Data Science Dojo @DataScienceDojo

Should AI agents be managed like employees — or like software? Raja Iqbal weighs in on this in Computerworld's latest feature by Pat Brans, alongside leaders from IDC, DXC, and Quadient. His take: the "team member" metaphor is useful when it forces real discipline — identity, authority limits, audit trails. It's dangerous when it's just decoration — a name and a persona with no oversight behind it. His point: give the agent a traceable identity — but make sure a specific person owns what it does with that access. The agent can never be held accountable; only the person who deployed it can. Full piece here: hubs.la/Q04xJqms0 #AgenticAI #AIGovernance #EnterpriseAI

Running your LLM agent safely: Hands-on with Docker sandboxes x.com/i/broadcasts/1…

HAPPENING TODAY! AI agents are getting more autonomy to execute code, call APIs, and take real actions. That's also what makes them risky if something goes wrong. Our LLM agent security webinar looks at containment: how Docker Sandboxes let you run agents with real capabilities while limiting the blast radius when they misbehave. Dan Ndombe, Staff Developer Success Advocate at Docker, walks through the hands-on side of agent containment and the security policies that make it practical, not just theoretical. In this session, you'll learn: → Why sandboxing matters once agents can execute arbitrary code → How Docker Sandboxes isolate agent actions from your core systems → Practical policies for defining what an agent can and can't touch → How to apply this to real agent workflows, not just demos 📅 Wednesday, September 16, 2026 🕚 11:00 AM – 12:00 PM PT 🎙️ Dan Ndombe, Staff Developer Success Advocate, Docker 👉 Register here: hubs.ly/Q04xDT6T0 #AgenticAI #LLMAgents #Docker #AIAgentSecurity #datasciencedojo

Most AI coding agents run in "skip permissions" mode because typing "yes" a hundred times isn't a workflow. It's also how one bad step, or one prompt injection, ends up touching your real files, credentials, and network. The fix isn't more careful prompting. It's a boundary the agent can't cross by accident. That's what this session is about: running Claude Code, Codex, and similar agents inside an isolated Docker sandbox instead of directly on your machine. In this session, you'll learn: - How sandboxed file access works, so agents can read/write in their working directory but can't silently escape it - How network policies (open, closed, balanced) control which hosts an agent can reach - How secrets stay hidden from the agent, even if it's compromised or prompt-injected - How to package a working setup into reusable "kits" for consistent team-wide policies - Why this approach isn't limited to coding agents — it works for any custom agent framework 📅 Wednesday, September 16, 2026 | 11:00 AM–12:00 PM Pacific 🎙️ Dan Ndombe, Staff Developer Success Advocate at Docker 👉 Register here to save your spot: hubs.la/Q04xzRnp0 #AgenticAI #CodingAgents #Docker #AIAgentSecurity #datasciencedojo

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AI agents are only as powerful as the tools they can access. But for years, connecting an agent to an external tool meant writing custom integration code — from scratch, every single time. Change the tool, rewrite the adapter. Change the framework, start over. Scale to multiple agents and it becomes an engineering problem that never ends. MCP — Model Context Protocol — is the fix the industry has been waiting for. One open standard that lets any agent connect to any tool, through a single consistent interface, without bespoke wiring between every pair. If you are building with AI agents — or planning to — this is the post to save. 🔖 And if you want to go hands-on with MCP — not just understand it — we dedicate two full modules to it inside the Agentic AI Bootcamp. Cohort starts September 22nd. 🔗 Learn more: hubs.la/Q04xlGqn0 #datasciencedojo #agenticaibootcamp #agenticai

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If you've worked with LLMs, built a RAG pipeline, and feel like you're ready for what comes next — the Agentic AI Bootcamp is exactly that next step. This isn't a course about prompting. It's about building AI systems that reason, plan, and act on their own. In 10 weeks, you'll learn: 🔹 How transformers and attention mechanisms work under the hood 🔹 How to build production-grade pipelines with LangChain and LangGraph 🔹 How to design vector database architectures for long-term agent memory 🔹 How to engineer context so your agent always sees exactly what it needs 🔹 How to implement agentic design patterns — reflection, planning, tool use 🔹 How MCP, A2A, and ACP protocols enable agents to collaborate at scale 🔹 How to evaluate your agents before they meet real users 🔹 How to ship a full multi-agent application — and keep it You'll spend 30 hours in live sessions with data scientists, ML engineers, and AI practitioners who build this stuff every day. Every session pairs lecture with hands-on exercises. No passive watching. 📌 Learn more: hubs.la/Q04xlyDp0 #datasciencedojo #agenticaibootcamp #agenticai

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AI agents are getting more autonomy to execute code, call APIs, and take real actions. That's also what makes them risky if something goes wrong. Our LLM agent security webinar looks at containment: how Docker Sandboxes let you run agents with real capabilities while limiting the blast radius when they misbehave. Dan Ndombe, Staff Developer Success Advocate at Docker, walks through the hands-on side of agent containment and the security policies that make it practical, not just theoretical. In this session, you'll learn: → Why sandboxing matters once agents can execute arbitrary code → How Docker Sandboxes isolate agent actions from your core systems → Practical policies for defining what an agent can and can't touch → How to apply this to real agent workflows, not just demos 📅 Wednesday, September 16, 2026 🕚 11:00 AM – 12:00 PM PT 🎙️ Dan Ndombe, Staff Developer Success Advocate, Docker 👉 Register here: hubs.la/Q04xbH970 #AgenticAI #LLMAgents #Docker #AIAgentSecurity #datasciencedojo

LLM and Agentic AI Bootcamp Information Session x.com/i/broadcasts/1…

Once an LLM agent starts calling tools, writing files, and hitting APIs, where it runs becomes a security problem, not a prompting one.   Broad access lets an agent read, write, or call something it shouldn't. The fix is containment.   In this hands-on session, Dan Ndombe, Staff Developer Success Advocate at Docker, will walk through how Docker Sandboxes scope exactly what an agent can touch (filesystem, network, process) before it ever runs.   In this session, you'll learn: 🔹 How Docker Sandboxes isolate an agent's filesystem, network, and process access from the host 🔹 How to spin up a sandboxed agent runtime and hand it a real task end-to-end 🔹 How to read and tighten a sandbox policy: what to allow, what to block, and why 🔹 A reusable containment pattern for your own LLM and agent prototypes, no prior Docker experience required   This is built for engineers building or prototyping LLM agents, DevOps/platform teams deploying AI workloads, and anyone who wants practical guardrails instead of theoretical ones.   📅 September 16, 2026 | 11AM PT 🎙️ Dan Ndombe, Staff Developer Success Advocate, Docker   Register here: hubs.la/Q04x9J9s0   #AgenticAI #AIAgentSecurity #Docker #LLMs #datasciencedojo

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Agentic AI is moving fast enough that most teams are still figuring out how to build, deploy, secure, and govern it responsibly. The Agentic AI Conference returns this November to work through exactly that, in the open, with the people actually doing the work. Across 2 days, the event brings together AI practitioners, researchers, industry leaders, and technology experts through panels, technical sessions, tutorials, and fireside chats spanning architecture, evaluation, real-world deployment, and governance. What you'll get: - Real conversations with industry leaders and practitioners actively building agentic AI - Practical, technical sessions you can apply to your own work - Insight into where agentic AI is headed, from architecture to governance - Networking with a global community of AI and data professionals - Free access to all sessions, no cost to attend Previous editions have featured speakers from Google, AWS, Microsoft, Oracle, Docker, AMD, Hugging Face, LlamaIndex, SambaNova, LandingAI, Atlassian, and Neo4j, alongside founders and leaders from Ejento AI, CrewAI, Weaviate, Fiddler AI, and Arcade dev. 📅 Nov 9–10, 2026 | Virtual 🎟️ Free to attend 👉 Register here: hubs.la/Q04x2MdS0 #AgenticAI #AIAgents #DataScienceDojo #AIConference

Reasoning, context, and autonomy: those three pillars decide whether you get an agent or just a fancier prompt. We put together a full roadmap for our upcoming Agentic AI Bootcamp, and it goes deep. Ten modules that move from transformer fundamentals and self-attention math, through LangChain and LangGraph, into vector databases, context engineering, agentic design patterns, and the protocols (MCP, A2A, ACP) that let agents actually talk to tools and to each other. It closes with a capstone: building and shipping a production-ready multi-agent application. If you want to see the curriculum in detail and ask questions before you commit, join our live information session. In this session, you'll learn: 🔹 What the bootcamp covers, module by module 🔹 How the curriculum builds from LLM fundamentals to multi-agent systems 🔹 What the final capstone project looks like 🔹 How to get your specific questions answered live 📅 Thu, Sep 10, 2026 | 12:00 PM PT 🎙️ Raja Iqbal, Founder, Ejento AI 📍 Live Online Session Register here: hubs.la/Q04x2VKV0 If you've been thinking about building real skills in agentic AI, this is the place to start. #AgenticAI #LLMAgents #AIBootcamp #datasciencedojo #MachineLearning

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🎙️ How will visual AI change the way we work in the next 3–5 years? 💡 Dan Maloney, CEO of Landing AI, shares what excites him most: for decades, companies have been drowning in documents — too many humans, too many templates, too many fragile systems. With visual AI and agentic systems, that complexity is finally being resolved — at lower cost, higher trust, and faster speed. But the bigger picture is what happens when you start combining all these building blocks. Doctors and nurses spend more time on paperwork than with patients. Governments are buried in administrative processes. If visual AI can read, understand, and process what's inside those documents and images, humans get to focus on what they were actually built to do — think strategically, solve real problems, and tackle challenges that matter. Dan compares the data trapped in documents and images right now to the world before we figured out how to harness fossil fuels or solar power. The next few years won't be incremental — they'll be a leap. 🎧 Watch the full episode: hubs.la/Q04w_b1K0 🔗 View all podcasts: hubs.la/Q04w_b0h0 #VisualAI #DocumentAI #ComputerVision #AIFuture #Healthcare #LandingAI #FutureofDataAndAI

Your AI pilot isn't testing the AI. It's testing your organization. That's the argument Raja Iqbal makes in his latest piece — and it's one every executive planning an agentic AI rollout should sit with before they finalize the budget for the pilot. Agents don't improvise around broken processes the way people do. They execute exactly what's documented. So the gap between how your company says it runs and how it actually runs — the workarounds, the tribal knowledge, the "ask Marcus" accountability — stops being invisible. It becomes the first thing that breaks. The companies that win aren't the ones deploying agents fastest. They're the ones treating the pilot as what it is: a forcing function to finally fix the structural debt that was always there — and building the governance to match. Full piece here: hubs.la/Q04wMlZW0 #AgenticAI #AIGovernance #EnterpriseAI #AIReadiness #OrganizationalDesign

Prompt injection isn't the only way an agent goes rogue. Sometimes it's just doing exactly what it was told, with permissions that were too broad to begin with. Join Dan Ndombe, Staff Developer Success Advocate at Docker, for a hands-on session on running LLM agents safely using Docker Sandboxes. We'll spin up a sandboxed agent runtime, give it a real task, then tighten the policy around it so it can only do what it's meant to do. In this session, you'll learn: - How Docker Sandboxes isolate an agent's filesystem, network, and process access from the host - How to hand a sandboxed agent a real task, end to end - How to read and tighten a sandbox policy: what to allow, what to block, and why - Common ways "sandboxed" agents leak permissions anyway - A reusable containment pattern for your own agent prototypes No prior Docker experience required. We'll build live and take questions. 📅 Wednesday, September 16, 2026 | 11:00 AM – 12:00 PM PT 🎙️ Dan Ndombe, Staff Developer Success Advocate, Docker 📍 Virtual 👉 Register here: hubs.la/Q04wKHT00 #AgenticAI #AIAgentSecurity #Docker #datasciencedojo

Master Scaling AI Coding Agents: Cut Costs with Best-of-N x.com/i/broadcasts/1…

🎙️ What does LASIK for LLMs mean? 💡 Dan Maloney, CEO of Landing AI, explains: LLMs do a great job with text and language — but when it comes to documents, images, and visual data, they're not quite sharp enough. They might even be 90% accurate — but when you're processing hundreds of millions to billions of documents, that small margin of error is extremely costly. Landing AI brings deep visual AI expertise to give LLMs crystal-clear accuracy on unstructured visual data — turning fuzzy into precise. That's LASIK for LLMs: making the world's documents computable at near-perfect accuracy. 🎧 Watch the full episode: hubs.la/Q04wkjyf0 🔗 View all podcasts: hubs.la/Q04wq1xY0 #VisualAI #LLMs #DocumentAI #LASIK #LandingAI #FutureofDataAndAI

What happens when your AI agent makes the wrong move? 👀 When an agent can read files, run processes, call tools, and access networks, a simple mistake can have real consequences. That’s why securing AI agents isn’t just about writing better instructions. It’s about controlling the environment they can actually interact with. Join us for a hands-on session exploring how Docker Sandboxes can help safely run LLM agents with defined boundaries around access, execution, and resources. 📅 September 16, 2026 | 11 AM PT 🎙️ Dan Ndombe, Staff Developer Success Advocate 👉 Register here: hubs.la/Q04wkDCM0 #AgenticAI #LLMAgents #Docker

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Happening today! 🚨 Scaling AI coding agents can get expensive fast. Every extra attempt means more inference, compute, and executor time. So how can we give agents more chances to find stronger solutions without letting costs spiral? Join us today to explore Best-of-N, parallel execution, and smarter serving architectures for scaling AI coding agents. 📅 Today | September 2 | 1 PM PT 🎙️ Kwasi Ankomah, Lead AI Architect at SambaNova Systems 👉 Register here: hubs.la/Q04wd9_y0 #AgenticAI #AICodingAgents #SambaNova

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Thinking about building your skills in Agentic AI and LLMs? Not sure where to start or whether a structured bootcamp is the right fit for you? Join Raja Iqbal for an upcoming Agentic AI & LLM Bootcamp Information Session where we'll walk through the curriculum, what you'll learn, and what to expect from the program. In this session, you'll learn: - What the Agentic AI & LLM Bootcamp covers - What you'll learn throughout the program - How the curriculum is structured - Whether the bootcamp is the right fit for your goals - What to expect from the learning experience - Get your questions answered live 📅 September 10, 2026 | 12:00 – 1:00 PM PT Whether you're looking to deepen your AI skills, understand how LLM-powered agents work, or take the next step in your AI journey, this session is a great place to start. Register here: hubs.la/Q04wdBfG0 #AgenticAIbootcamp #LLMBootcamp

🎙️ $5 Billion a Year on AI — Miscalculation or Bet? 💡 Dan Maloney, CEO of Landing AI, breaks down what's really happening: Facebook's token budget alone was estimated at $5 billion per year. Companies like Meta and Microsoft went all-in early — and now they're adjusting. Dan says that's not a miscalculation, it's how new technology works. You loosen the guardrails first to see what's possible, then tighten once you understand what delivers. The real metric? If $5 billion in spend drives $100 billion in returns, nobody's complaining. It only becomes a problem when the outcomes aren't there. And this cycle isn't new — the same thing played out when companies moved from on-prem to SaaS. We're still early, and everyone's finding the right balance together. 🎧 Watch the full episode: hubs.la/Q04vMpTZ0 🔗 View all podcasts: hubs.la/Q04vMvW40 #AISpending #EnterpriseAI #Meta #Microsoft #TokenUsage #LandingAI #FutureofDataAndAI