The Startup Ideas Podcast

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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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

In this episode, I sat down with Chris Koerner and we go through a set of approachable startup ideas that start low-friction but can scale if you get distribution right. We start with a potential “app ecosystem” opportunity around Facebook Marketplace, plus a product-studio framework that combines short-form video, AI, and 3D printing to validate “dumb” products via demand before you invest. We then jump to more grounded, local-first ideas—bike washing/maintenance subscriptions, bar anti-spike stickers, and even vending-machine concepts like “shiny rock” drops at trailheads. We close with a weird Pokémon-card “meme + supply control” play inspired by the Kabuto King, including Chris’s own collecting “big reveal.” From there, I dig into why PSA-style grading feels slow and expensive, and we workshop a more modern grading experience (including a livestream/packaging angle and an AI-from-photo approach).

Timestamps

00:00 – Intro

02:28 – Startup Idea 1: Facebook Marketplace App Studio

07:43 – Startup Idea 2: DTC Product Studio

17:05 – Startup Idea 3: Bike Washing/Maintenance Subscription

24:29 – Startup Idea 4: Anti-Drink-Spike Stickers

31:55 – Startup Idea 5: Shiny Rock Vending Machines

36:37 – Startup Idea 6: The Kabuto King and Card Grading

Key Points

• I look for “alpha” where people are already obsessing, but the market structure is still primitive (like collectibles + grading).
• I treat “distribution” as the multiplier—short-form can make “dumb” products viable if the content loop is strong.
• I push for starting manually first (prove demand), then upgrading into infrastructure, subscriptions, and scale.
• I pay attention to marketplaces with huge usage but weak third-party tooling—there’s often a platform-layer opportunity there.
• I keep coming back to “repackaging” as a business model: same underlying thing, new wrapper, new buyer, new channel.
  
  

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 CHRIS ON SOCIAL:

X/Twitter: https://x.com/mhp_guy

Instagram: https://www.instagram.com/thekoerneroffice/

Youtube: https://www.youtube.com/@thekoerneroffice

We got Ryan Carson on the pod to break down the “Ralph Wiggum” Agent and why it’s suddenly everywhere. He walks me through a simple workflow that lets an autonomous agent build a full product feature while I sleep: start with a PRD, convert it into small user stories with tight acceptance criteria, then run a looped script that ships work in clean iterations. The big idea is you’re not “vibe coding” one giant prompt—you’re giving the agent testable, bite-sized tickets and letting it execute like an engineering team. By the end, Ryan shows how this becomes repeatable (and safer) with a memory layer—agents.md for long-term notes and progress.txt for iteration-to-iteration context.

Timestamps

00:00 – Intro

02:44 – What is the Ralph Wiggum AI Agent

03:40 – Step 1: PRD Generator

06:11 – Step 2: Convert PRD to Json

09:47 – Step 3: Run Ralph

12:05 – Step 4: Ralph Picks a Task

13:14 – Step 5: Ralph Implements Task

14:49 – Tokens + Cost: What It Actually Spends

15:45 – Guardrails: Small Stories + Clear Criteria Keep It Sane

16:19 – Step 6: Ralph commits the change

16:38 – Step 7: Ralph Updates PRD json file

16:55 – Step 8: Ralph Logs to Progress txt

20:08 – Step 9: Ralph Picks another Task

20:48 – Step 10: Ralph Finishes Tasks

21:18 – Example of how Ryan uses Ralph

24:08 – How To Start Today (Ralph Repo) and Tips

Links Mentioned:

Ralph Wiggum Agent: https://startup-ideas-pod.link/Ralph-agent 
AI Agent Skills: https://startup-ideas-pod.link/amp-skills 
AMP: https://startup-ideas-pod.link/amp-code 
Ryan’s Ralph Step-by-Step Guide: https://startup-ideas-pod.link/Ryans-Ralph-Guide

Key Points

• I can’t expect “sleep-shipping” unless I translate the feature into small, testable user stories with clear acceptance criteria.
• Ralph works like a Kanban loop: pull one story, implement, commit, mark pass/fail, then grab the next.
• The real leverage is the reset: each iteration starts fresh with a clean context window, instead of one giant, messy thread.
• agents.md becomes long-term memory across the repo; progress.txt is short-term memory across iterations.
• The bottleneck isn’t “coding”—it’s the upfront spec quality: PRD clarity, atomic stories, and verifiable criteria.

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 RYAN ON SOCIAL:

X/Twitter: https://x.com/ryancarson

Amp: https://ampcode.com

In this episode, I’m breaking down a guide from Ben Tossel on how you can actually build with AI agents without being technical. I walk through what he’s shipped as a “non-technical” builder, why he lives in the terminal/CLI, and the exact workflow he uses to go from idea → spec → build → iterate. We also talk about the meta-skill here: treating the model like your over-the-shoulder engineer/teacher, and using every bug as a learning checkpoint. The takeaway is simple: pick a tool, ship fast, fail forward, and build your own system as you go.

Ben’s Article: https://startup-ideas-pod.link/Ben-Tossell-Article

Timestamps

00:00 – Intro

01:04 – What Ben Has Shipped

03:21 – The Workflow: Feed Context → Spec Mode → Let The Agent Rip

07:52 – His Agent Setup

08:56 – Coding On The Go

10:07 – Things to Learn

13:33 – The New Abstraction Layer: Learning To Work With Agents

14:33 – Learning from Others

16:15 – Use The Model As Your Teacher (Ask Everything)

18:13 – Contributing to Real Products

19:13 – Why this is Different

21:31 – Asking Silly Questions

24:00 – Beyond “Vibe Coding”: A New Technical Class

24:43 – Vibe Coding is a game

27:12 – Fail Forward + Permission To Build And Throw Things Away

28:16 – Pick One Tool, Minimize Friction, Keep Shipping

Key Points

• I don’t need to be a traditional engineer to ship—I can learn by watching agent output and iterating.
• The terminal/CLI is the power move because it’s more capable and I can see what the agent is doing.
• “Spec mode” works best when I interrogate the plan like a philosopher instead of pretending I understand everything.
• agents.md becomes my portable instruction manual so every new repo starts clean and consistent.
• The fastest learning path is building ahead of my capability and treating bugs as checkpoints—fail forward.
  
  

Numbered Section Summaries

1. The Thesis: Non-Technical Doesn’t Mean Non-Builder I open with Ben’s core claim: you can ship real software by working through a terminal with agents, even if you can’t write the code yourself—because you can read the output and learn the system over time.
2. Proof: What He’s Actually Shipped I run through examples Ben built—custom CLIs, a crypto tracker, “Droidmas” experiments, an AI-directed video demo system, and automations that keep projects moving even when he’s away from his desk.
3. The Workflow: Context → Spec Mode → Autonomy High Ben’s process is straightforward: talk to the model to load context, switch into spec mode to pressure-test the plan, link docs/repos for exploration, then let the model run while he watches and steers when needed.
4. http://agents.md/ The “Readme For Agents” That Follows You Everywhere I explain why agents . md matters—one predictable place to tell your agent how you want repos structured, how to commit, how to test, and what “good” looks like so each session gets smoother.
5. Coding On The Go: PRs, Issues, Phone, Telegram, Slack We get into the real “agent native” behavior: install the GitHub app, work via pull requests and issues, tag the agent to self-fix, and even push changes from your phone—plus using Slack as a one-person “product” with an agent in the loop.
6. Learning The Primitives: Bash, CLIs, VPS, Skills I cover the building blocks Ben’s learning: bash commands and repeatable terminal workflows, preferring CLIs over MCPs to save context, and using a VPS + syncing to keep projects always-on.
7. The Mindset Shift: The Model Is The Teacher The real unlock is treating the model like your patient expert—ask everything you don’t understand, bake “explain simply” into your agent instructions, and close knowledge gaps as they appear.
8. Fail Forward, Pick One, Keep Shipping I end on the playbook: build ahead of your capability, treat it like play, give yourself permission to throw things away, and stop tool-hopping—pick one system and go deep.

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 walk through Alibaba’s new AI agent tool, Accio, and show how it helps you go from “what should I build?” to actual product concepts and supplier options. I demo how it spots rising trends, pulls specific product opportunities (with context like search and sales movement), and even generates early design concepts. Then I test it on a real research task and use that to spin up a “cozy gaming” keyboard concept aimed at Gen-Z women. I close by showing how Accio can vet suppliers and even draft a supplier outreach email so you can start the sourcing process faster.

Timestamps

00:00 – Intro

01:55 – Trend Spotting Demo

03:31 – Designing Products Demo

07:04 – Product Opportunity Pain Points Demo

10:10 – Supplier Search Demo

11:06 – Mechanical Keyboard Market Research and Pain Points

16:03 – Cozy Gaming Mechanical Keyboard For Gen Z Women

18:42 – Supplier Vetting + Due Diligence

22:00 – Supplier Outreach

Key Points

• Accio compresses the e-commerce workflow: trends → product ideas → design concepts → supplier shortlists.
• The real leverage is pairing insights (ratings, negative tags, review pain) with concrete product recommendations.
• The “agent task” flow feels like a research assistant: it gathers sources, updates a plan, and synthesizes outputs.
• Accio can move from concept to execution by suggesting suppliers and drafting a structured inquiry email.
• You still need real diligence: call suppliers, vet claims, and start with small orders.
  
  

Numbered Section Summaries

1. Accio As An “Unfair Advantage” For E-Commerce I introduce Accio as an AI agent built around e-commerce workflows—idea generation, trend analysis, product concepts, and supplier sourcing. My core point is it reduces the friction that usually keeps me (a software person) from starting e-commerce.
2. Trend Spotting That Goes Beyond Generic Charts Using a baby products example, I show that it’s not just search/sales graphs—it surfaces specific product categories and differentiators (like smart features) plus recommendations you can validate elsewhere.
3. Turning Pop Culture Into Product Concepts (With Caveats) I try a “Squid Game” prompt to generate product directions and visuals. I’m clear this isn’t a “press button, print money” system, but it gets the creative juices flowing and connects ideas to sourcing.
4. Finding Opportunities By Reading What Customers Hate In the senior dog pet supplies example, Accio highlights product opportunities and connects them to the underlying pain (accessibility, cognitive decline, weak ratings). I emphasize that the edge is insight—knowing why current products underperform.
5. Supplier Discovery Without The Usual Alibaba Overwhelm I run a supplier prompt with constraints (OEM, private label, MOQ, certifications, reviews). The key is Accio structures what’s normally chaotic and gives a shortlist you can actually act on.
6. Agent Research: Mechanical Keyboard Pain Points, Ranked I test an agent task to find unmet pain points and cluster them by theme, with “proof” from reviews/forums/Q&A. The point isn’t keyboards—it’s showing how fast you can go from “trend” to “what to build” using structured research.
7. From Pain Points To A Launchable Niche Concept (Cozy Gaming) I pivot from the research into a niche: mechanical keyboards for Gen Z women aligned with “cozy gaming.” Accio proposes brand directions, a flagship product concept, and early roadmap thinking.
8. Reality Check: Sourcing, Verification, And Outreach I ask for trusted suppliers and get a short list plus technical verification prompts (finish, sound profile, color matching). Accio then drafts a supplier email and shows how the workflow can extend to sending inquiries—while I remind you to vet suppliers carefully and start small.

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 walk through a beginner-friendly, step-by-step way to set up Claude Skills so you can get more consistent, higher-value output over time. I show where to enable Skills (it’s not on by default), how to create a new skill using Claude’s “create a skill together” flow, and why Skills are different from Projects for ongoing, reusable workflows. Then I demo a real example: building a conversion-focused copywriting review skill for an agency workflow, installing it, and testing it on app store screenshots + website copy. I close with how to level up Skills by iterating them over time, using a 10-step process I reference from a “Boring Marketer” tweet.

Timestamps:

00:00 – Intro

00:40 – Enable Skills (Settings → Capabilities → Skills Preview)

01:21 – Creating a new skill

06:34 – Why Skills are important Projects for “always-on” workflows

07:49 – Reviewing the skill

10:34 – Installing the skill (copy to skills / upload in Skills)

11:28 – Testing the Skill 16:14 – How to improve skill over time

Key Points

• Skills make Claude’s output more consistent because you bake in reusable context and workflows.
• Skills aren’t enabled by default—turn them on in Settings → Capabilities.
• The easiest path for most people is “Create a skill together,” then answer Claude’s scoping questions.
• A strong skill includes frameworks, scoring, and an output template—not vague advice.
• The real power comes from iterating: test on real scenarios, critique, refine, and keep improving the skill over time.

Numbered Section Summaries

1. Why Skills Matter For Beginners I open by explaining that Skills help you get more consistent, higher-value output from Claude over time, especially if you’re a beginner and want repeatable results.
2. Turn On Skills First Skills aren’t enabled by default, so I show the exact path: Settings → Capabilities → enable the Skills preview feature.
3. Create A Skill (Three Paths) I walk through the three options: create with Claude, write skill instructions, or upload an existing skill
4. Build A Real Skill: Conversion Copy Review I describe the skill I want: a conversion-focused copywriting reviewer for apps and websites, built like a specialist “employee” that can critique headlines, CTAs, value props, pricing pages, and more.
5. Skills vs Projects (And Why Skills Win For Ongoing Work) I explain why I prefer Skills for ongoing workflows: Projects can be context-specific to a campaign, while Skills are meant to work across day-to-day work regardless of the project timeline.
6. What Claude Generates (And Why Markdown Is Great) I show Claude generating the skill structure and markdown files (like skill md and framework docs), and I call out why markdown is practical and easy for non-technical folks to edit.
7. Install + Test The Skill On A Real Example I install the skill (copy to Skills / upload) and test it on real assets—app store screenshots and website copy—to see if it actually follows the skill workflow.
8. Make The Skill Better Over Time (The Improvement Loop) I share the idea that Skills shouldn’t stay static. I reference a 10-step process (understand the problem, explore failures, research, synthesize, draft, self-critique, iterate, test, finalize) and emphasize ongoing iteration based on real outputs.

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/

Today I break down a big news item I think is flying under the radar: OpenAI quietly launched Skills for Codex, and I explain what that means (and how it differs from sub-agents and MCPs). I then share a fast-moving trend I’m watching and why it’s a strong wedge for a simple app. After that, I recommend the to-do app I’ve used for 14 years and give away a startup idea. I close with a practical 6-step framework for going from idea → viral validation → mobile app launch in 2026.

Timestamps

00:00 – Intro: the new format (news, trend, app, startup idea, framework)

00:40 – AI New Item: OpenAI launches Skills for Codex

05:45 – Trend: Face Yoga

07:56 – App Recommendation: Things

09:33 – Startup Idea: Call-an-expert service for non-developers stuck at 80% done

14:44 – Framework: Viral Mobile App Framework

Key Points

• OpenAI “Skills” make Codex/ChatGPT more reusable and consistent by packaging repeatable workflows.
• A “skill” is the recipe, a “sub-agent” is extra worker instances, and an “MCP” is the tool access plug.
• Face yoga is an emerging sub-niche with clear app potential (simple routines, monetization via paid or ads).
• Last 20 is a practical marketplace idea: pay for 15 minutes of expert unblock help to finish the last 20%.
• Viral validation favors apps that are visually obvious, explainable in three words, and tied to insecurity-driven outcomes.

Numbered Section Summaries

1. OpenAI Skills: The Quiet Upgrade I walk through OpenAI’s launch of Skills for Codex—reusable bundles of instructions/scripts/resources that can be called directly or chosen automatically. I’m excited because this makes agent workflows more consistent and scalable across tasks.
2. The Foundation: Skill vs Sub-Agent vs MCP I clarify the taxonomy: a skill is the written playbook, sub-agents are extra “worker” copies of the model that split a big job, and MCPs are what let the model access external systems like tickets or repos. This is the mental model I want everyone using going into 2026.
3. The Trend: Face Yoga As An App Wedge I share a niche trend I’m seeing—face yoga—and why it’s a product opportunity similar to how yoga apps became huge. I call out the obvious app angles: guided routines, jawline/face-slimming programs, and content-driven growth via short videos.
4. The Tool: Things (My Simple Focus System) I recommend the Things to-do app because it’s simple: “Today,” “Upcoming,” and “Someday,” without a monthly fee. I also note what’s missing (I’d like more AI features), but it still wins for focus if you don’t want a “kitchen sink” system.
5. The Startup Idea: Last 20 (Phone-A-Friend For Vibe Coders) I give away the idea: builders get stuck at 80% after using Cursor/Replit/V0, so Last 20 matches them with someone who’s solved that exact wall before. The product is a fast screen-share session—problem solved—priced per session or bundled for teams/agencies, with the marketplace taking a cut.
6. The Distribution Framework: Viral Validation → Launch I share a 6-step process: warm up the account, design a visually obvious app, build a tiny MVP fast, post daily until something hits, build the community before the product, then launch with a hard paywall and keep content rolling. It’s a simple playbook for getting to organic traction in 2026.

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 go over one AI news item I can’t stop thinking about, one trend you can build a business around, two tools I’m using, one startup idea you should steal, and one framework to end on. I start with a leak suggesting Anthropic is productizing “agent mode” for Claude with structured task buckets and a progress/context UI. Then I use Hyrox as an example of how I validate trends quickly with search data (and what “low competition + cheap CPC + explosive growth” signals). I wrap by pitching a hotel guest-communication concierge and the “thousand people framework” for getting to clarity on your ICP and what they’ll reliably pay for.

Timestamps

00:00 – Intro

00:32 – AI New Item: Anthropic leak: Agent Task Mode for Claude

04:47 – Trend: Hyrox

08:59 – AI App: Krea and Notebook LLM

12:23 – Startup idea: Digital Hotel Concierge

15:59 – Framework: The “1000 People”

For founders doing $50k+ MRR+: https://startup-ideas-pod.link/offline-mode

Key Points

• Agent workflows get “productized” when the UI guides the task (not just a blank prompt box).
• Trend validation can be fast: look for explosive growth + low competition + cheap CPC, then ideate apps around it.
• NotebookLM’s slide generation is an underrated workflow for turning sources into clean decks.
• The “Guest Guide” concept is a simple AI/QR wedge: answer repetitive hotel questions and monetize per property.
• The thousand-people exercise forces clarity: who exactly buys, what they pay yearly, and how you reach them.

Section Summaries

1. The Claude Agent Mode Leak I break down a leak claiming Anthropic is preparing a more structured “agent mode” for Claude, organized into buckets like research, analyze, write, and build plus choices like depth, format, and outputs. The big shift is moving from “open chat” to “delegating distinct tasks” with visibility into progress and context.
2. Productized Prompts = Better Output I explain why a blank text box can be daunting, and why UI that scaffolds intent (validate/compare/forecast, quick vs. thorough, doc vs. slides vs. spreadsheet) can make results meaningfully better. To me, it points at a future where you “check in” on agents like teammates.
3. Trend Hunting I use Hyrox, an indoor fitness competition that’s “like the new CrossFit,” as a real example of how I sanity-check whether something is becoming a business opportunity. The workflow is simple: I see it in culture, then I go straight to Idea Browser to pull search/CPC/competition signals.
4. Two Tools I’m Testing I call out Krea as a creative AI subscription bundling multiple models, and then I highlight NotebookLM’s slide/infographic feature as the underrated part—turning a source (including transcripts) into clean, well-designed slides with strong hierarchy.
5. Steal This: Guest Guide I pitch a hotel digital concierge that handles common guest questions via QR-code guides, priced per property with affiliate upside, and I reference Sadie as an adjacent AI hospitality product (more on calls/reservations). Then I close with the “thousand people framework”: define the real ICP, map what they’ll pay yearly, and figure out distribution—because clarity is the driver.
   
   

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/