How I Use Obsidian + Claude Code to Run My Life
How I Use Obsidian + Claude Code to Run My Life
I sit down with my dear friend Vin (Internet Vin) for a deep, hands-on walkthrough of how he uses Obsidian and Claude Code together as a thinking partner, idea generator, and personal operating system. Vin demonstrates live how Claude Code can read, reference, and surface patterns across an entire Obsidian vault of interlinked markdown files — turning years of personal notes into actionable insights, project ideas, and even custom commands. This episode covers everything from the basic setup to advanced workflows like tracing how ideas evolve over time, generating contextual startup ideas, and delegating tasks to autonomous agents. If you are serious about getting the most out of LLMs, this is the episode that shows you how your own writing becomes the fuel.
Link to Vin's skills and my notes: https://startup-ideas-pod.link/obsidian-commands
Timestamps
00:00 – Intro
02:10 – What Is Claude Code?
06:45 – What Is Obsidian?
10:28 – Obsidian CLI: Giving Claude Code Access to Your Vault
14:53 – Thinking Tools: Ghost, Challenge, Emerge, Drift, Ideas, Trace
22:51 – The Role of Reflection in Building a Powerful Vault
25:15 – How This Relates to OpenClaw (Autonomous Agents)
29:13 – Live Demo: /Connect — Bridging Two Domains
31:25 – Meeting Notes & External Info
33:23 – Why Vin Keeps a Strict Separation: Human-Written vs. Agent-Written
35:42 – How Claude Code uses Obsidian
41:46 – Live Demo: /Ideas — Generating Actionable Ideas from Your Vault
47:10 – The /Graduate Command
50:29 – Why Obsidian Is the Missing Link for AI Companies
54:53 – The Alpha: Why 99.99% of People Won't Do This
57:38 – Closing Thoughts & Where to Follow Vin
Key Points
* Claude Code is a command-line agent that can control your computer through natural language — and its power multiplies when you feed it rich, persistent context files instead of re-explaining projects every session.
* Obsidian is uniquely valuable because it sits on top of interlinked markdown files; the new Obsidian CLI lets Claude Code see both the files and the relationships between them.
* Vin built custom slash commands (/trace, /connect, /ideas, /ghost, /drift, /challenge) that let him use Claude Code as a thinking partner — surfacing latent patterns, contradictions, and ideas he would never see on his own.
* Writing and daily reflection are the engine of the entire system: the more you write, the more context the agent has, and the more it can do for you.
* Markdown files are the real oxygen of LLMs; if you are serious about building a personal OS with AI, a centralized note-taking tool built on markdown is foundational
Numbered Section Summaries
1. Obsidian as an Interlinked Knowledge Base
Vin introduces Obsidian as an interface that sits on top of a folder of markdown files, with the critical addition of backlinks — connections between files that mirror how the brain forms associations. He walks through his own vault, showing how daily notes, project files, and notes on people all link together in a visual graph.
2. Obsidian CLI: The Bridge Between Your Vault and Claude Code
The real breakthrough comes from Obsidian CLI, which gives Claude Code access to both the files and their interrelationships. This means the agent can see that a note about filmmaking is connected to a note about world building, and can surface cross-domain patterns you have been circling for months without realizing it.
3. Custom Slash Commands as Thinking Tools
Vin demonstrates a suite of custom commands he built: /context loads his full life and work state; /today pulls calendar, tasks, and daily notes into a prioritized plan; /trace tracks how an idea has evolved over time; /connect bridges two domains using the vault's link graph; /ghost answers a question the way Vin would; /challenge pressure-tests his current beliefs. These turn Claude Code from a generic assistant into a deeply personalized thinking partner.
4. Markdown Files as the Foundation of the AI Era
I make the case that if you are serious about using LLMs to their full potential, a centralized markdown-based note-taking system is table stakes. Writing and reflection are the raw material; files are perfect memory where human recall is flawed; and the 99.99% of people who skip this step are leaving massive value on the table.
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 VIN ON SOCIAL
X: https://x.com/internetvin
Youtube: https://www.youtube.com/@otherstuffpod
Personal Website: https://internetvin.com/Index
Making $$$ with OpenClaw
I sit down with Nick Vasilescu, founder of Orgo, to break down exactly how people are turning OpenClaw — the open-source computer use agent — into a real revenue stream. Nick walks me through live demos of deploying OpenClaw for business clients, shows how sub-agents and parallelization multiply output, and shares his design-thinking framework for identifying and automating high-value workflows. We even build a TikTok trend-hunting agent from scratch during the episode to prove how fast you can go from idea to working prototype.
Timestamps
00:00 – Intro
02:50 – Getting Set Up with OpenClaw
05:02 – Finding the Wedge: Automating Real Business Outcomes
07:39 – The Upwork Hack: Finding Paid Automation Jobs
09:41 – Andreessen Horowitz on Computer Use Agents
11:01 – Setting Up a Client Workspace in Minutes
12:41 – Design Thinking: Mapping Value vs. Effort
15:23 – Using OpenClaw to Prioritize Automations
17:57 – Building Automation Pipelines with Claude Code
19:33 – Sub-Agents vs. Tasks vs. Skills
23:22 – Automation Possibilities are huge
24:54 – Live Build: TikTok Trend Hunter from Idea Browser
32:09 – Start with an MVP Skill, Then Iterate
32:41 – Architecture of the TikTok Agent Script
36:59 – The Arbitrage Opportunity: Most Businesses Still Need Help
40:30 – Agents Are the New SaaS
42:42 – Demoing TikTok Trend Hunter
44:11 – Building Assets & the Abundance AI Will Bring
47:58 – Closing Advice: Get Your Hands Dirty
Links Mentioned:
Orgo: https://startup-ideas-pod.link/orgo
Key Points
* OpenClaw is more than a personal assistant — it is a deployable business tool that can automate end-to-end workflows for paying clients.
* The fastest path to revenue is finding automation jobs on Upwork (RPA, desktop automation, workflow building) and fulfilling them with OpenClaw and Claude Code.
* Sub-agents allow your main OpenClaw instance to delegate specialized tasks, keeping the orchestrator free and multiplying throughput through parallelization.
* A design-thinking approach — mapping automation opportunities by value vs. effort — is essential before building anything.
* Verticalizing computer use agents for a specific industry (manufacturing, real estate, distributorships) is the major startup opportunity Andreessen Horowitz is calling out.
* Always start by building a lightweight MVP skill, test it, debug, and iterate before scaling.
Numbered Section Summaries
1) OpenClaw Setup and Deployment Options
Nick demonstrates how easy it is to install OpenClaw on a virtual machine using Orgo, though he makes clear you can use Manus, Kimi, a Mac Mini, or any setup you prefer. He spins up a workspace for me in under a minute — just a curl command in the terminal and it is ready. The point: the barrier to entry is nearly zero.
2) The Wedge: Finding Business Automation Opportunities
The viral demos on Twitter are fun but toyish. The real money is in identifying a specific workflow inside a business — like downloading product data from a legacy platform and uploading it into a Zoho CRM — and automating that end to end. Nick calls this the "wedge" and it is the foundation of the entire business model.
3) Sub-Agents and Parallelization
OpenClaw can spawn up to eight sub-agents, each with its own computer. Nick shows two parallelization strategies: splitting one task across multiple agents, or running the same task across multiple instances for volume. He spawned sub-agents to scrape Upwork jobs, build demo proposals, and pick the best one — all automatically.
4) The Upwork Hack
If you have zero clients, Upwork is the starting point. People are posting $500–$5,000 jobs right now asking for AI workflow automation, desktop automation, and RPA replacements. Nick's approach: find the job, give the context to OpenClaw or Claude Code, build a demo, and submit the proposal. It is a lead generation machine.
5) Design Thinking for Automation
Before touching any code, Nick maps every potential automation on two axes: value created and effort/cost/time. You start with high-value, low-effort opportunities — the low-hanging fruit. Then you map out the step-by-step workflow in Figma (or Mermaid code for ExcaliDraw/TLDraw) so OpenClaw can execute tip to tail.
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 NICK ON SOCIAL
Youtube: https://www.youtube.com/@nickvasiles
Instagram: https://www.instagram.com/nickvasilescu/
Personal Website: https://www.nickvasilescu.com/
Claude Code built me a $273/Day online directory
I sit down with Frey Chu to go deep on how to use Claude Code to build AI-coded directories, specifically how to tackle the hardest part: getting valuable data. Frey walks us through three real-world directory examples (a funeral home directory, a senior living directory, and GasBuddy), we play a game guessing their traffic and monetization, and then he does a full live walkthrough of the seven-step process he used to build a luxury restroom trailer directory in four days for under $250. I also ask him about the future of directories in a world where LLMs are changing how people search.
Timestamps
00:00 – Intro
02:15 – What you’ll learn
03:00 – Directory Game:Parting(Funeral Home Directory)
05:42 – Directory Game: A Place for Mom (Senior Living Directory)
08:00 – Directory Game: GasBuddy (Crowdsourced Gas Price Directory)
12:32 – The Data Moat Thesis
14:02 – Luxury Restroom Trailers: The Niche Directory Demo
15:52 – Before & After: WordPress Directory vs. Claude Code Directory
19:04 – Cost Breakdown: Built in 4 Days for Under $250
21:23 – Step 1: Scraping Raw Data with Outscraper
22:25 – Step 2: Cleaning Data with Claude Code
23:27 – Step 3: Using Crawl4AI for Automated Website Verification
28:01 – Step 4: Enriching Trailer Inventory Data
31:33 – Step 5: Scraping & Verifying Images with Claude Vision
36:33 – Step 6: Amenities, Features & Filter Data
38:31 – Step 7: Service Areas
39:15 – Niche Directory Ideas: Dementia Care, ADA Bathrooms, Tap Water Quality
43:38 – For Naysayers: Is Building a Directory Worth It in 2026?
47:51 – LLMs, AI Search & the Future of Directories
Links Mentioned:
Outscraper: https://startup-ideas-pod.link/outscraper
Crawl4AI: https://startup-ideas-pod.link/crawl4AI
Key Points
* Data is the moat for any successful directory — and with Claude Code plus Crawl4AI, the hardest part (data cleaning and enrichment) is now dramatically faster and cheaper.
* Every successful directory helps people save time, save money, or make money — and price transparency is a massive, underserved opportunity across boring niches.
* Frey built a fully enriched luxury restroom trailer directory in four days for under $250, a process that would have taken 2,000+ hours of manual work.
* Monetization depends on the niche: lead generation, vertical SaaS, agency services, ads, debit cards, affiliate, and marketplace models all work.
* Directories remain strong in an AI search world because users browsing a directory are in the decision-making phase, especially in high-stakes niches like health, legal, finance, and senior living.
* Building a directory is one of the best playgrounds to learn Claude Code, SEO, and lead generation — even if the first one is just a learning exercise.
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 FREY ON SOCIAL
X/Twitter: https://x.com/freychu
YouTube: https://www.youtube.com/@FreyChu/featured
ShipYourDirectory: https://www.shipyourdirectory.com/
Stop Shipping AI Slop. Design with Weavy AI, Claude etc.
I sit down with my friend Suraya Shivji, a designer who sold her last company to Snap, to tackle the biggest problem in vibe coding: everything looks the same. Suraya walks me through her full AI design workflow — from Google AI Studio to Claude to Weavy AI to Figma and back — showing how to turn a generic one-shot prototype into a beautifully branded app. Together we live-build a voice journaling app called "Cassette," covering everything from defining how a product should *feel*, to generating color palettes, custom assets, and logos using Weavy AI, Flux, and Ideogram. This is a start-to-finish tutorial for anyone who wants their vibe-coded products to look like a real brand designer made them.
Timestamps
00:00 – Intro
03:35 – Why Every Vibe-Coded App Looks the Same
04:34 – Prototyping with Google AI Studio
09:34 – Defining How Your App Should Make Someone Feel
11:07 – Using Claude to build Brand Identity/Guidelines
16:38 – Building a Mood Board with Cosmos
17:58 – Intro to Weavy AI: Node-Based Visual AI Tool
19:32 – Generating Color Palettes with Flux 2 Pro in Weavy
26:54 – Creating Record Buttons and Custom Assets in Weavy
30:46 – Generating Cassette Tape History Elements
34:47 – Logo Generation with Ideogram V3 in Weavy
38:52 – Compositing the Final App Screens in Figma
47:38 – Pasting the Design Back into Google AI Studio
47:00 – Comparing Figma Output vs. Google AI Studio Output
52:20 – Final Advice: Spend Time on Inspiration, Then Build
Key Points
- Vibe-coded apps are easy to build now, but they all look the same — branding is what makes someone actually download and use your product.
- Weavy AI is a node-based tool that lets you run image models like Flux 2 Pro and Ideogram visually, making it easy to generate color palettes, buttons, assets, and logos from reference images.
- Claude serves as the ideal brainstorming partner for writing brand guidelines, crafting image generation prompts, and refining your creative direction.
- The full workflow is: Google AI Studio (prototype) → Claude (brand strategy) → Cosmos (mood board) → Weavy AI (visual assets) → Figma (composition) → back to AI Studio (final build).
Numbered Section Summaries
1) The Vibe-Coded Sameness Problem
I open by laying out the core issue: anyone can build an app now, which is amazing, but everything ends up looking identical. If your app looks like everything else, it is really tough to expect anyone to download it. Soraya and I set out to prove you can go from a generic prototype to something that looks like an agency designed it.
2) Defining How Your Product Should Feel
Soraya's process always starts with emotion: who is this for, and how should they feel using it? We decide our journaling app is for overthinkers who are tired of being on their phones and want something analog and calm. She pastes this framing into Claude to generate deeper brand insights, including what the product is and what it is *absolutely* meant to avoid being (a productivity tool, a social app).
3) Brand Guidelines and Mood Boarding
Claude helps us write brand guidelines for our app, now called "Cassette." Soraya then moves to Cosmos (a Pinterest alternative) to build a mood board of vintage cassette imagery. The key insight: brand guidelines are really just a prompt you bring into your visual tools — they guide every design decision downstream.
4) Weavy AI: The Visual Asset Engine
Here is the core of the episode. Soraya shows how Weavy AI works as a node-based canvas where you feed in reference images and run them through models like Flux 2 Pro. We generate color palettes, textured backgrounds, record buttons, and cassette tape history elements — all grounded in the mood board. She switches between Claude (for prompt writing) and Weavy (for visual output) throughout.
5) Compositing in Figma and Final Comparison
Soraya assembles all the generated assets — logo, record button, cassette tapes, color palette — into iPhone frames in Figma. She shares practical tips like using blend overlay for automatic color matching. We then paste the Figma reference images back into Google AI Studio and compare outputs. The AI Studio version is dramatically better than the original one-shot, and Soraya notes you could skip Figma entirely if you prefer.
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 SURAYA ON SOCIAL
X/Twitter: https://x.com/surayashivji
Personal Website: https://www.surayashivji.com/
Claude Cowork Explained
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.
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.
Numbered Section Summaries
1. Cowork Makes Claude Code Feel Like A Teammate
I frame Cowork as a UI-first way to access Claude Code that feels approachable for non-technical users. Boris and I focus on real use cases, especially the “work on my stuff” mindset around files and day-to-day operations.
2. “Agentic” Means Actions, Not Answers
Boris draws a clear line between chat-style tools and agents that take action across your computer. We talk about why tool use and computer use matter, and why that direction has been core to Anthropic’s roadmap.
3. Demo: Clean Up Your World With Folder Access
We start simple: granting access to a receipts folder and renaming files to match receipt dates. It’s an easy first workflow that helps people build intuition for how Cowork operates with real files.
4. Demo: From Receipts → Spreadsheet → Google Sheet
We push the demo into “real work”: extracting receipt details into a spreadsheet, then moving it into Google Sheets through browser control. This is where the mental model shifts—Cowork becomes an operator across apps.
5. Parallelism Beats Speed
I bring up the obvious critique (“humans can do this faster”), and Boris explains the real advantage: running multiple tasks in parallel while you bounce between them. The workflow becomes tending to multiple agents instead of doing every click yourself.
6. Skills, Extensions, MCP: When To Customize
We talk about keeping Cowork simple early, then adding skills when you hit specific software workflows. Skills act like repeatable procedures that help the agent perform better inside specialized tools.
7. Boris’s Claude Code Setup: Plan → Execute → Verify
I break down Boris’s viral thread on how he works: run many sessions, start in plan mode, then switch into execution once the plan looks right. The signature upgrade is verification—giving Claude a way to test and confirm its own output.
8. Claude md As Compounding Engineering
We close on one of the most practical systems: a shared Claude md file checked into the repo, updated constantly by the team. Boris ties this to a “never repeat feedback” loop that turns recurring review comments into durable behavior.
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
Claude Code Built My $450K Marketing Campaign
I sit down with Jonathan Courtney, host of Unscheduled CEO Podcast, to talk about the gap between building AI-powered products and actually making money from them. Jonathan walks through his four-step "Promoter Blueprint" — traffic, holding pattern, selling event, and conversion — and shows exactly how he uses Claude and Claude Code to execute each phase. This one is a wake-up call for any founder spending more time optimizing automations than promoting what they sell.
Timestamps
00:00 – Intro and Welcome Back
04:13 – The Founder’s Real Job: Promotion, Period
09:23 – The Promoter Blueprint (Screen Share)
19:38 – Using AI with Promoter Blueprint
22:52 – Inside Claude: Jonathan's Claude Workflow
28:41 – Moving from Claude to Claude Code for Builds
30:55 – Building a $450K Webinar Campaign with Claude
37:30 – Scale Up, Abundance Over Efficiency
43:57 – Final Advice: Embrace Your Role as Promoter
Links Mentioned:
JC's promoter blueprint: https://startup-ideas-pod.link/promoter-blueprint
Key Points
* A CEO's primary job is promoting the business — building is secondary to getting people in the door.
* AI tools become "procrastination machines" when builders optimize systems that have zero customers.
* Every revenue engine follows four phases: traffic, holding pattern, selling event, conversion (and a loop back).
* Claude projects combined with Claude Code create a fast workflow for going from research to a shipped marketing asset in under an hour.
* The current play is abundance and scale, using AI to run five campaigns instead of one, rather than cutting headcount for efficiency.
* Off-the-shelf solutions still beat custom builds in many cases — always ask before you spend three days vibe-coding something.
Numbered Section Summaries
1) The Builder Trap
Jonathan opens with a blunt observation: too many founders treat AI tool mastery as the job itself. He compares it to building the world's most automated restaurant and then telling zero people it exists. If you are spending days on automations and your revenue has stayed the same, you are procrastinating with extra steps.
2) The Promoter Mindset
Every successful CEO Jonathan can name — Dario Amodei, Sam Altman, Peter Levels, Jason Fried — spends at least half their time promoting. The founders people know by name are the founders who show up everywhere. Jonathan frames promotion as oxygen for the business: cut it off and the business dies regardless of how good the product is.
3) The Four-Step Promoter Blueprint
Jonathan shares a framework he normally sketches on paper for clients. Step 1 is traffic (organic or paid). Step 2 is the holding pattern — newsletters, podcasts, social — where you warm people up. Step 3 is the selling event: webinars, demos, email sequences, retargeting campaigns, or direct outreach. Step 4 is conversion, and everyone who does not convert loops back into the holding pattern for the next campaign.
4) Claude as a CEO's Marketing Co-Pilot
Jonathan walks through how he prepped for this very episode inside a Claude project — dumping a voice memo, having Claude create an ADHD-friendly outline, researching my past episodes, and auto-generating project instructions at the end of each chat. He then exported the context into a Claude MD file and moved to Claude Code to build the visual blueprint that shipped to Vercel in about an hour total.
5) From Marketing Brain to Lead Magnet in Minutes
Live on-screen, Jonathan shows his "AJ&Smart Marketing Expert Brain" Claude project — a setup loaded with books he has written, a 17,766-line swipe file of competitor emails, and custom instructions. He prompts it to generate lead magnet ideas tied to our episode and gets three strong concepts in seconds. The whole flow from podcast appearance to landing page used to take his team two to three days; it now takes half a day.
6) Less Prep, More Action
Jonathan and I agree that over-preparation is the biggest red flag in a founder. These tools are forgiving enough to learn on a live project. Jonathan jumped straight into Claude Code on a real campaign, hit the context window limit, figured out chunked workflows by necessity, and kept shipping. The takeaway: just cut.
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 JONATHAN ON SOCIAL
Unscheduled CEO Podcast: https://www.unscheduledceo.com/
X/Twitter: https://twitter.com/Jicecream
LinkedIn: https://www.linkedin.com/in/jonathan-courtney-4510644b/
Claude Code Clearly Explained
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.
Links Mentioned:
Ras's Ralphy AI Agent: https://startup-ideas-pod.link/ras-ralphy
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
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.
Numbered Section Summaries
1. **The Research-First Foundation** James opens with his core philosophy: most people jump into AI tools and start prompting immediately, which is where AI slop comes from. I watch him demonstrate how he spends a full hour doing deep market research with the Perplexity MCP — analyzing competitors, finding gaps, and building rich context documents before ever creating a marketing asset. This context loading step is the foundation everything else builds on.
2. **Live Build: AI Marketing Agency Funnel** We go hands-on with a fictional use case — launching an AI marketing agency targeting boring local businesses doing $2–10M in revenue. James uses the positioning angles skill to surface five distinct angles, then spins up a task-based agent (prompted to think like me) to pick the strongest one. The winner: "Boring Money," an anti-agency positioning that resonates deeply with overlooked trade businesses.
3. **Traffic Strategy and the Full System** The session closes with James invoking keyword research and DTC ad skills to build a traffic plan. Claude Code identifies underserved local markets, generates SEO content pages for the website, and produces a paid ad strategy — all informed by the positioning, brand voice, and competitive intelligence gathered earlier. The full marketing system — research, positioning, landing page, lead magnet, ad creative, SEO content, and traffic strategy — is built in roughly one hour from the terminal.
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/
48:55Claude Opus 4.6 vs GPT-5.3 Codex
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.
Numbered Section Summaries
1) Setup and Configuration for Opus 4.6
I have Morgan walk through the exact steps every developer needs: update via NPM, verify version 2.1.32+, set the model to Opus in settings.json, and — critically — enable the experimental Agent Teams flag by setting `claude_code_experimental_agent_teams` equal to one. He also covers adaptive thinking (API-only), effort levels (max is Opus 4.6 exclusive), and TMUX split panes for visualizing multiple agents in action.
2) Feature-by-Feature Comparison
Opus 4.6 offers a 1-million-token context window, strong architectural comprehension, and less tendency to write reckless code. GPT-5.3 Codex has a roughly 200,000-token context window, wins on SWE-Bench Pro and coding benchmarks, and excels at progressive execution and rapid iteration. Morgan frames it well: Claude is your senior staff engineer asking "should we do this?" while GPT-5.3 is your founding engineer asking "how fast can I ship this?"
3) Live Build: Prompt Design and Fair Setup
Morgan creates separate prompts tailored to each model's strengths. For Opus, he instructs it to build an agent team with four specialists (architecture, prediction market domain, UX, testing). For Codex, he gives a parallel prompt asking it to think deeply about the same four areas. He starts both at essentially the same moment to keep the comparison honest.
4) Final Verdict and Recommendations
Morgan is clear: this is about methodology, not a winner-takes-all contest. Opus 4.6 excels when you want to delegate whole chunks of work to autonomous agents and review comprehensive results. Codex 5.3 excels when you want a fast, interactive collaborator you can steer in real time. Many teams will end up using both. Morgan encourages engineering leaders to give their teams access to both models and let them experiment.
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/
The Claude Code Skill My Smartest Friends Use
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.
Numbered Section Summaries
1. What Is "Last 30 Days"Matt explains the core problem: AI and online conversations move too fast to track manually. Last 30 Days solves this by aggregating real-time data from X, Reddit, and web searches into a single Claude Code skill, letting users become instant experts on any topic.
2. API Setup and How It WorksThe skill pulls together multiple API connections—OpenAI for Reddit access, XAI for X/Twitter search, plus standard web search. Matt notes he is exploring direct Reddit API integration to improve results further.
3. Cold Email Frameworks DemoMatt prompts the tool to research high-performing cold email techniques from the last 30 days, then uses that research to generate personalized outreach emails. The tool surfaces frameworks like AIDA, Three Ps (Praise-Picture-Push), and Intention Data Triggers—all without Matt reading the underlying research.
4. From Research to Product BuildThe episode moves into building a Moltbot competitor. Matt shows how he uses Last 30 Days to research Moltbot use cases, then feeds that intelligence into Compound Engineering to plan an enterprise-grade product from scratch.
5. Trending Web Design for Landing PagesMatt queries what website designs are getting the most love on X right now. Results include the Shopify "Winner Edition" page and a praised YC landing page. He then prompts Claude Code to generate a Figma-ready design spec for a SaaS productivity app.
6. Building Without Engineering SkillsMatt emphasizes he has not shipped production code since high school. His workflow involves running Claude Code in the terminal, taking screenshots of errors, pasting them into ChatGPT for debugging help, and iterating. The biggest unlock: learning to paste screenshots with Control+V instead of Command+V.
7. Getting Started RecommendationsMatt advises signing up for Claude Code's $20 plan, using ChatGPT as a troubleshooting copilot, and experimenting with skills like Last 30 Days and Compound Engineering. Trial and error, combined with lots of terminal windows, is the path forward.
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
Screensharing Kevin Rose's AI Workflow/New App
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.
Numbered Section Summaries
1. Nylon: A Solo “Techmeme-Level” Build
Kevin shows me Nylon, a nights-and-weekends project built to answer a single question: can one person assemble a Techmeme-quality feed tailored to AI velocity. He frames it as personal curiosity first, product second.
2. From Sources To Articles: The Ingestion Spine
He pulls from dozens of sources (RSS, Reddit, major tech outlets) and stores everything in Postgres. Each article flows through a status pipeline that tracks enrichment steps and readiness.
3. Enrichment Stack: iFramely, Firecrawl, Gemini
Kevin uses iFramely for rich link metadata cards and Firecrawl for deeper crawling, then leans on Gemini as a last-resort “grounded” fill when crawls fail or quality looks weak. A judge picks the “winner” per field so the database keeps the best available representation.
4. TLDRs And Embeddings: Turning Text Into Math
He generates a purposely rich TLDR for vector embeddings, stores vectors in Postgres, and uses them to compare meaning across stories. Kevin highlights how embeddings capture nuance like role reversal in similar headlines.
5. Durability With trigger.dev
Instead of fragile cron glue, he runs TypeScript tasks as orchestrated jobs with retries, traces, and monitoring hooks. That keeps the pipeline resilient while he develops locally and scales later.
6. Clustering And Expansion: From Three Signals To The Whole Web
Once a topic crosses a threshold, he expands coverage via search APIs (Brave, Tavily) to pull in relevant articles outside the RSS set. The cluster page becomes a living dossier with timing, sources, and similarity distances.
7. The Gravity Engine: Editorial Judgment As Code
Kevin layers an “editorial vote” system over clusters, scoring dimensions like industry impact, novelty, technical depth, viral potential, and PR-fluff risk. The point is prioritization: a small list of truly worthy items for a specific person.
8. The Meta Lesson: Personal Software And Play As Strategy
We zoom out to vibe coding, distribution mechanics, and how “for fun” projects sometimes become the biggest businesses. Kevin shares ways to connect with him through DIG and his Venice studio, plus his view on when capital makes sense.
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
How I Use Clawdbot to Run My Business and Life 24/7
I sit down with Kitze to unpack how he uses Clawdbot (now known as OpenClaw) 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 – Security Advice and Best Practices
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
Numbered Section Summaries
1. The Personal OS Premise
I frame the episode around practical Clawdbot use cases and bring Kitze in to show his day-to-day setup. We move quickly from concept to real workflows you can copy.
2. One Gateway, Many Personas
Kitze describes running a single Clawdbot gateway that connects to multiple front ends like Discord and Telegram. Each persona carries its own skills, tone, and scope so conversations stay focused.
3. Persona Playbooks For Real Life
We go through examples like Guilfoyle for engineering, Kevin for accounting, Dr Cox for health analysis, and Darlene for home management. The separation routes tasks to the right context and keeps each agent aligned to its job.
4. Discord As A Control Panel
I ask why Discord beats a single chat thread, and Kitze shows how sections and channels create a map of work. Threads function as temporary tasks or skills in progress, while channels serve as durable hubs.
5. Customer Support Through Threads And Sub-Agents
Kitze describes scraping or fetching signals from email and DMs, then spawning customer threads with summaries and action plans. A main channel stays the command layer while sub-agents process individual customers in parallel.
6. Self-Learning Through Shell And Network Access
We talk through how an agent can find printers, cast dashboards, and discover devices through Home Assistant and the local network. Kitze shares examples like printing ASCII art, casting screens, and generating dashboards for TVs and e-ink displays.
7. High-Leverage Use Cases: From Captcha To Wearables
We run a rapid tour: AntiCaptcha as a backstop for automations, a programmable ring as a voice-input interface, and TRMNL as a life OS display surface. We also cover home presence sensors and context injection so the assistant gets room-level state.
8. Prompt Products And The Wrap
Kitze shows Spellbook, a prompt organizer that turns templates into variable-driven forms users fill out. I wrap by pointing people toward Kitze’s work and his community for deeper tinkering.
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/
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