Agent Skills, Rules, Subagents: Explained!

🔥 Join Maker School & get customer #1 guaranteed: https://skool.com/makerschool/about 💎 Check out my SaaS, Clairvo (we 2x your pickup rate): https://clairvo.io?s=nick ➡️ Get all AI agent course resources 100% free: https://skool.com/maker-zero/about If this is your first video: I'm Nick Saraev. I run LeftClick, an AI growth agency. We've done work for large brands you're likely familiar with, like Mr. Beast, Anthropic, OpenAI, and a few others. In plain English: I help people build systems that generate leads, close deals, and scale businesses, mostly using new AI models like Claude. I also make videos about how to do all of that here on YouTube. It hasn't always been this way. My family immigrated from a Soviet bloc country (People's Republic of Bulgaria) in the 90s. They worked extremely hard, and we were broke for a very long time. I grew up wishing for more security, stability, and freedom over my own life. I don't have a programming degree, and never took formal education for IT or workflows. I learned it all myself from YouTube videos like you're watching now. As for my path: I started my first business at 19 in college. We threw events (mostly parties) at campus bars, and charged people for entry. That failed to provide me enough money to pay my bills, so at 21, I started another business, a door-to-door marketing agency. From there, every year, I would start several companies, over 10 in total. I did this in a variety of industries, like e-commerce, photography, videography, SaaS, credit repair, etc. Each grew slightly more profitable, until, at 25, I would start 1SecondCopy, a content writing company. A friend and I eventually scaled that to over $90,000/m. It was my first taste of financial independence, and the reason I'm here today. Since starting my journey, I've grown a fair bit of capital. To diversify my income, at 30, I began investing in other businesses and advising companies on how to grow in the AI era. These include SaaS businesses, like Clairvo, agencies like Dental Connect, and more. Collectively, the businesses that I own outright or are a part of generate over $10 million per year. This returns far more than the 5-10% you would get in the stock market, but also requires a lot of my active time. There's a tradeoff there, but I greatly prefer active investing, where I have control over the entities I'm a part of. It wasn't easy to get here. But I did in the end! For anyone on their own entrepreneurial journey: I wish you luck, happiness, and perseverance. You can make it! Summary ⤵️ Hey, this is an end to end, extremely comprehensive course all about AI agents. It covers the three modern agentic AI tools: Codex, Claude Code, and Antigravity, and is agnostic to whichever you use. I will guide you through initial setup; workspace configuration; and then a variety of foundational to prompting techniques like self modifying agent instructions, multi agent MCP orchestration, video-to-action pipelines, agent chatrooms, subagent verification loops, prompt contracts, reverse prompting, and even more! By the end, you will have learned, no fluff, both foundational AI agent design and advanced prompt engineering both. You will also have mastered a bunch of key agentic AI principles, like context management and token usage optimization! Thanks and happy watching! My software, tools, & deals (some give me kickbacks—thank you!) 🚀 Instantly: https://link.nicksaraev.com/instantly-short 📧 Anymailfinder: https://link.nicksaraev.com/amf-short 🤖 Apify: https://console.apify.com/sign-up (30% off with code 30NICKSARAEV) 🧑🏽‍💻 n8n: https://n8n.partnerlinks.io/h372ujv8cw80 📈 Rize: https://link.nicksaraev.com/rize-short (25% off with promo code NICK) Chapters 00:00 Introduction to AI Agent Full Course 02:14 Multi-Agent Chrome MCP Workflow Demonstration 04:28 Core Agent Workflow 09:09 Understanding AI Agent Architecture 13:18 The Three Major AI Agent Platforms (Codex, Claude Code, Antigravity) 22:29 Platform-Specific Performance Insights 25:43 Self-Modifying System Prompts 34:57 Standardizing Workflows with Agent Skills 39:03 Multi-Agent Orchestration Strategies 47:20 Video-to-Action Pipeline 56:07 Implementing Stochastic Multi-Agent Consensus 1:04:44 Agent Suggestions Unveiled 1:05:08 Consensus Reports and Insights 1:06:05 Harnessing Multiple Agents 1:07:41 Agent Chat Rooms Explained 1:10:34 Debate and Collaboration Among Agents 1:13:25 Sub-Agent Verification Loops 1:17:32 The Mixture of Experts 1:20:56 Prompt Contracts Introduced 1:24:23 Crafting Effective Prompt Contracts 1:27:40 Reverse Prompting for Clarity 1:31:41 Context Management Strategies 1:37:34 Multi-Agent Chrome Automation 1:48:49 Understanding MCP Tools and Skills 1:53:34 Context Compression Techniques 1:59:19 Optimizing Token Usage 2:06:46 Cost-Efficient Multi-Agent Strategies 2:11:30 LLM Pricing Principles

⚡ 72% OFF Sintra AI employees with code LEONVANZYL: https://sintra.ai/leonvanzyl 🚀 Agentic Labs — exclusive AI coding courses, live Q&As, workshops & deep dives: https://skool.com/agentic-labs 🎁 Free RAMP course + all the resources from my videos: https://skool.com/leonvanzyl Claude Code is powerful, but it locks you into one provider and one bill. OpenCode is the open source alternative that gives you the same agentic workflow with any model you want — including completely free ones. In this walkthrough you'll go from install to advanced workflows: agent skills for better output, subagents that protect your context window, memory files that keep the agent on your rules, and automated browser testing. Together we build a full AI project planner and let the agent test it in a real browser — without me touching a thing. You'll also see why I never pay per token, and the one file that instantly fixes an agent that won't listen. ▶️ Watch next: I Locked Claude Code in a Docker Sandbox and Let It Go Full YOLO — https://youtu.be/iUDuN9dyuTY ⏱️ Chapters 00:00 - OpenCode vs Claude Code: What You Get Free 00:39 - OpenCode Setup & Install 01:25 - OpenCode Zen: Free AI Models 04:55 - Subscriptions vs API Keys (Stop Overpaying) 07:30 - OpenCode Skills from skills.sh 10:30 - AGENTS.md Memory Files 13:00 - Subagents & Context Window Protection 15:50 - Sponsor: Sintra AI 28:30 - OpenCode MCP: Playwright Auto Testing Connect X: https://x.com/leonvz TikTok: https://www.tiktok.com/@leonvanzyl Business & sponsorships: leon@cognaitiv.ai

Learn to use Anthropic's Claude Agent SDK (formerly Claude Code SDK) for AI-powered development workflows! https://platform.claude.com/docs/en/agent-sdk/overview https://x.com/trq212 **AI Summary** This workshop by Thariq Shihipar (Anthropic) details the architecture and implementation of the **Claude Agent SDK**. The session moves from high-level theory—defining "agents" as autonomous systems that manage their own context and trajectory—to a live-coding demonstration. Shihipar builds an agent "Harness" from scratch, implementing the core **Agent Loop** (Context Thought Action Observation), integrating the **Bash tool** for general computer use, and demonstrating **Context Engineering** via the file system to maintain state across long tasks. **Timestamps** 00:00 Introduction: Agenda and the "Agent" definition 05:15 The "Harness" concept: Tools, Prompts, and Skills 10:10 Live Coding Setup: Initializing the Agent class and environment 15:45 implementing the "Think" step: Getting the model to reason before acting 25:20 The Agent Loop: connecting `act`, `observe`, and `loop` 33:10 Tool Execution: Handling XML parsing and tool inputs 42:00 The "Bash" Tool: Giving the agent command line access 49:30 Safety & Permissions: "ReadOnly" vs "ReadWrite" file access 58:15 Context Engineering: Using `ls` and `cat` to build dynamic context 01:05:00 The "Monitor": Viewing the agent's thought process in real-time 01:12:45 Handling "Stuck" States: Feedback loops and error correction 01:21:20 Multi-turn Complex Tasks: Building a "Research Agent" demo 01:35:10 Refactoring patterns: "Hooks" and deterministic overrides 01:48:39 Q&A: Reproducibility, helper scripts, and non-determinism 01:50:31 Q&A: Strategies for massive codebases (50M+ lines) 01:52:00 Closing remarks and future SDK roadmap * **Evolution of AI Capabilities:** Shihipar argues we are shifting from **LLM Features** (categorization, single turn) to **Workflows** (structured, multi-step chains like RAG) to **Agents**. He defines agents as systems that *"build their own context, decide their own trajectories, and work very autonomously"* rather than following a rigid pipeline. * **The Claude Agent SDK Architecture:** The SDK is built directly on top of **Claude Code** because Anthropic found they were *"rebuilding the same parts over and over again"* for internal tools. * **The Harness:** A robust agent requires more than just a model; it needs a "Harness" containing Tools, Prompts, a **File System**, Skills, Sub-agents, and Memory. * **Opinionated Design:** The SDK bakes in lessons from deploying Claude Code, specifically the "opinion" that general computer use (Bash) is often superior to bespoke tools. * **The Agent Loop & Intuition:** Building a successful agent loop is described as *"kind of an art or intuition"*. The loop generally follows a **Gather Context Take Action Verify Work** cycle. Shihipar emphasizes that this loop allows the agent to self-correct, a capability missing from rigid workflows. * **Strategies for Determinism (Hooks):** During the Q&A, a technique for controlling agent behavior is discussed: **Hooks**. * If an agent hallucinates or skips a step (e.g., guessing a Pokemon stat instead of checking a script), a hook can intercept the response and inject feedback: *"Please make sure you write a script, please make sure you read this data."* * This enforces rules like "read before you write" without retraining the model. * **Scaling to Large Codebases:** For massive codebases (50M+ lines), standard tools like `grep` or basic context window stuffing fail. * **Semantic Search Limitations:** Shihipar notes that while semantic search is a common solution, it is *"brittle"* because the model isn't trained on the specific semantic index. * **Solution:** He recommends good **"Claude MD"** files (context files) and starting the agent in a specific subdirectory to limit scope, rather than trying to index the entire 50M lines at once. --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/TqC1qOfiVcQ-claude-agent-sdk-workshop Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIE New York, October 12–14 — the first AI Engineer Finance mainstage summit - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---

In this episode, I sit down with Alex Finn for a full, screen-shared walkthrough of Hermes Desktop, the new desktop home for the Hermes AI agent. I open with a clear challenge: by the end, sell me on installing Hermes Desktop, show me real ways to make money and stay productive, and explain his move from OpenClaw. Alex tours every major surface — sessions, profiles, artifacts, skills, cron jobs, and sub-agents — and shares money-saving tactics at each step. We close on the idea that matters most to me: aiming these agents at other people's challenges as the clearest path to real value. Timestamps 00:00 – Intro 04:04 – Sessions and Context Management 06:10 – Profiles Explained 08:49 – Model-Based vs Role-Based Profiles 12:58 – Artifacts as a Second Brain 14:32 – Why Alex Switched From OpenClaw 17:32 – Skills, Tools, and Tool Sets 19:19 – Messaging and Cron Setup 21:44 – Reverse Prompting and the Brain Dump 28:09 – Sub-Agents vs Profiles 32:12 – Putting It Together: Solving Challenges 32:38 – The Daily Business Opportunity Scan 37:05 – Local Models: Mac Studio vs DGX Spark 39:03 – Reframing Cost as Investment 41:59 – The Real Way to Make Money With Hermes 42:51 – Closing Thoughts Key Points * Hermes Desktop pulls sessions, profiles, artifacts, skills, and cron jobs into one polished, Apple-style interface. * Smart session and context management keeps each message slim and keeps monthly costs low. * Profiles map to different models — Opus 4.8 for strategy, ChatGPT 5.5 for coding, a local Qwen model for free research — so each task runs on its best fit. * Reverse prompting plus a personal brain dump produces far stronger prompts, cron jobs, and outputs. * Sub-agents handle one skill across many parallel tasks; profiles handle work where each step needs a distinct skill set. * The biggest opportunity: aim your agent at Reddit and X to surface real problems you are positioned to solve. Numbered Section Summaries 1. The Moment Hermes Overtook OpenClaw Alex shares his screen and calls Hermes Desktop the best AI agent experience available right now, framing the recent release as the moment Hermes pulled ahead. He compares the focused, polished Hermes updates to Apple and the broader OpenClaw approach to Android, and notes his switch came purely for the love of the game. 2. Sessions and Context Management Alex shows how each new chat opens its own session, keeping context clean and separated by topic. He explains that slim context keeps every message small, and small messages keep monthly bills modest — his top money-saving tip. 3. Profiles Mapped to Models Profiles are separate Hermes agents, each with its own skills, a soul.md personality, and its own memories. Alex organizes his by model — Opus 4.8 for high-level strategy, ChatGPT 5.5 for coding, and a local Qwen model for free, fast research — and picks the profile whose strengths match the task. 4. Artifacts as a Productized Second Brain Artifacts gathers every link, image, and file you send your agent into one searchable place. Alex drops links to his "Librarian" profile and lets Artifacts file them automatically, which turns the agent into a tidy, searchable second brain. 5. Skills, Tools, and the Cron Section Alex walks the Skills interface, where 150-plus skills ship out of the box and you keep only the ones you use to trim context and cost. He highlights tool sets as a fresh way to group skills together, and praises the Cron section for giving one-click confirmation that scheduled tasks truly exist. 6. Reverse Prompting and the Brain Dump My favorite tip from Alex: brain dump everything about yourself — interests, goals, skills — then ask the agent for the best prompt to use. He demos it live by building a morning brief, and the reverse prompt returns a detailed, well-formatted instruction that pulls fresh, real headlines, prices, and scores from the last 24 hours. 7. Sub-Agents vs Profiles Alex clarifies the difference: sub-agents are copies of your main agent that share its skills, ideal for running one skill across many parallel tasks, like building several features of a micro-SaaS at once. Profiles each carry distinct skill sets and memories, ideal when a job needs a researcher, a writer, and a designer working in sequence. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com/ LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ALEX ON SOCIAL Youtube: https://www.youtube.com/@AlexFinnOfficial/videos X/Twitter: https://x.com/AlexFinnX Creator Buddy: https://www.creatorbuddy.io/

Try https://waku.one, Me https://seanchen.io, Open Source: https://github.com/ShenSeanChen/waku-agent I An LLM is an incredibly powerful brain that knows everything about humanity and nothing about you or the software you run. This video walks through the four buzzwords that turn that raw brain into a system you can trust: agent harness, loop engineering, LLM Ops, and eval. No jargon, step by step, technical or not. You can build anything. You can learn anything. 💪 Timeline 0:00 Intro: the 4 AI agent buzzwords 0:42 What an AI agent run actually is 1:52 The memory system: procedural, semantic, episodic 3:37 What "harness" really means (the horse) 5:07 Storing and updating memory (databases, skills, summarizer agent) 8:28 Retrieval: RAG, SQL vs semantic search 10:00 Tool calling and why agents loop 10:52 Loop engineering and end-loop guardrails 13:21 A Claude Code hooks example 14:18 Eval and LLM Ops: why you need them 15:55 Tracing every run (Langfuse, LangSmith) 16:43 Evaluation: LLM as a judge 17:20 Diagnosing what broke 18:16 The gate: ship the fix or fix the bug 18:57 Zoom out: the full system 19:53 Wrap up Launch Full-Stack App Template: https://github.com/ShenSeanChen/launch-mvp-stripe-nextjs-supabase My AI Agent Startup AutoManus.io is an AI sales lead manager for made-to-order product sales. We embed directly where conversations happen (WhatsApp, email, web chat) to capture inbound, automate follow‑ups, and kill CRM busywork; live with 4 pilots and 2 contracts in motion, pre‑seed backed by Character VC. Focused on US/UK/Germany, raising to expand engineering and scale deployments. ☕️ Buy me a coffee: https://buy.stripe.com/5kA176bA895ggog4gh - X: https://x.com/ShenSeanChen - Sean's Discord: https://discord.gg/tvECErKcFr - AutoManus Discord: https://discord.gg/5HhcNjCR - LinkedIn: https://linkedin.com/in/shen-sean-chen - Github Link: https://github.com/ShenSeanChen - Instagram: https://www.instagram.com/sean_ai_stories Sub Count when launched: 13,050 Top Github Repos - LaunchMVP NextJS,Supabase,Stripe (1015 stars): https://github.com/ShenSeanChen/launch-mvp-stripe-nextjs-supabase - ReactNextJSTips (114 stars): https://github.com/ShenSeanChen/yt-react-nextjs-tips - DeepResearchAgentBackend (70 stars): https://github.com/ShenSeanChen/yt-DeepResearch-Backend - SupabaseTipsKanban (64 stars): https://github.com/ShenSeanChen/yt-supabase-tips-kanban - RAGVectorDB (56 stars): https://github.com/ShenSeanChen/yt-rag - KimiK2Claude (37 stars): https://github.com/ShenSeanChen/yt-kimi-k2-claude - DeepResearchAgentFrontend (33 stars): https://github.com/ShenSeanChen/yt-DeepResearch-Frontend - AgenticRAG (13 stars): https://github.com/ShenSeanChen/yt-agentic-rag You Can Build Anything Playlist (Full-Stack Dev Without CS Degrees) - Core7: 95% React/NextJS Use Cases https://www.youtube.com/watch?v=vZzFlAjz4rA&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=16 - Core6: 95% Supabase Use Cases https://www.youtube.com/watch?v=Pnoq2tIif3s&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=15 - Core5: StripeNextJSSupabase https://www.youtube.com/watch?v=ad1BxZufer8&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=8 - Core4: AuthSupabaseGoogle https://www.youtube.com/watch?v=AZAU3ClAWWE&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=6 - Core3: FastapiGCPPro https://www.youtube.com/watch?v=u3sfqpzzo-U&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=5 - Core2: SupabaseHero https://www.youtube.com/watch?v=V0kmgkyPsVQ&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=4 - Core1: LaunchAnApp https://www.youtube.com/watch?v=iQ2izvGG4tQ&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=3 - Launch WhereToMeet w/ GoogleMaps, Calendar, Supabase, Cursor: https://www.youtube.com/watch?v=5xMjX1QxGUY&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=2 - Launch EncourageMe w/ Cursor, Supabase, Vercel https://www.youtube.com/watch?v=hnvL4xa2DHA&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR

SpaceXAI recently acquired Cursor for $60 Billion. In this complete course I will teach you Cursor from start to finish, ensuring mastery. I will cover every single Cursor feature, and build multiple applications with Cursor in this course. Throughout the course, I've used the Grok 4.5 model, which was released jointly by Cursor and SpaceXAI. I walk you through this full masterclass where I start by talking to you about how Cursor came to be and how to start using Cursor. I then teach you about the Cursor interface and some cool features in Cursor. I teach you how to build apps from scratch using Cursor, and I also talk about Github, Vercel, Native Browser, Design Mode, Skills, MCP, Plugins, and how to make money with Cursor. Hope this course provides value! Timestamps: 00:00 Introduction to the Cursor Course 00:55 Understanding Cursor 02:36 Cursor Pricing 03:45 Learning about the Cursor Interface 05:31 Modes in Cursor 06:47 Prompt Box 07:31 Building your First Application 13:58 Iterating on the First App 17:47 Native Browser in Cursor 19:24 Design Mode in Cursor 24:08 Grok 4.5 26:56 Rules in Cursor 28:44 Context Window Explained 29:59 Tokenomics in Cursor 31:09 Model Routing 32:49 Prompt for the Second App 35:44 Plan Mode 42:12 Reviewing the Application 45:56 Ask Mode 48:26 Testing the Final Version 50:17 Github 55:26 Deploying with Vercel 57:22 Agent Skills in Cursor 1:07:17 MCP and Plugins 1:11:44 Subagents in Cursor 1:13:17 Revising Plugins 1:13:56 Dictation 1:15:41 Prompting Tips 1:18:42 Debugging Tips 1:22:27 Multitask and Parallel Agents 1:26:08 Usage Check 1:26:28 How to Make Money with Cursor 1:31:19 Thank You