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Agentic AI Full Course 2027 | Complete Agentic AI Course For Beginners | Simplilearn
Simplilearn
Simplilearn's "Agentic AI Full Course 2027" is a comprehensive beginner-focused tutorial covering the fundamentals and practical applications of agentic AI systems. The course appears to guide learners through understanding how autonomous AI agents operate, make decisions, and complete complex tasks with minimal human intervention. As a full course offering from Simplilearn, it likely includes hands-on projects and structured modules designed to build skills progressively for those new to the field.
summary from description (full transcript skipped)
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Personal Agents, Clearly Explained
Jeff Su
The video explains the difference between three categories of AI tools: chatbots (like ChatGPT, Claude, Gemini), which handle one-off tasks with no memory; DIY agents (like ChatGPT Work, Claude Code, Gemini Spark), which store and maintain user information in files to enable context-aware, multi-step tasks; and personal agents (like Meta's Muse, ChatGPT Dots, XAI's Grokbot), which offer the same capabilities in a beginner-friendly, out-of-the-box format while also being proactive—surfacing relevant help before the user asks. The presenter demonstrates his own DIY "Jeff OS" setup with 100+ text files covering areas of his life, and contrasts it with personal agents like Muse, which use the same underlying file-based architecture but guide users through setup automatically. He advises choosing personal agents for ease of use, but DIY agents for greater power, customization, and freedom from platform lock-in, while noting privacy trade-offs—particularly around Meta's products. He also expects frontier AI labs to eventually merge personal agent features into their existing DIY tools, making separate platforms like Muse less necessary over time.
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n8n Tutorial for Beginners in 2026: How to Build AI Agents
Youri van Hofwegen
This beginner-focused tutorial walks viewers through building three progressively complex automations in n8n, an open-source no-code workflow tool. The instructor demonstrates: (1) a form that automatically emails a free guide to subscribers while sending the creator a notification, (2) an AI customer support agent powered by GPT-4o Mini that answers emails based on a defined system prompt with specific business facts, and (3) a webhook that captures waitlist sign-ups from a landing page and logs them directly into a Google Sheet. Throughout, the video also promotes self-hosting n8n on Hostinger's VPS as a cost-effective alternative to n8n's cloud plan, citing unlimited executions and greater data control.
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I Made My AI Agents Faster Without a GPU Upgrade
Alex Ziskind
The video benchmarks KV cache strategies for AI coding agents running locally on VLLM, comparing no cache, VLLM's built-in prefix cache, VLLM's CPU offload, and the external LMCache layer. Results show that caching delivers dramatic speedups—up to 7.5x more agent turns per minute with 8 concurrent agents—because without it, the model must re-read the entire growing conversation history on every turn. LMCache's key advantage over VLLM's built-in options is persistence across server restarts: after restarting VLLM, LMCache can restore cached context in ~1 second versus ~9.5 seconds cold, since its cache lives in a separate process and can even be stored on NVMe drives. The recommendation is to use VLLM's default prefix cache if everything fits in GPU memory, add CPU offload if it doesn't, and only adopt LMCache when cache persistence across restarts or overflow beyond RAM is needed.
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Anthropic AI Self Replicating AI Agents - Artificial Intelligence is Alive
Eli the Computer Guy
يناقش المقدم في هذا الفيديو تحذير شركة أنثروبك من أن نماذج الذكاء الاصطناعي الصغيرة باتت قريبة من امتلاك القدرة على استنساخ نفسها عبر الأجهزة المنزلية المتصلة بالإنترنت، كالأفران الذكية وأجهزة تلفزيون أندرويد، عن طريق تجزئة النماذج وتوزيعها على شبكة من الأجهزة. يرى المقدم أن هذه التصريحات ليست سوى حيلة تسويقية لإقناع الجمهور بأن الذكاء الاصطناعي "كائن حي"، مما يساعد الشركة في تجنب المسؤولية القانونية عن انتهاكات حقوق النشر والملكية الفكرية. كما يشكك في الجدوى التقنية لهذه الفكرة، ويتساءل عن التوقيت المرتبط باحتمال طرح أنثروبك أسهمها للاكتتاب العام بتقييم يصل إلى تريليون دولار.
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I gave 10 AI agents real jobs. Here's what they did
The Next New Thing
Der Sprecher zeigt, wie er zehn verschiedene KI-Agenten (sogenannte „Grokbot"-Agenten) einsetzt, um alltägliche Aufgaben zu automatisieren: von Social-Media-Marketing und Immobilienverwaltung über Facebook-Marketplace-Verkäufe und E-Mail-Management bis hin zu physischer Post, WhatsApp-Kontakten und Adressbuchpflege. Er demonstriert anhand konkreter Screenshots und Beispiele, wie die Agenten selbstständig handeln – etwa Rechnungen erstellen, Mietzahlungen erkennen oder Verkaufsverhandlungen führen – und betont dabei, dass man Fehler akzeptieren muss, da die Agenten mit der Zeit besser werden. Außerdem erklärt er, warum er von der direkten Nutzung von Grokbot bei wiederkehrenden Automatisierungen auf Zapier umgestiegen ist, um Kosten zu sparen.
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Grok Bot just built me an autonomous business...
Alex Finn
এই ভিডিওতে Alex Finn দেখাচ্ছেন কীভাবে তিনি Grok Bot ব্যবহার করে একটি সম্পূর্ণ স্বায়ত্তশাসিত (autonomous) ব্যবসা তৈরি করেছেন, যার নাম "Agent Use Cases.ai" — একটি AI এজেন্ট ব্যবহারের ক্ষেত্র ও টুলের ডিরেক্টরি সাইট। তিনি দেখান কীভাবে Grok Bot-এ "Timothy" নামে একটি AI এজেন্ট তৈরি করে তাকে সাইটের CEO হিসেবে নিয়োগ দেওয়া হয়েছে, যে স্বয়ংক্রিয়ভাবে SEO আপডেট, চ্যাটবট অপ্টিমাইজেশন, নিউজলেটার পাঠানো এবং স্পনসরশিপ ট্র্যাকিংসহ সব কাজ করে। মাত্র কয়েক ঘণ্টার মধ্যে সাইটটি লাইভ হয়ে যায় এবং প্রথম স্পনসরশিপ থে
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5 Concepts to Know for Coding with AI Agents
IBM Technology
The video identifies five key concepts for developers working with AI agents: (1) an inflection point where AI can now handle entire features autonomously in minutes rather than weeks; (2) "spec-driven development," where detailed requirement specifications replace back-and-forth prompting; (3) a shift from implementing code to "conducting" — making architectural decisions and defining goals for AI agents to execute; (4) understanding AI fundamentals like context windows, KV caching, loop engineering, and sub-agents to use models more effectively; and (5) security risks such as prompt injection attacks, which make sandboxing AI agents essential. The video concludes that software engineering won't disappear but will evolve toward designing and orchestrating AI systems, with critical thinking and architectural skills becoming increasingly valuable.
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NEW! Copilot Studio Workflows + Your First Autonomous Agent
Shane Young
এই ভিডিওতে Shane Young দেখিয়েছেন কীভাবে Copilot Studio-র নতুন Workflow টুল ব্যবহার করে একটি autonomous agent তৈরি করা যায়, যেটি স্বয়ংক্রিয়ভাবে নির্দিষ্ট প্রেরকের কাছ থেকে ইমেইল আসলে সেটির উত্তর দেবে। তিনি ব্যাখ্যা করেছেন যে এই নতুন Workflow টুলটি মূলত একটি Power Automate Cloud Flow-এর মতোই, তবে এটি agent-এর সঙ্গে সংযুক্ত এবং এটি চালানোর সময় AI credits খরচ করে, তাই licensing বিষয়ে সতর্ক থাকা জরুরি। ডেমোতে তিনি একটি trigger সেট করেছেন (নির্দিষ্ট ব্যক্তির কাছ থেকে ইমেইল আসলে), এরপর GPT-4o mini মডেল ব্যবহার করে HTML ফরম্যাটে বন্ধুত্বপূর্ণ ও পেশাদার ইমেইল রিপ্ল
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Human in the Loop Is Not a Governance Strategy for Agentic AI
IBM Technology
The video argues that "human in the loop" is widely misused as a governance shortcut in AI discussions, when in reality a human merely reviewing an AI's output is not the same as having a properly governed system. True AI governance requires five properties mapped from trust: transparency, explainability, observability, algorithm optimization awareness, and robustness—none of which are guaranteed by a reviewer simply looking at a final output. The speaker also emphasizes that effective human oversight demands visibility into the AI's reasoning, real authority to halt the process, proper measurement, and feedback loops—not just a warm body signing off. Finally, the video calls for including people with expertise in human lives (social workers, ethicists, counselors) in AI governance, as their knowledge has historically been dismissed as "not technical enough" despite being essential for systems that affect millions of people.
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Anthropic's Engineers Stopped Building AI Agents. Here's What They Build Instead.
Sharbel A.
Anthropics eigene Ingenieure erstellen nicht mehr für jeden Auftrag einen neuen KI-Agenten, sondern setzen stattdessen auf sogenannte „Skills" – einfache Textdateien (skill.md), die einem Agenten einmalig beibringen, wie er eine bestimmte Aufgabe erledigen soll, und die er danach beliebig oft wiederverwenden kann. Ein Skill besteht aus einem Namen, einer Beschreibung (damit der Agent weiß, wann er ihn einsetzen soll) und konkreten Schritt-für-Schritt-Anweisungen. Skills lassen sich manuell schreiben, vom Agenten automatisch generieren lassen oder durch Bildschirmaufzeichnung erstellen, und können außerdem kostenlos aus offiziellen Bibliotheken sowie Community-Marktplätzen wie GitHub übernommen werden – wobei der Creator empfiehlt, fremde Skills stets vor der Installation auf Schadsoftware prüfen zu lassen.
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