for risky actions, (3) immutable audit receipts you can replay during incident response.

One governance pattern that prevents “agent went rogue” incidents: treat every tool like a production API. - explicit scopes per role (read vs write) - approval gate for high-risk actions (payments, deletions, sending emails) - immutable audit receipts (who/what/why + inputs/outputs) so you can replay an incident - continuous evals/red-team prompts after every model/tool change Without receipts + scopes, you can’t do incident response—only storytelling.

@databricks

@databricks Great initiative! Governing AI agents is crucial for data safety and transparency. Excited to learn more!

@databricks governance is the new competitive advantage

@databricks Critical insight on AI governance. As AI agents become more autonomous, what frameworks are you implementing to ensure responsible deployment while maintaining innovation velocity? #ResponsibleAI

@databricks real data with respect

@databricks the data access permissions piece is where most people skip corners. good to see it framed as a core pillar not an afterthought

@databricks This course sounds like a game-changer for AI safety!

@databricks This is such an important step for the AI ecosystem. 👏 Governance isn’t just a safeguard — it’s what makes agents trustworthy and production-ready. Excited to see Databricks and Amber Roberts leading this effort! #AI #TechAI

@databricks @grok explain this

@databricks Practical risk register control: for each agent capability, record owner, data boundary, approval step, and review date with evidence attached. If evidence is missing, freeze scope expansion until it is remediated.

@databricks This is a must if you are working with agents.

@databricks Awesome!!! I recommend this course . I think is very good!!!

@databricks The real innovation in AI isn’t what it can do but what it’s prevented from doing

@databricks AI agents with access? Someone's testing the limits.

@databricks This course is perfect for anyone serious about safe and secure AI.

@databricks real data with care, not cooked vibes