AI marketing Masterclass: From beginner to expert in 60 minutes

I sit down with James Dickerson, a growth marketer, Claude Code power user, and the mind behind The Boring Marketer, to watch him build an entire marketing system live from the terminal. James walks me through his full workflow: deep research with the Perplexity MCP, positioning angle discovery, direct response copywriting, landing page creation, lead magnet design, ad creative generation with Remotion, and traffic strategy — all inside Claude Code using stacked skills and MCPs. By the end, we have a conversion-ready funnel for a fictional AI marketing agency serving boring local businesses, and James shares the free playbook he created from a two-hour recorded session so listeners can replicate the process themselves. Timestamps 00:00 – Intro and Camera Setup Chat 02:57 – Episode Preview: Building a Vibe Marketing System 06:33 – Perplexity MCP for Market Research 08:13 – Live Demo: Researching an AI Marketing Agency Niche 09:48 – Positioning Angles Skill 11:34 – Direct Response Copywriting Skill 15:43 – Playwright MCP for Competitive Intelligence 17:37 – Keeping Your MCP Stack Simple (Perplexity, Firecrawl, Playwright) 20:59 – Anthropic's Front End Design Skill 25:51 – Remotion: Creating Video Ads from the Terminal 28:47 – Landing Page Review: "Boring Money" Agency 30:43 – Orchestrator Skill: Deciding What to Do Next 34:10 – Lead Magnet Skill 34:10 – Are Skills Underrated 39:08 – Claude Code Costs: $200/Month Max Subscription 42:03 – Live Lead Magnet Review 43:28 – Keyword Research and Traffic Strategy Skills 45:23 – The Evolution of Vibe Marketing 47:11 – Remotion Setup and Ad Creation Demo 54:47 – Final Ad and SEO Page Review 57:25 – Final Thoughts Links Mentioned: Vibe Marketing Playbook: https://startup-ideas-pod.link/vibe_marketing_playbook Vibe Marketing Skills: https://startup-ideas-pod.link/Vibe_marketing_skills Key Points Spending an hour on upfront research with the Perplexity MCP produces dramatically better marketing outputs than jumping straight into prompting. Skills are instruction manuals for your AI agent — the expert perspective you build into them (the last 10–20%) is what separates great output from generic AI slop. You can build a complete marketing funnel — landing page, lead magnet, ad creative, SEO content, and traffic strategy — in a single Claude Code session. Remotion lets you create programmatic video ads directly from the terminal at zero cost, in multiple formats, with custom branding. An orchestrator skill can guide you through what to do next, removing the "I have a landing page, now what?" paralysis. The same Claude Code environment where you build products can also ship your entire marketing system — research, copy, design, and deployment in one place. 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 JAMES ON SOCIAL X/Twitter: https://x.com/boringmarketer  LinkedIn: https://www.linkedin.com/in/jadickerson/

I sit down with Morgan Linton, Cofounder/CTO of Bold Metrics, to break down the same-day release of Claude Opus 4.6 and GPT-5.3 Codex. We walk through exactly how to set up Opus 4.6 in Claude Code, explore the philosophical split between autonomous agent teams and interactive pair-programming, and then put both models to the test by having each one build a Polymarket competitor from scratch, live and unscripted. By the end, you'll know how to configure each model, when to reach for one over the other, and what happened when we let them race head-to-head. Timestamps 00:00 – Intro 03:26 – Setting Up Opus 4.6 in Claude Code 05:16 – Enabling Agent Teams 08:32 – The Philosophical Divergence between Codex and Opus 11:11 – Core Feature Comparison (Context Window, Benchmarks, Agentic Behavior) 15:27 – Live Demo Setup: Polymarket Build Prompt Design 18:26 – Race Begins 21:02 – Best Model for Vibe Coders 22:12 – Codex Finishes in Under 4 Minutes 26:38 – Opus Agents Still Running, Token Usage Climbing 31:41 – Testing and Reviewing the Codex Build 40:25 – Opus Build Completes, First Look at Results 42:47 – Opus Final Build Reveal 44:22 – Side-by-Side Comparison: Opus Takes This Round 45:40 – Final Takeaways and Recommendations Key Points Opus 4.6 and GPT-5.3 Codex dropped within 18 minutes of each other and represent two fundamentally different engineering philosophies — autonomous agents vs. interactive collaboration. To use Opus 4.6 properly, you must update Claude Code to version 2.1.32+, set the model in settings.json, and explicitly enable the experimental Agent Teams feature. Opus 4.6's standout feature is multi-agent orchestration: you can spin up parallel agents for research, architecture, UX, and testing — all working simultaneously. GPT-5.3 Codex's standout feature is mid-task steering: you can interrupt, redirect, and course-correct the model while it's actively building. In the live head-to-head, Codex finished a Polymarket competitor in under 4 minutes; Opus took significantly longer but produced a more polished UI, richer feature set, and 96 tests vs. Codex's 10. Agent teams multiply token usage substantially — a single Opus build can consume 150,000–250,000 tokens across all agents. 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/ Morgan Linton X/Twitter: https://x.com/morganlinton Bold Metrics: https://boldmetrics.com Personal Website: https://linton.ai

I sit down with Matt Van Horn, creator of the "Last 30 Days" skill for Claude Code, as he demonstrates how this tool turns anyone into a real-time research expert. By pulling trending data from X, Reddit, and the web, Last 30 Days supercharges Claude Code prompts with current intelligence. Matt walks through live demos, from discovering popular rap songs to generating cold emails to building a Moltbot competitor, showing how non-engineers can ship products using AI tools with almost no coding background. Timestamps 00:00 – Intro 01:39 – What Is "Last 30 Days" 03:29 – Live Demo: Most Popular Rap Songs 04:47 – Cold Email Frameworks Demo 07:04 – Growing an X Following Using Recent Data 07:49 – Researching Moltbot to Build a Competitor 08:26 – Best Practices for Last 30 days 09:26 – Growing an X Following Using Recent Data Results 11:17 – Best Practices for Webdesign Research 13:44 – Building an Enterprise Moltbot Clone Live 17:43 – Generating Figma Prompts and Nano Banana Images 21:54 – Advice for Non-Engineers Getting Started with Claude Code Links Mentioned: Last 30 Days Skill: https://startup-ideas-pod.link/last30days Key Points Last 30 Days searches X, Reddit, and the web for content from the past month, creating highly optimized prompts for Claude Code. The tool requires Claude Code access, an OpenAI API key (for Reddit data), and an XAI key (for X/Twitter access). Matt demonstrates using minimal prompts to generate cold email frameworks, research trending topics, and kickstart new product builds. Compound Engineering serves as a planning tool to turn research into structured project roadmaps. Non-engineers can ship functional products by combining Claude Code with ChatGPT for troubleshooting errors via screenshots. 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/ Matt Van Horn X/Twitter: https://x.com/mvanhorn

I sit down with Kevin Rose for a live screen share where he walks me through “Nylon,” a personal Techmeme-style news engine he vibe-coded to track AI and tech stories. He breaks down how he pulls from RSS, enriches articles with tools like iFramely, Firecrawl, and Gemini, then generates TLDRs and vector embeddings to cluster stories with real nuance. We dig into his “gravity engine,” an editorial scoring system that ranks stories by impact, novelty, and builder relevance. The bigger theme is simple: with today’s models and workflows, a solo builder can ship wild, high-leverage software fast, then refine by cutting features down to the few that matter. Timestamps: 00:00 – Intro And What Kevin Plans To Demo 03:10 – Techmeme Breakdown And How Signal Gets Ranked 06:44 – RSS Sources, Ingestion, And The Article Pipeline 11:23 – Winner Selection: RSS vs iFramely vs Firecrawl vs Gemini 13:01 – Why iFramely And Firecrawl, Explained 16:37 – TLDRs, Vector Embeddings, And Why They Beat Keyword Search 19:49 – Task Orchestration With trigger.dev And Retries 24:58 – Clusters: Expanding With Search APIs And Discovery 27:07 – The Gravity Engine: Editorial Scoring Rubric 31:31 – Product Management: Gut, Iteration, And Cutting Features 34:53 – Synthetic Audiences And Personal Software 37:03 – What “Success” Looks Like 43:52 – Retention Mechanics And The Idea Browser Example 47:19 – “Blurred Presence” Blog Project From A 12-Year-Old Idea 50:34 – This the best time to build 51:55 – How To Work With Kevin, DIGG Reboot, And VC Today Keypoints I watch Kevin’s end-to-end pipeline for turning messy RSS links into clean, enriched, clustered stories. Kevin uses a “winner” judge to pick the best source of truth per field (summary, main content, metadata). Vector embeddings plus clustering unlock meaning-level grouping that keyword search misses. trigger.dev gives durable background jobs, retries, and observability for a solo builder workflow. His “gravity engine” acts like an editorial layer that prioritizes novelty, impact, and builder relevance. 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/ Kevin Rose: x: https://x.com/kevinrose personal website: https://www.kevinrose.com/about Youtube: https://www.youtube.com/@KevinRose

I sit down with Kitze to unpack how he uses Clawdbot as a personal OS that runs across Discord, Telegram, and other chat surfaces. We walk through his one-gateway setup, persona-based bots, and the way he structures channels and threads to manage customers, home logistics, and engineering work. We also dig into the self-learning angle: giving an agent shell and network access so it can discover devices, build dashboards, and automate workflows end to end. We close with a lightning round of concrete examples you can adapt across your own life and business. Timestamps 00:00 – Intro 01:42 – The Personal OS Idea 04:20 – Persona Design for Clawdbot 06:00 – Discord As The Control Center 08:23 – Self-Learning Through Shell And Network Access 09:23 – Discord Threads And Agent Workflows 10:13 – Platform Choices: Telegram, Discord, Slack 11:47 – Email Automation, Security, And Model Selection 15:07 – How Agents Change Work 18:00 – Lightning Round of Clawdbot use cases 27:09 – Spellbook: Variable-Driven Prompt Templates 29:15 – Closing Thoughts Key Points I treat Clawdbot like a gateway that routes the same core agent into many persona shells for distinct jobs I keep work organized via Discord sections, channels, and threads so agent output stays searchable I lean on shell and network access to let the agent discover devices and ship automations that span apps, NAS, and smart home I use stronger models for high-trust surfaces like email and credentials, and I scope access gradually I prototype interfaces that turn prompts into parameterized forms so workflows stay reusable and fast 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 KITZE ON SOCIAL X/Twitter: https://x.com/thekitze Tinkerer Club: https://tinkerer.club Personal Website:  https://www.kitze.io

I sit down with Alex Finn to break down how he sets up Moltbot (formally Clawdbot) as a proactive AI employee he treats like a teammate named Henry. We walk through the core workflow: Henry sends a daily morning brief, researches while Alex sleeps, and ships work as pull requests for review. Alex explains the setup that makes this work; feeding the bot deep personal and business context, then setting clear expectations for proactive behavior. We cover model strategy (Opus as “brain,” Codex as “muscle”), a “Mission Control” task tracker Henry built, hardware options, and the security mindset around prompt injection and account access. Timestamps 00:00 – Intro 02:08 – Clawdbot Overview 03:33 – The Morning Brief Workflow 05:01 - Proactive Builds: Trends → Features → Pull Requests 07:27 – The Setup: Context + Expectations For Proactivity 09:38 – The Onboarding Prompt Alex Uses 12:05 – Hunting “Unknown Unknowns” For Real Leverage 12:43 – Using the right Models for cost control 14:18 – Mission Control: A Kanban Tracker Henry Built 17:16 – The future of Human and AI workflow 22:01 – Hardware And Hosting: Cloud vs Local (Mac Mini/Studio) 25:47 – The Productivity Framework 27:10 – The Possible Evolution of Clawdbot 28:53 – Security and Privacy Concerns 33:38 – Closing Thoughts: Tinkering, Opportunity, And Next Steps Key Points I get the most leverage when I treat the agent like a proactive teammate with clear expectations and rich context. Henry delivers compounding value by shipping work for review (pull requests) based on trend monitoring and conversation memory. I separate “brain” and “muscle” by delegating heavy coding to Codex while using Opus for reasoning and direction. I track autonomous work with a dedicated “Mission Control” board so progress stays visible over time. I keep risk contained by controlling environment and account access, especially around email and prompt injection. 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/

I sit down with Furqan Rydhan, a founding team member of Applovin and cofounder Founders Inc, as he walks me through Nebula, a Slack-like workspace where every channel holds an agent that can execute real work across the tools teams already use. We watch Nebula create and edit a Google Slides deck end-to-end, including generating an image and handling failures by retrying until it lands. Furqan shows how Nebula turns one-off work into repeatable “recipes” with scheduled triggers, like adding slides daily or publishing blog posts multiple times per day. We also talk about what “business-in-a-box” looks like in the AI era; where direction, taste, and quality loops become the edge as automation gets widely available. Timestamps: 00:00 – Intro 01:51 –Building useful agents for real work 03:34 – Nebula: a Slack-like agent workspace 05:04 – Demo: Nebula creating a Deck with Google Slides 13:25 – The “business in a box” content dream (newsletters, affiliates, ads) 14:39 – Demo: Automate Blog Posting 15:52 – What stays valuable when everyone automates 21:23 – Agent workforce and Building quality loops 25:38 – Services and agencies: delivering work with fewer humans 28:53 – Final Thoughts Key Points I watch Nebula run like “cloud code for everything else,” automating real work across tools and workflows. Agents turn one-time actions into repeatable systems via triggers and schedules. The interface mirrors Slack because work already lives in channels, threads, and context. Quality becomes the differentiator: critics, scoring, and iteration loops upgrade outputs over time. Service businesses and agencies scale faster when agents handle production-heavy tasks 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 FURQAN ON SOCIAL Furqan's X: https://x.com/FurqanR Fuqan’s personal website: https://furqan.com Nebula: https://www.nebula.gg

In this episode, I sit down with Boris, the creator of Claude Code and one of the key builders behind Claude Cowork, to unpack what Cowork actually unlocks and how people use it in the real world. He walks through a hands-on demo where Cowork organizes files, extracts receipt data, builds a clean spreadsheet, and even drives the browser to create and share a Google Sheet. We go deep on how “agentic” work feels different when the model takes actions across your computer, your browser, and your tools. Then I shift into Boris’s viral workflow for Claude Code: parallel sessions, plan-first execution, Claude.md as a compounding team memory, and verification loops that dramatically improve output quality. Timestamps: 00:00 – Intro 03:26 – Cowork Overview 05:51 – Demo: Folder Access + Renaming Receipts 08:23 – Demo: Turning Receipts Into A Spreadsheet 10:52 – Demo: Google Sheets + Chrome Control 15:52 – Demo: Emailing The Sheet + Parallel Tasking 22:07 – Best way to start/use with Cowork 24:22 – Where will AI and Agents Go Next 28:44 – Boris’s Claude Code Setup 41:12 – The “Claude” Pronunciation Discussion Key Points I use Cowork as a “doer,” not a chat: it touches files, browsers, and tools directly. I think about productivity as parallelism: multiple tasks running while I steer outcomes. I treat Claude.md as compounding memory: every mistake becomes a durable rule for the team. I run plan-first workflows: once the plan is solid, execution gets dramatically cleaner. I give Claude a way to verify output (browser/tests): verification drives quality. 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 BORIS ON SOCIAL X/Twitter: https://x.com/bcherny

In this episode, I sit down with Professor Ras Mic for a beginner-friendly crash course on using Claude Code (and AI coding agents in general) without feeling overwhelmed by the terminal. We break down why your output is only as good as your inputs and how thinking in features + tests turns “vague app ideas” into real, shippable products. Was walks me through a better planning workflow using Claude Code’s Ask User Question Tool, which forces clarity on UI/UX decisions, trade-offs, and technical constraints before you build. We also talk about when not to use “Ralph” automation, why context windows matter, and how taste + audacity are the real differentiators in 2026 software. Timestamps 00:00 – Intro 01:22 – Claude Code Best Practices 05:31 – Claude Code Plan Mode 09:30 – The Ask User Question Tool 14:52 – Don’t start with Ralph automation (get reps first) 16:36 – What are “Ralph loops” and why plans and documentation matter most 18:41 – Ras’s Ralph setup: progress tracking + tests + linting 23:48 – Tips & tricks: don’t obsess over MCP/skills/plugins 27:44 – Scroll-stopping software wins Key Points Your results improve fast when you treat AI agents like junior engineers: clear inputs → clean outputs. The biggest unlock is planning in features + tests, not broad product descriptions. Claude Code’s Ask User Question Tool forces real clarity on workflow, UI/UX, costs, and technical decisions. If you haven’t shipped anything, don’t hide behind automation—build manually before using “Ralph.” Context management matters: long sessions can degrade quality, so restart earlier than you think. Numbered Section Summaries The Real Reason People Get “AI Slop” I frame the episode around a simple idea: if you feed agents sloppy instructions, you’ll get sloppy output. Ras explains that models are now good enough that the failure mode is usually unclear inputs, not model quality. How To Think Like A Product Builder (Features First): Ras pushes a practical mindset: don’t describe “the product,” describe the features that make the product real. If you can list the core features clearly, you can actually direct an agent to build them correctly. The Missing Piece: Tests Between Features: We talk about the shift from “generate code” to “build something serious.” The move is writing and running tests after each feature, so you don’t stack feature two on top of a broken feature one. Why Default Planning Mode Isn’t Enough: Ras shows the standard flow: open plan mode, ask Claude to write a PRD, and get a basic roadmap. The issue is it leaves too many assumptions—especially around UI/UX and workflow details. The Ask User Question Tool (The Planning Upgrade): This is the big unlock. Ras demonstrates how the Ask User Question Tool interrogates you with increasingly specific questions (workflow, cost handling, database/hosting, UI style, storage, etc.) so the plan becomes dramatically more precise. Spend Time Upfront Or Pay For It Later: We connect the dots: better planning reduces back-and-forth, reduces token burn, and prevents “I built the app but it’s not what I wanted.” The interview-style planning forces trade-offs early instead of late. Don’t Use Ralph Until You’ve Built Without It: Ras makes a strong case for reps: if you can’t ship something end-to-end yet, automation won’t save you—it’ll just move faster in the wrong direction. Build feature-by-feature manually first, then graduate to loops. Practical Tips: Context Discipline + Taste Wins: Ras shares a few operational habits: don’t obsess over tools like MCP/plugins, keep context usage under control, and restart sessions before quality degrades. We wrap on a bigger point: in 2026, “audacity + taste” is what makes software stand out. 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 MIC ON SOCIAL X/Twitter: https://x.com/Rasmic Youtube: https://www.youtube.com/@rasmic

Today I’m joined by Samuel Thompson, an internet capitalist who’s launched 100 companies in 10 years, and he walks me through a live, end-to-end build of an info product using AI. We break down how he goes from idea → AI-written book → mockups → Shopify product page → ad creatives in a ridiculously short amount of time. The big takeaway is that this isn’t just “info products,” it’s a repeatable launch system you can apply to e-comm, SaaS, mobile apps, and pretty much anything where customer acquisition matters. We also get into the real game: CAC vs LTV, conversion rates, and how to build what Sam calls a “rigged slot machine” you can scale. Timestamps 00:00 – Intro 02:32 – Choosing the offer 05:36 - Writing ebook with ChatGPT (outline → chapters → upgrade quality) 07:30 – Mockups with Canva & Envato Elements 10:25 – Shopify themes that convert (Solo Drop + Elixir) 12:05 – Finding products to sell 16:28 - Building the Shopify Store 21:16 – Using ChatGPT to generate product-page copy fast 24:13 – What “good” conversion rates look like (3–5% target range) 28:51 – Bonus gifts strategy = perceived value + conversion lift 33:26 – HeyGen for AI photo/video ad assets + voice clone insight 35:37 – Canva static ads + high-performing angles 38:57 – Big picture: one person can build a “real business” with AI Key Points Sam’s launch loop is offer → AI asset creation → Shopify page → Meta ads → iterate on math Start with low-friction products (ebook/info) to validate customer acquisition fast The real framework is CAC vs AOV vs conversion rate, not “brand vibes” 3–5% conversion rate is a strong target on a direct-response product page Use bonus gifts to increase perceived value and lift conversion Static ads + strong angles can outperform everything when the message hits 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 SAMUEL ON SOCIAL: X/Twitter: https://x.com/samuelthompson