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I sit down with Leon van Zyl, who ran a web design company for 10 years and now teaches over 700 people how to build real applications with coding agents. We walk through his exact workflow for building professional, client-ready websites using Google Stitch for the design system and Claude Code for the build — no coding skills required. Leon shows the difference between a one-shot AI-generated site and what you get when you front-load the design system before touching code. By the end, you'll have a repeatable workflow for going from design concept to finished website — including custom AI images that match your brand. Links Mentioned: Google Stitch: https://stitch.withgoogle.com Claude Code: https://docs.anthropic.com/en/docs/claude-code Cursor: https://www.cursor.com Next.js: https://nextjs.org Stitch MCP Server Docs: https://stitch.withgoogle.com/docs/mcp Stitch Skills: https://stitch.withgoogle.com/docs/skills Timestamps 00:00 – Intro 00:06 – What you'll learn: design systems for client-ready websites 02:04 – Jumping into the screen share 02:25 – The problem: one-shot AI websites look terrible 03:52 – The Stitch workflow result: side-by-side comparison 07:32 – Starting from a vanilla Next.js project 08:50 – What is Google Stitch and how to get started 10:00 – Prompting Stitch with brand details, fonts, and colors 13:00 – Why design systems matter for coding agents 16:00 – Iterating on the homepage before building more pages 17:44 – Sharing Stitch designs with clients for approval 21:23 – Setting up the Stitch MCP server in Claude Code 23:18 – What an MCP server actually is (simple explanation) 25:56 – Pulling the design system into your project 28:47 – Memory files: Claude.md vs Agents.md explained 33:24 – Converting the Stitch design into a working website 35:06 – Installing the Stitch React Components skill 41:11 – When to use this workflow: client work vs personal projects 44:27 – Viewing the finished website vs the Stitch mockup 48:27 – Downloading and converting images to WebP for performance 53:46 – Generating custom AI images with Nano Banana Pro 58:14 – Final result with branded AI-generated hero image 01:00:48 – Key takeaways and wrap-up FIND ME ON SOCIAL X/Twitter: https://x.com/coreyganim Instagram: https://www.instagram.com/coreyganim/ LinkedIn: https://www.linkedin.com/in/coreyganim/ FIND LEON ON SOCIAL YouTube: https://www.youtube.com/@leonvanzyl

Claude Code just dropped routines, and when I first saw the three options — routine, schedule, and loop — I had no idea when to use which. In this video, I break down all three modes in plain language and then demo building a routine from scratch using an X trend scanner I already had in my skill library. You'll see the full setup: GitHub connection, system prompt config, trigger options, and connector permissions. By the end, you'll know exactly which mode to use for any automation you want to build and how to get your first routine live. Links Mentioned: Claude Code Routines: https://claude.ai/code/routines GitHub: https://github.com Timestamps 00:00 – Intro: The confusion with Claude Code's new features 00:20 – The three modes: routine, schedule, and loop 00:50 – When to use each mode (simple breakdown) 01:10 – Using Claude Code to find a skill to demo 01:45 – Selecting the X scan routine 02:00 – GitHub requirement for routines explained 02:18 – Creating a new routine at claude.ai/code/routines 02:35 – Naming your routine and connecting your GitHub repo 02:50 – Dropping in your system prompt 03:05 – Setting the schedule trigger (10am Eastern daily) 03:20 – Configuring connectors and permission sets 03:40 – Running on demand and reviewing the output 04:10 – Full recap of all three modes Key Points * Claude Code has three automation modes — routine (runs on Anthropic's cloud, set it and forget it), schedule (needs local access, also available in Cowork), and loop (immediate execution in the CLI). Picking the wrong one means your automation won't work the way you expect. * Routines require a GitHub repository. You can't create one without it, so get your repo connected before you start. * The whole setup happens at claude.ai/code/routines — no coding required beyond having a system prompt in markdown format ready to paste in. * Routines support three trigger types: time-based schedule, GitHub event, or API call. That gives you flexibility depending on whether you want it cron-based, push-based, or fired from another system. * The X trend scanner ran automatically and surfaced several trending topic candidates with suggested content angles — zero manual research, just results ready to use. FIND ME ON SOCIAL X/Twitter: https://x.com/GanimCorey Instagram: https://www.instagram.com/coreyganim/ LinkedIn: https://www.linkedin.com/in/coreyganim/ FIND NICK ON SOCIAL X: https://x.com/NickSpisak_ LinkedIn: https://www.linkedin.com/in/nicholasspisak/ YouTube: https://www.youtube.com/@UCusMlMDWZS0uOlhgL0M_q-A

Grab the free Google Doc to build and deploy your first Claude Managed Agent in 60 seconds: https://return-my-time.kit.com/2872b904f5 I sit down with Nick Spisak, an AI agent builder who deployed his first Claude Managed Agent the same week Anthropic released the capability, to break down exactly what this platform is, who it's for, and when it makes financial sense to use it. We walk through the four user personas Claude Managed Agents is built for. Links Mentioned: Corey's X article: https://x.com/coreyganim/status/2042286607449874527 Nick's X article: https://x.com/NickSpisak_/status/2041949191887262164 Timestamps 00:00 – Intro 00:05 – What is Claude Managed Agents? 00:29 – Architecture: decoupling tools, sessions, and orchestration 01:15 – Who managed agents is and isn't for 01:33 – The four user personas breakdown 03:58 – Why AI Tinkerers should stick with Claude Code subscription 04:21 – Free Google Doc: build your first agent in 60 seconds 05:28 – Platform-as-a-service model explained 05:43 – Cost comparison: Managed Agents vs Agent SDK 06:09 – Live look inside platform.claude.com 06:23 – Workbench, sessions, and output walkthrough 08:16 – Sessions: tool calls vs. finished output explained 08:31 – Analytics dashboard and real cost breakdown 09:36 – When the ROI math works (and when it doesn't) 11:18 – Next steps: articles on X, how to get started 12:04 – Outro Join the Build With AI community - weekly AI implementations, live coaching, and templates built for non-technical entrepreneurs: https://www.skool.com/buildwithai/about FIND ME ON SOCIAL X/Twitter: https://x.com/coreyganim Instagram: https://www.instagram.com/coreyganim/ LinkedIn: https://www.linkedin.com/in/coreyganim/ YouTube: https://www.youtube.com/@coreyganim FIND NICK ON SOCIAL X: https://x.com/NickSpisak_ LinkedIn: https://www.linkedin.com/in/nicholasspisak/ YouTube: https://www.youtube.com/@nickspisak_

Download Nick's free second brain skill -- one-click install that sets up your entire Obsidian vault and ingestion workflow inside Claude Code: https://return-my-time.kit.com/286e11f7e6 I brought on Nick Spisak to build a complete second brain live -- start to finish, in under 20 minutes. By the end of this episode, you'll know exactly how to build your own second brain -- and you can grab Nick's free skill to do it in one click. Timestamps 00:00 - Intro and Karpathy's viral second brain tweet 00:24 - What the second brain concept is 03:28 - Obsidian Web Clipper: scraping pages into your vault 04:41 - Nick's free skill: wizard, ingest, query, and lint commands 05:53 - Live demo: running the setup wizard in Claude Code 08:38 - How many vaults to manage: personal vs. business 10:30 - Opening the vault and exploring the file structure 12:21 - Graph view: seeing connections between your data 15:38 - Ingest command: raw data into organized wiki 16:29 - Automating ingestion on a cron schedule 19:12 - Compounding value and syncing the vault across devices 20:19 - Pruning the vault with the lint command 21:53 - Your data set as a moat in the AI age Key Points * Karpathy released a framework for building an LLM knowledge base. Nick turned it into a free Claude skill with a guided setup wizard, ingest, query, and lint commands -- works across Claude Code, Codex, Gemini CLI, and more. One-click install, no coding required. * The system runs on three tiers: raw (brain dump), wiki (AI-organized knowledge base), and outputs (answers from querying). Drop files into raw, run ingest, and the AI maps everything into structured wiki entries with relationship graphs. * You can automate ingestion using Claude Code's loop feature so the vault stays current without manual work. Pair with Obsidian's paid sync tier and a note captured on your phone is indexed before you're back at your desk. * The lint command health-checks your wiki for outdated entries and missing connections -- and tells you exactly what to clip next to close the gaps. The wiki tells you what it doesn't know yet. * Day zero this thing is basic. Day 90 it's a company asset no competitor can copy. Your private knowledge base is the foundation for every agent and skill you build -- and nobody else will have it. Join the Build With AI community - weekly AI implementations, live coaching, and templates built for non-technical entrepreneurs: https://www.skool.com/buildwithai/about FIND ME ON SOCIAL X/Twitter: https://x.com/coreyganim Instagram: https://www.instagram.com/coreyganim/ LinkedIn: https://www.linkedin.com/in/coreyganim/ YouTube: https://www.youtube.com/@coreyganim FIND NICK ON SOCIAL X: https://x.com/NickSpisak_ LinkedIn: https://www.linkedin.com/in/nicholasspisak/ YouTube: https://www.youtube.com/@nickspisak_

Eliot Prince is an SEO specialist with 10+ years of experience ranking businesses at the top of Google. He's now deep in the AI world, coaching businesses on how to do SEO faster and better using AI tools. In this episode, Eliot walks through how he's using Perplexity Computer to build repeatable SEO machines — systems that audit websites, generate deliverables, and even push changes live to WordPress, all from a single conversation. We run a live audit on ReturnMyTime.com, watch three audit modules execute in parallel, and dig into the results — competitive analysis, keyword gaps, technical fixes, and auto-generated page copy. Eliot also demos a LinkedIn lead machine he built that reads DMs, scores leads, and drafts replies automatically using Perplexity's Linkup API connector. The big takeaway: Perplexity Computer runs 19 LLM agents in the cloud simultaneously, meaning you can build systems that would traditionally take weeks of manual work or expensive SEO tool subscriptions - and you don't need to write a single line of code to do it. Find Eliot YouTube's channel here:@princeeliot Join the Build With AI community here: https://www.skool.com/buildwithai/about

James Dickerson (AKA The Boring Marketer) has been consulting businesses on marketing and growth since 2012 — and he's now using Claude Code to do what used to require a $5-10K/month agency. In this episode, James goes screen-share and builds a complete marketing funnel live from scratch: a landing page, a quiz funnel, a 14-day email nurture sequence, and dozens of social and SEO content assets — all inside Claude Code with zero coding.   We break down the psychology behind high-converting email sequences (micro commitments, reciprocity, objection handling), how James's "skills" system encodes expert marketing knowledge into portable AI instruction files, and why anyone with these tools can immediately outperform 80% of marketers. If you've been procrastinating on Claude Code, this is your sign to just download an IDE and start. X: https://x.com/BoringMarketer Website: https://vibemarketer.com Youtube: @theboringmarketer

Grab the free one-page OpenClaw setup guide with every step and command listed out: https://corey-ganim.kit.com/c93f43577e I walk through the complete OpenClaw setup process from zero to a working AI agent connected to Telegram — all in under seven minutes. You'll see every step: running the installer, configuring your Anthropic API key, creating a Telegram bot through BotFather, pairing it to your OpenClaw instance, and enabling web search with DuckDuckGo. One prerequisite, one terminal command, and you're live. Key Takeaways: OpenClaw installs with a single terminal command — the only prerequisite is having Node.js installed, which is also a one-command setupThe guided onboarding handles every configuration decision (model, API key, channel, search) through simple yes/no prompts — no manual config filesCreating a Telegram bot through BotFather takes about 60 seconds: message BotFather, run /newbot, choose a name ending in "bot," and copy the tokenDuckDuckGo is the fastest search provider to start with because it requires zero additional API keys or setupSkills and hooks can be added after the initial install — you don't need to configure everything before getting your agent runningThe OpenClaw control panel gives you a browser-based chat window plus access to channels, sessions, usage stats, cron jobs, files, skills, and nodesTimestamps: 00:00 - Introduction 00:02 - Running the OpenClaw installer from the terminal 00:30 - Node.js prerequisite (quick install) 00:45 - Guided onboarding: Quick Start setup 01:05 - Choosing Anthropic as your model provider 01:20 - Entering your Anthropic API key 01:35 - Selecting Claude Sonnet 4.6 01:52 - Creating a Telegram bot with BotFather 02:45 - Naming your bot and choosing a username 03:15 - Connecting the bot token to OpenClaw 03:30 - Enabling DuckDuckGo web search 03:45 - Skipping skills and hooks (configurable later) 04:06 - OpenClaw control panel overview 04:30 - First chat with your bot in the browser 05:15 - Pairing the bot with your Telegram account 06:10 - First Telegram message confirmed 06:30 - Setup complete — next steps for personalization Links Mentioned: OpenClaw: https://openclaw.aiAnthropic API Console: https://console.anthropic.comBotFather (Telegram): https://t.me/BotFatherDuckDuckGo: https://duckduckgo.comNode.js: https://nodejs.orgEnjoyed this episode? -> Subscribe and leave a review -> Join the community waitlist: https://return-my-time.kit.com/1bd2720397

What if you could describe an automation in plain English and get a fully functional web app back in 15 minutes? In this episode, Kevin Fernando walks through exactly how he built a daily social media post generator using a tool called Appy. The agent researches trending stories in your niche every morning at 7 AM, writes platform-specific posts in your voice (not generic AI slop), generates properly sized images for each platform, and emails you the drafts. Kevin built it live, deployed it to the web, and even had Corey sign up and generate posts in real time during the episode. If you've been building automations in Make.com or N8N, this is the next evolution. Guest IntroductionKevin Fernando a 20-year entrepreneur, former head of marketing for multiple SaaS companies, e-commerce store builder/seller, and former agency owner (six years). Kevin now runs the Solopreneur YouTube channel where he teaches entrepreneurs how to get more leverage from AI tools and software without needing a team. YouTube: youtube.com/solopreneur Kevin just dropped the full step-by-step Appy tutorial on his channel. Watch it here and grab the exact prompt he used: Full Tutorial: https://youtu.be/eOkSQgh5UJo Grab the Prompt: https://solopreneur2020.kartra.com/page/appy-prompt

Corey puts two leading agentic AI tools head-to-head in a real-world showdown. He tests Perplexity Computer ($200/month) against Manus ($20/month) across three practical use cases: multi-source research with website deployment, connected app integrations with Google Workspace, and data collection with visualization. You'll see exactly how each tool performs on speed, accuracy, output quality, and which one earns Corey's recommendation for 2026. Join the Build With AI community waitlist: https://return-my-time.kit.com/1bd2720397 • Perplexity Computer completed tasks 5-10x faster than Manus across most tests — finishing in 60 seconds what took Manus 10 minutes • Both tools nailed data accuracy when researching AI startup funding, pulling identical figures from TechCrunch • Perplexity's Google Workspace integration produced cleaner, properly formatted deliverables (tables, headers, structured docs) while Manus output jumbled text • For website deployment, Manus actually had slightly better UI design — but both successfully created shareable public URLs • When stuck, Perplexity self-corrected and found the data; it recovered gracefully from errors • ClickUp was recommended by both tools as best value for project management pricing ($12/user/month for Business plan) • Perplexity Computer wins overall for speed, output quality, and cleaner UI despite the 10x higher price tag Timestamps: 00:00 - Introduction and test overview 00:30 - Pricing comparison ($200 vs $20 plans) 01:00 - Test 1: Multi-source research + website deployment 14:04 - Test 1 results: Speed comparison (2 min vs 10 min) 16:25 - Website design comparison 18:30 - Test 2: Gmail + Calendar + Google Docs integration 27:14 - Test 2 results: Output quality comparison 29:40 - Perplexity's formatted table vs Manus' jumbled text 32:00 - Test 3: Data collection, analysis, and visualization 39:30 - Test 3 results: Bar charts and pricing spreadsheets 41:52 - Final verdict and recommendation Links Mentioned: Perplexity Computer vs Claude Cowork: https://youtu.be/_s0ymvl6vNc• Perplexity Computer: https://perplexity.ai/ • Manus: https://manus.im/

What if you could go from a blank folder to a fully functional competitive research tool complete with scoring rubrics, interactive dashboards, and repeatable skills—in under an hour? In this episode, marketing veteran Adam Sandler (yes, that's his real name) shares his screen and builds the entire workflow live using a real-world use case: finding distressed wedding venues in North Carolina for a friend's acquisition business. No coding. No technical background. Just Claude Code, plain English, and a process that any knowledge worker can replicate. Check Adam's youtube channel:https://www.youtube.com/@ViableEdge

Nick Spisak, a 15-year software veteran turned AI entrepreneur, walks through the complete OpenClaw setup for non-technical users. You'll learn how to install your first instance, give it skills that read documentation for you, and troubleshoot any issue using natural language. Nick even gives away his "OpenClaw Prime" skill that turns any coding agent into an OpenClaw expert, plus a visual step-by-step diagram. • OpenClaw Prime Skill: https://corey-ganim.kit.com/f1f13dee60 • Excalidraw Setup Diagram: https://corey-ganim.kit.com/ab1cc7ab21 Key Takeaways: • Build a skill that reads the docs so you don't have to. Nick's "OpenClaw Prime" skill makes Claude Code or Codex an instant OpenClaw expert. • Troubleshooting works 100% of the time. Point your coding agent at your OpenClaw files, describe the issue in plain English, and let it fix itself. • Skills are portable across models. Write it once for Codex, ask AI to convert it for Claude Code or Gemini. • Spend 90% of your time in planning mode. Use Shift+Tab to enter plan mode and remove assumptions before execution. • Real business use case: AI receptionist. Set up OpenClaw on WhatsApp to respond to leads while you're on a job site. One extra $10K roofing lead pays for the whole system. • Telegram is the easiest platform to connect. Message the Bot Father, get your token, plug it into OpenClaw. • Customize your agent's personality via the Soul file. Make it concise, opinionated, and aligned with how you work. Timestamps: 00:00 - Introduction and what you'll learn 01:02 - Using Claude Cowork + Excalidraw for planning 03:46 - WhisperFlow: talk to your terminal with natural language 06:30 - OpenClaw Prime skill explained 08:41 - Why skills teach AI to "fish" (not just follow tutorials) 11:02 - Live troubleshooting demo: bringing Annie back online 13:44 - Claude Code vs Codex (skills are portable) 16:44 - Planning vs execution mode (the 90/10 rule) 19:21 - Real business use cases: AI receptionist for contractors 23:28 - 100% success rate troubleshooting (even with no code experience) 25:13 - Walkthrough of the Excalidraw setup diagram 27:16 - Setting up Telegram (easiest platform) 28:51 - Soul file and agent identity customization 30:26 - Wrap up and where to get free resources Links & Resources Mentioned: • OpenClaw Docs: https://docs.openclaw.ai • Claude Cowork: https://claude.ai • WhisperFlow: https://whisperflow.com • Ghost TTY (Terminal): https://ghostty.org Enjoyed this episode? → Subscribe and leave a review to help others discover the show → Join the Build with AI Community waitlist: https://return-my-time.kit.com/1bd2720397

Tom Nassr, co-founder and CEO of X-Ray, walks us through building a Zapier Agent from scratch in under 10 minutes. He demonstrates a practical use case: creating an AI agent that scans Gmail for specific emails and delivers a weekly summary to Slack. You'll learn the key difference between Zapier Agents and traditional Zaps, when to use each, and how to think about deterministic vs. non-deterministic automation. Check Tom's youtube channel: https://youtube.com/@xrayautomation Resources Mentioned: • Zapier: https://zapier.com/ • X-Ray Website: https://xray.tech/ • X-Ray Search Tool (free): https://search.xray.tech/

In this episode I put two of the hottest AI agent tools head-to-head: Perplexity Computer ($200/mo) vs. Claude Cowork ($20/mo). After running both through three identical real-world tasks, he reveals which tool delivers better outputs, which one goes above and beyond, and whether the 10x price difference is actually justified. Spoiler: the winner might surprise you. Grab the Google doc with the 3 test cases + full prompts here: https://return-my-time.kit.com/389d61df6a Tools Mentioned: • Perplexity Computer (Max plan): $200/mo - perplexity.ai • Claude Cowork (Pro plan): $20/mo - claude.ai • Zoho Invoice: zoho.com/invoice • Invoice Ninja: invoiceninja.com • Invoice Sherpa: invoicesherpa.com

Craig Hewitt, founder of the 7-figure SaaS Castos, breaks down how he uses Claude Code to run his entire content marketing operation. Despite not being a developer, Craig built his first Claude Code project in 45 minutes while waiting outside his son's basketball practice. In this episode, he walks through the exact system he uses, demonstrates live builds, and shares his free, open-source SEO Machine project that anyone can download and use today. YouTube: youtube.com/@thecraighewitt

Paul Noon ( aka The AI Professor) joins the show to give a full under-the-hood walkthrough of Google's NotebookLM. Paul's been using this tool daily in his business and personal life, and he breaks down exactly how it works, why it's different from ChatGPT or Gemini, and the real-world use cases that make it a must-have for any business owner. The best part? It's completely free. This episode was inspired by Paul's viral "Top 25 NotebookLM Tips" video on YouTube — this is the deeper dive. Check Paul’s YouTube channel: https://www.youtube.com/@TheProfessor-AI