Get your creative juices flowing with The Startup Ideas Podcast.
I go live and get my hands dirty with Claude Design, Anthropic's new design tool in research preview. Across roughly an hour, I run a real workflow end-to-end: pulling a product idea from Idea Browser, generating wireframes, iterating into visual designs, building a pitch deck, and attempting a 30-second video ad. I share my first reactions in real time and take feedback from the chat. By the end, I land on a clear verdict — best-in-class for wireframes and visuals, weaker for video — and give you a practical sense of where this tool fits in your workflow.
Timestamps
00:00 – Intro
00:50 – Claude Design walkthrough
03:48 – Picking a product idea from Idea Browser: Senior Brains
05:54 – Wire-framing Senior Brains
13:54 – Reacting to the generated wireframe
20:44 – Building a pitch deck for Senior Brains
30:39 – Reacting to a pitch deck
34:58 – Reacting to Hi-Fi wireframe
40:40 – Creating a 30-second animated video ad
48:58 – Reacting to animated video ad
58:10 – Final verdict and recommendations
Key Points
Claude Design's wireframing is the strongest capability I've seen in a design tool to date, especially the questionnaire that extrapolates like a product manager.
The pitch deck generation nails roughly 90% of the output with minimal input, which saves hours.
Visual design mockups come through clean and usable, ready to iterate with 30 minutes of back-and-forth.
Video generation lands at about a 5/10 — workable as a social post, weaker as a real commercial.
Start with wireframes first to conserve tokens and sharpen feature decisions before committing to high fidelity.
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/
In this episode I sit down with my friend Sirio, one of the most creative AI minds I know, to break down Seedance V2. Sirio walks us through the exact use cases, prompts, and tactics he's using to build on top of this model inside his platform Enhancor, covering multi-input generation, virtual try-ons, ad translation, AI influencers with lip sync, video extension, and 3D product template replacement. I wanted this to go beyond the "look how cool this is" tutorials and focus on how creators and founders can actually build businesses, run ads, and produce creative assets with it. By the end, you'll have a practical playbook for Seedance V2 and a clear view of where it fits alongside other models like Kling 3, Veo, and fine-tuned options.
Timestamp
00:00 – Intro
02:22 – Demo 1: Replacing Characters and Background in a Green Screen Scene
08:03 – Prompting Tactics and Optimize Prompts
09:45 – Demo 2: Virtual Try-On in Montreal (Minus 30 Degrees)
13:05 – Demo 3: Ad Translation and Character Replacement (Chinese to English)
16:02 – Demo 4: 3D Product Template with Brand Texture Swap
18:40 – Demo 5: Video Extension and Filling in the Middle
20:55 – Demo 6: AI Influencers and Prompting Realistic Emotion
29:31 – What Happens to Adobe Over the Next Five Years
Key Points
Seedance V2 is the first widely available video model to support true multi-input generation — up to two images, two videos, and an audio file combined in a single prompt.
Treat Seedance V2 as a video editor, not just a generator: character swap, background swap, text preservation, ad translation, and template population all work from natural-language prompts.
Seedance rewards highly specific prompts; I pair my own draft with Claude Opus 4.6 to optimize prompts for vision models.
Strong source reference images remain the single biggest quality lever — the model mimics taste from what you feed it.
For AI influencers and lip sync, describe muscle movements and emotional transitions rather than simply labeling an emotion like "sad" or "happy."
Seedance V2 is the current default for editing and generating video, yet other models (Kling 3 for cinematic feel, Enhancer V4 for talking-head realism) still win on specific use cases.
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 SIRIO ON SOCIAL
Enhancor AI: https://www.enhancor.ai
Instagram: https://www.instagram.com/heysirio/
Youtube: https://www.youtube.com/@SirioBerati
I sit down with Amir, who's back on the pod, and we walk through the full stack of taking a business idea from zero to a validated, A/B-tested landing page in a single session. I use Idea Browser's new MCP integration with Claude Code to pull project context, generate a lead magnet concept, design a landing page in Paper, and then wire up analytics and live experiments through HumbleLytics — all without writing a single line of front-end code manually. We cover the tools, the workflow, and why this stack creates massive arbitrage for marketers and builders right now.
Timestamps
00:00 – Intro and Episode Preview
02:30 – Building a Growth Strategy with Idea Browser
06:10 – Designing Landing Pages in Paper
08:38 – Refining Copy, Layout, and Components in Paper
20:06 – Deploying Landing Page and Adding HumbleLytics Analytics
28:38 – Running A/B Experiment on the Headline
32:44 – The Arbitrage Opportunity and Closing Thoughts
Links Mentioned:
Amir’s Agentic Marketing Skill: https://startup-ideas-pod.link/amir_marketing_skill
Key Points
Idea Browser now connects to Claude Code as an MCP, letting you pull project context, growth strategies, and skills directly into the terminal for building and iterating on business ideas.
Paper replaces the traditional Figma-to-developer handoff by letting you design, iterate, and refine landing pages visually — all connected to Claude Code so changes stay in sync.
HumbleLytics enables no-code A/B experiments that dynamically update page content without deploying new code, so you can test headlines, CTAs, and layouts in real time.
Storing performance context (A/B results, revenue data, growth metrics) back into Idea Browser compounds your results over time because every future decision is informed by past data.
This full stack — Idea Browser, Paper, Claude Code, HumbleLytics — creates a significant arbitrage opportunity right now because almost nobody is using it at this level.
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 AMIR ON SOCIAL
Humblytics: https://humblytics.com/?via=community
X/Twitter: https://x.com/amirmxt
Youtube: https://www.youtube.com/@amirmxt
I sit down with Ras Mic to break down how AI agents actually work and why most people are using them wrong. Ras Mic explains the mechanics of context windows, makes the case that agent md files are largely unnecessary, and shares his step-by-step methodology for building custom skills that make agents dramatically more productive. Whether you're coding with Claude Code or automating workflows with OpenClaw, this episode gives you the foundational knowledge to stop wasting tokens and start getting real results from your AI tools.
Timestamps
00:00 – Intro
00:42 – The Models Are Good Now
01:20 – How Context Windows Actually Work
04:55 – The Power of Skills
09:17 – How to create Skills
16:35 – Skill Maxxing
19:05 – What you need too build a project
20:40 – Recursively Building and Improving Skills
29:23 – Context Window Management and Token Efficiency
33:02 – Closing Thoughts
Key Points
The models (Opus 4.6, GPT 5.4) are exceptionally good now — the differentiator is the context and harness you build around them.
Agent md and claude md files get loaded into context on every single turn, burning tokens and degrading performance as the context window fills up. 95% of users can skip them entirely.
Skills use progressive disclosure: only the name and description sit in context until the agent determines it needs the full file, saving thousands of tokens per conversation.
The best way to create a skill is to walk through the workflow with the agent step by step, achieve a successful run, and then have the agent write the skill based on that real context.
Recursively refine skills by feeding failures back into the agent and having it update the skill file so the same mistake is avoided going forward.
Scale for productivity by starting with one agent and building up workflows before adding sub-agents — start simple, then expand.
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
I sit down with Flo, founder of Lindy, to get a live demo of their new product, Lindy Assistant, an AI executive assistant that lives in iMessage and works proactively across email, calendar, Slack, Notion, and 100-plus other tools. Flo walks me through a real day of his own Lindy usage, showing how it drafts email replies, prepares meeting briefs, updates CRMs, and handles calendar changes without being asked. We compare Lindy to OpenClaw and Claude's ecosystem, talk pricing, edge-case power users, and where Lindy goes over the next five years.
Try the ultimate AI assistant: https://startup-ideas-pod.link/lindy
Timestamps
00:00 – Intro
01:09 – What Lindy Assistant is and why Flo built it
02:27 – The daily morning brief
05:16 – Setup: two steps, two minutes, out of the box
05:53 – Get the most out of Lindy Assistant
09:42 – My three assistant use cases: research, scheduling, and sales leads
15:51 – Lindy vs. OpenClaw
17:57 – Lindy vs. Claude ecosystem
19:51 – Where Lindy goes over the next five years
23:42 – Integrations overview (100-plus tools)
24:42 – What Lindy does well and what it does not replace
26:52 – Pricing: starts at $49/month
27:15 – How power users are using Lindy
28:18 – Voice memos, incoming phone calls, and outbound calls
30:00 – How to use Lindy alongside a human executive assistant
Key Points
Lindy Assistant lives in iMessage, connects to email, calendar, Slack, Notion, and 100-plus other apps, and acts proactively without being prompted.
Setup takes two minutes: provide a phone number and connect a Google account, and Lindy ingests existing email and tool data immediately.
Lindy pre-drafts email replies, preps meeting briefs, updates CRMs after calls, flags billing issues, and reschedules dinners at closed restaurants — all without user initiation.
The voice and tone of the assistant took extensive prompt engineering; the lowercase, casual register is intentional and difficult to achieve with current models.
Lindy targets the "chief everything officer" — the overwhelmed founder or executive — rather than developers or power users who want a fully programmable agent.
Pricing starts at $49/month for 90-plus percent of users; heavy users can exceed that and are prompted to upgrade.
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 FLO ON SOCIAL
X/Twitter: https://x.com/Altimor
Lindy: https://www.lindy.ai
I go solo on this episode to walk through the full list of AI trends and opportunities keeping me up at night — literally. From the one-hour company stack to ambient businesses, vertical AI, the agent economy, and the real security threats I see coming, I cover what I believe is the most asymmetric window in startup history. I share the frameworks I use to think about what to build, what to avoid, and why acting now matters more than waiting for things to settle down.
Timestamps
00:10 – Intro
01:09 – 1) The One-Hour Company Stack
02:09 – 2) Old vs. new startup timeline
03:58 – 3) Ambient businesses and autonomous companies
05:18 – 4) The agent economy timeline
07:17 – 5) Agent hiring Agents
08:01 – 6) The Vertical Agent Map
09:39 – 7) Vertical AI vs. Vertical SaaS
10:53 – 8) Boring goldmine verticals
11:40 – 9) SaaS Pricing Evolution
13:26 – 10) Seat-Based vs Outcome-Based
14:51 – 11) The SaaS graveyard
16:04 – 12) The scarcity flip
17:03 – 13) The Premium Stack
18:21 – 14) The experience economy boom
18:59 – 15) Founder-agent fit
20:32 – 16) Ghost team org chart
21:56 – 17) The micro monopoly math
24:00 – 18) Agent attack surface
25:19 – 19) Agent Injection vs Phishing
26:34 – 20) Agent permission stack
27:37 – 21) The closing window
28:46 – 22) why this window is asymmetric
29:34 – 23) Building in public
30:50 – Final Thoughts
Key Points
I can build, launch, and get a first customer in under an hour using today's agent engineering tools and a pre-existing audience.
Vertical AI taps directly into labor P&L — it replaces headcount, not just software licenses — making the TAM 10x larger than vertical SaaS.
Ambient businesses running on near-zero daily human input are early but real; the arrow of progress points here.
The value shift I see coming: execution gets commoditized, judgment and physical presence become premium.
Agent injection is the new phishing — and I believe it scales faster and hits harder than any phishing attack did.
The 100 true fans model now applies in the AI age; with agents cutting costs, 100 paying customers at $500–$1,000 a month builds a real business.
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/
I break down the seven distribution strategies every vibe coder and builder needs to actually get customers. With 200,000 new projects launching daily on platforms like Lovable, the real bottleneck is distribution and I believe the wealthiest people over the next decade will be marketers, because code is now commoditized. I walk through each strategy with step-by-step instructions you can start this week, from MCP servers and programmatic SEO to acquiring newsletters and building AI repurposing engines.
Timestamps
00:00 – Intro
01:07 – The Great Flip: Distribution Over Engineering
03:08 – The Build-First Trap
04:18 – Strategy 1: MCP Servers as Your Sales Team
06:49 – Strategy 2: Programmatic SEO (10,000 Pages)
10:09 – Strategy 3: Free Tool as Top of Funnel
13:03 – Strategy 4: Answer Engine Optimization (AEO)
15:48 – Strategy 5: Viral Artifacts (Make Outputs Shareable)
18:56 – Strategy 6: Buy a Niche Newsletter
21:40 – Strategy 7: AI Content Repurposing Engine
25:13 – Final Takeaways
Key Points
Distribution is the new moat — AI can build the product, but it can't build your audience or brand.
Building an MCP server in 2026 is like building for mobile in 2010; early movers will own AI-native distribution channels.
Programmatic SEO can scale to 300,000 monthly visitors if you create 10,000 quality pages that each pull just 30 visits a month.
Free tools act as always-on marketing: you can vibe code one in a day, ship it by lunch, and it markets itself forever.
Answer engine optimization (AEO) is where SEO was in 2010 — Peter Levels saw AI referrals jump from 4% to 20% in one month.
You can buy a 10,000-subscriber niche newsletter for $5,000–$20,000 and inherit a direct channel to your exact audience on day one.
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/
I sit down with Dotta, the pseudonymous co-founder of Paperclip, the open-source agent orchestrator that exploded to 30,000 GitHub stars in under three weeks. We walk through a live demo where I pick a startup idea from my idea browser and we spin up a full AI-agent company in real time — hiring a CEO, founding engineer, QA agent, video editor, and content strategist inside Paperclip. Dotta shares practical tips on agent configuration, memory systems, skill installation, and the "Memento Man" mental model for keeping agents on track. The conversation covers everything from token spend management and agentic design patterns to the future of importable, shareable companies and the upcoming Maximizer Mode.
Skills to build your agent team: https://startup-ideas-pod.link/skill-suite
Timestamps:
00:00 Intro
02:32 What is Paperclip
04:21 Choosing a Startup Idea for the Demo
05:48 Setting Up your agents
07:51 Hiring Your First Agent and Creating a Plan
12:39 Agent Configuration and Persona Setup
17:08 Skills: Installing and Managing Agent Capabilities
21:02 How to Get Top-Quality Output from Agents
24:05 Token Spend Tracking and Subscription Usage
25:49 Agentic Design Patterns and QA Loops
29:05 Taste and Values: What AI Still Cannot Do
30:09 How Many Agents Run the Paperclip Project
32:32 Routines: Automating Recurring Agent Tasks
36:36 Who Is Using Paperclip Today
38:57 Shareable and Importable Companies
42:49 The Unproven Frontier: Do Agent Orgs Actually Work?
42:49 Maximizer Mode and What's Next
44:29 Did Dotta Expect It to Go This Viral?
Key Points
Paperclip is a bring-your-own-bot orchestrator: it works with Claude Code, Codex, OpenCode, and any model on OpenRouter, so you are not locked into a single provider.
AI agents are "Memento Man" — they wake up capable but with zero memory, so you need heartbeat checklists, persona prompts, and written context to keep them effective.
The biggest lever for quality output is encoding your own taste and values into agent skills and brand guides, because AI can do everything except know what you actually want.
Agentic design patterns like engineer-to-QA review loops matter more than one-shotting an entire startup; structure prevents compounding errors.
Paperclip tracks every token spent and every task completed, solving the problem of running dozens of agent windows with zero accountability.
Importable, shareable company templates (like Gary Tan's G-Stack or a full game studio) point toward a future where you "aqua-hire" proven agent teams instead of building from scratch.
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 DOTTA ON SOCIAL
X/Twitter: https://x.com/dotta
Paperclip: https://paperclip.ing
Github: https://github.com/cryppadotta
I break down Firecrawl and it solves AI’s biggest blind spot, access to clean web data. I walk through the full AI agent stack every builder needs, explain why this is the "AWS moment" for web data, and share a dozen startup ideas you can build this week using Firecrawl for scraping, enrichment, and automation. Whether you want to launch a niche SaaS, a lead gen service, or a data-as-a-service business, this episode gives you the frameworks and the specifics to get started.
Shoutout Firecrawl - Turn websites into LLM-ready data: https://startup-ideas-pod.link/firecrawl
Timestamps
00:00 – Intro
02:14 – Why this matters now
07:40 – What is Firecrawl
11:20 – How does Firecrawl work
12:57 – The Agent Stack
14:35 – 7 Startup Ideas
24:01 – Firecrawl Hired an AI Agent as an Employee
26:24 – Final Thoughts
Key Points
AI models are only as good as the data they can access — clean, structured web data is the new critical infrastructure.
Firecrawl replaces thousands of lines of custom scraping code with a single API call that returns clean markdown, structured JSON, and screenshots.
The biggest opportunity is taking horizontal SaaS categories (SEO tools, job boards, price trackers) and building hyper-niche versions using Firecrawl at a fraction of the cost.
I think about the AI agent stack in five layers: agent harness, search layer, web data layer, ops brain, and outbound/audience stack.
The real business model is selling the data output, not the tool — you can charge $200 to $5,000 per month per client with margins above 95%.
Vertical software always wins because people pay for specificity; Constellation Software built a ~$75 billion company on this principle.
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/
I sit down with Moritz Kremb, an OpenClaw power user and agency builder based in Berlin, to break down how to actually make OpenClaw useful. Moritz walks through a 10-step optimization guide covering everything from troubleshooting and memory management to model selection and security basics. He then demos two real systems he built with OpenClaw: a full short-form video content pipeline and a conversational CRM. This episode is for anyone who tried OpenClaw, hit a wall, and wants a clear path to turning it into a superhuman digital employee.
Timestamps
00:00 – Intro and episode promise
02:17 – What is OpenClaw
03:17 – OpenClaw vs. ChatGPT vs. Claude Code
07:43 – Where Claude Cowork and Dispatch fit in
09:47 – Why choose OpenClaw over Cowork
11:03 – Step 1: Setting up OpenClaw
14:46 – Step 2: Personalize your workspace files
18:04 – Step 3: Fix and optimize memory
22:43 – Step 4: Choose the right model (OAuth method)
25:56 – Anthropic ban and model provider gray areas
27:33 – Step 5: Organize Telegram groups and topics
30:19 – Step 6: Understand the three browser modes
35:18 – Step 7: Skills — built-in, marketplace, and custom
39:03 – Step 8: Optimize the heartbeat file
42:00 – Step 9: Security basics and prompt injection
48:08 – Step 10: Least access principle and agent-owned accounts
49:52 – Use case 1: No AI Slop content system
58:37 – Use case 2: Conversational CRM
01:01:15 – Final thoughts on the future of personal agents
01:02:55 – Jensen Huang's take: OpenClaw as the new computer
Key Points
Upload the OpenClaw documentation into a Claude project to create a dedicated troubleshooting baseline — it solves roughly 99% of setup issues.
Use the OAuth method (your existing $20 ChatGPT or Anthropic subscription) to avoid expensive API costs, and always configure backup models.
Memory problems are almost always caused by memory never being saved in the first place; add an auto-save instruction to the heartbeat file so it logs every 30 minutes.
Organize your OpenClaw conversations into separate Telegram groups and topics with group-specific system prompts to avoid context bleed.
Stronger models are meaningfully more resistant to prompt injection; pair that with least-access principles and agent-owned accounts for a solid security posture.
Custom skills are the path to real automation — whenever you do something repeatedly, tell your OpenClaw to turn it into a skill.
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 MORITZ ON SOCIAL
Youtube: https://www.youtube.com/@promptwarrior/videos
Instagram: https://www.youtube.com/@promptwarrior/
I sit down with Remy Gaskell to break down how anyone can build AI agents to run entire departments of their business. Remy walks through the core concepts: agent loops, context files, memory, MCP tool connections, and skills. We put everything together by building a fully functional executive assistant live on screen. This is a beginner-friendly crash course that covers Claude Code, Codex, Cowork, Antigravity, Manus, and OpenClaw, showing that once you understand how to "drive," you can jump into any agent platform. By the end, listeners know exactly how to set up markdown-based context files, connect their everyday tools, and create reusable skills that compound over weeks and months.
Timestamps
00:00 – Intro
01:35 – Agents vs Chat
03:22 – The Agent Loop
05:46 – How Agents work
06:39 – Demoing Agents (Claude Code, Codex, Antigravity)
08:52 – Security and Agent Permissions
10:43 – Comparing Results Across Three Platforms
13:57 – Startup Idea: Cold Email Website Offer
14:50 – Folder Structure and Department-Based Agents
15:52 – Onboarding an Agent Like a Real Employee
17:05 – Voice-to-Text With Monologue and WhisperFlow
18:04 – Chat Memory vs. Agent Memory
19:34 – Building the agents md
22:20 – Context Engineering Over Prompt Engineering
24:29 – How Memory Compounds and Reduces Errors
30:27 – How Big Can memory md Get?
31:43 – Connecting Tools via MCP (Model Context Protocol)
34:49 – Working in Claude Code for High-Value Tasks
37:09 – Why the Real Value Is in Stacking, Not Summarizing
40:04 – What Are Skills? (SOPs for AI)
43:08 – Creating Skills
48:36 – Real-World Example: Ads Analyst Skill: 4-Hour Process in Minutes
50:37 – Chaining Skills together
52:01 – Real-World Example: Automated Car Search
53:34 – OpenClaw and Migrating Agents to More Autonomous Platforms
55:19 – Which Platform Should Beginners Start With?
56:28 – Global vs. Project-Level Skills, Context, and MCPs
Key Points
Agent platforms (Claude Code, Codex, Cowork, Antigravity, Manus, OpenClaw) are all running the same observe-think-act loop under the hood — learning one means you can use any of them.
The shift from chat to agents requires moving from prompt engineering to context engineering: load the agent with rich context so simple prompts produce excellent results.
A memory md file creates a self-improving loop where the agent learns preferences across sessions and makes fewer errors over time.
MCP (Model Context Protocol), built by Anthropic, acts as a universal translator between your agent and every tool it needs — Gmail, Calendar, Stripe, Notion, and more.
Skills are reusable SOPs packaged as markdown files; once you explain a process once, you can invoke it repeatedly, and they compound as you add three to five per week.
Scheduled tasks turn skills into automated workflows — morning briefs, car searches, ad library analyses — that run on a cron without any manual trigger.
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 REMY ON SOCIAL
Youtube: https://www.youtube.com/@aiwithremy
Instagram: https://www.instagram.com/aiwithremy/