The Startup Ideas Podcast

I sit down with Nick, co-founder of Orgo, to break down how to build a custom Grok Bot for a business and sell it for $25,000 up front with a $3,000-a-month retainer. Nick demos Bops, the agent platform he built in a 36-hour weekend, where each bot has its own phone number, email, and computer with four screens. He walks me through his research, design, and build process, the stack behind each bot, and the offer he takes to business owners. We also cover how to pick a niche by calling 50 people you know and how to turn one free case study into warm referrals. If you want to sell AI employees to businesses, this episode gives you the stack, the offer, and an open source repo you can fork today.

Links Mentioned

Nick’s Bops: https://startup-ideas-pod.link/bops

Timestamps

00:00 – Intro

03:09 – Bops, Custom Grok Bot Team

05:07 – Dumb SaaS vs. Custom Apps

07:02 – Selling AI Agent Teams

09:49 – Demoing Bop

13:57 – One Agent per Platform

15:07 – Step 1: Research

17:49 – Step 2: Design

22:12 – Step 3: Picking The Stack

26:43 – Step 4 and 5: Hosting and Shipping Fast

27:21 – The Offer and Business Model

38:02 – Why start this now

40:21 – Finding your first client

47:27 – Closing Thoughts

Key Points

• Busy owners want their problems solved, so a GrokBot built for their industry wins over a platform they have to set up.
• Nick builds in three steps: research the category, design in Paper, then pick a stack and read the docs.
• Each bot gets its own email, phone number, computer, and connectors through Agent Mail, Agent Phone, Orgo, and Composio.
• The SMB offer is $25,000 up front for a system the owner keeps, plus an optional $3,000-a-month retainer.
• A free website redesign, a money-back guarantee, and free lead magnets make the offer easy to accept.
• Call 50 people you know, do the first build free, and trade the case study for warm intros.

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/

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/

In this solo episode, I explain why I say SaaS is dead and what I see taking its place. For 15 years, SaaS meant paying engineers to build a tool and charging per seat, and now models like Opus 5.5, GPT-6, and Argon make the tool easy to build. I walk through what I call smart SaaS: give the tool away for free, collect data and network effects, and make money by upselling AI agents and human services. I share a calorie tracking example, three ways to charge, and why enterprises still pay per seat. If you build software, this episode gives you a map for building something people want in a market where the tool is free.

Timestamps

00:00 – Intro

00:47 – SaaS 1.0

02:56 – SaaS 2.0: The New Business Model

05:12 – How to monetize SaaS 2.0

06:18 – Service is the new Software

07:22 – SaaS Is Dead, Long Live SaaS

08:58 – SMB vs Enterprise

10:31 – Closing Thoughts

Key Points

• AI makes the tool easy to build, so the per-seat model of the last 15 years has run its course.
• Smart SaaS gives the tool away and collects data and network effects as payment.
• The money comes from upselling intelligence from AI agents and services from humans.
• Agents can charge by token or by outcome, and human services by the week or month.
• SaaS for SMBs, prosumers, and individuals trends toward free, while enterprises still pay something per seat.
• The market for getting things done is bigger than the market for tools, so the total market for SaaS grows.

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/

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 Jon Noronha, co-founder and chief product officer of Gamma, to break down agent harnesses and the startup openings around them. Jon explains how Gamma rebuilt its product as a creative agent this year and walks me through the roughly 20 models and 200 calls behind one finished presentation. We talk about AI smell, why taste carries more weight than evals in creative work, how Gamma tests a new model within the hour, and the fast mode test that lost to good friction. Jon also shares the harnesses he wants to see, from a Slack agent that learns his voice to a couch shopping tool that checks the fit in your room. If you want to build a vertical agent, this episode gives you a clear model of what a harness is and where your edge can come from.

This episode was made possible thanks to Anthropic (the team behind Claude) for hosting us at Claude Founder house and sponsoring the episode.

Timestamps

00:00 – Intro

01:23 – What Is an Agent Harness

03:36 – Harnesses as the New Wrappers

04:25 – Inside One Gamma Prompt

08:23 – Where Vertical Harnesses Fit

11:08 – Finding Your Edge

11:56 – Opportunities for Harnesses

13:09 – Designing a Niche Harness

13:48 – AI Smell

15:49 – Evals and Taste

18:40 – Who Pays for AI

19:44 – The Gamma for X

20:19 – A Harness for Slack

22:01 – Building on Other People's Models

23:28 – Closed vs. Open Source Models

24:11 – A Broad but Shallow Stack

24:57 – Prompts vs. Fine-Tuning

25:30 – Testing New Models

26:25 – Running Experiments

29:10 – The Marketing Engineer

32:26 – Interesting Automations

33:33 – The Top 1% Marketing Engineer

35:00 – Everyone Is Now a VP of Agents

36:19 – Experiments as a Numbers Game

38:26 – Underhyped: AI Image Models

40:42 – Startup Opportunities

45:40 – What Jon Would Build Next

47:26 – Closing Thoughts

Key Points

• An agent harness is the set of tools an agent uses to act, check its own work, and deliver a finished result.
• One Gamma presentation uses about 20 models and 200 calls, including rounds of visual QA.
• Strong harness ideas sit in subjective work, where people care about the output and want a human in the loop.
• Your edge comes from a distinct vision, proprietary data, or a business that mixes AI with the physical world.
• Gamma gets 98% of its value from prompts and treats fine-tuning as a cost and quality optimization.
• Experiments reward volume, and Gamma's fast mode test showed that good friction raised paid conversion.

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

FIND JON ON SOCIAL

X/Twitter: https://x.com/thatsjonsense?lang=en

LinkedIn: https://www.linkedin.com/in/jonnoronha/

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP

I sit down with James Dickerson, the Boring Marketer, who owns Diesel Dudes, a mobile diesel repair business in Charlotte, North Carolina, and spent years running agencies for local businesses. James shows how to sell AI-built funnels to Main Street trades businesses doing $2 million to $20 million a year, starting with a Boring Funnels search that found 100 Dallas plumbers worth pitching. He walks through the leaks he finds on their landing pages, the funnel offers he'd sell, and how he'd win clients with the Dream 100, lumpy mail, and local meetups. If you know how to use coding agents, this episode gives you a full playbook for a service business built around booked jobs.

Build funnels that sell: https://startup-ideas-pod.link/boring_funnels

Timestamps

00:00 – Intro

01:23 – Sponsor: Brex

02:08 – Why sell AI to Main Street

03:05 – James's Background

04:32 – Finding and Picking a Niche

07:26 – The $2M to $20M Opportunity

09:02 – Plumbing and HVAC Market Size

10:56 – Underserved Trades Niches

12:38 – Auditing Five Dallas Plumbers

13:50 – Personal Agents vs. Google

15:02 – Selling Booked Jobs and Phone Calls

17:41 – Funnel Offer Overview

19:43 – Funnel Example

23:19 – Matching Ads to Funnels

24:14 – Chet Holmes and the Dream 100

28:18 – Branding your Firm

30:04 – Meta Ads for your firm

31:37 – Stacking Old School and New School Marketing Strategy

34:31 – Find, Pitch, Deliver

36:02 – Showing Owners the ROI

37:37 – Pricing your Offer

41:45 – Reporting With AI

42:33 – Closing Thoughts

Key Points

• Main Street trades businesses doing $2 million to $20 million a year have budgets and few useful pitches in their inbox.
• James sells booked jobs and phone calls, since owners care about revenue and ROI over AI.
• The biggest leaks sit on the landing page: missing ad promises, hidden Google ratings, and buried booking buttons.
• Funnels with tripwires, instant prices, quizzes, and owner videos turn paid traffic into booked jobs.
• The Dream 100, lumpy mail, and local meetups build trust with owners over months.
• One free build in exchange for a case study gets you to paid work.

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/

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/

In this solo episode, I break down the war on AI agents, from Amazon blocking Meta's Muse to Delta treating outside booking agents as unauthorized automated activity to Yelp charging agents for access. I share how I think about an agent, as a customer with a credit card who reads your site instead of looking at it, and the ladder of trust that runs from research to prepare to pay. Then I walk through each big player's bet, my nine stages for how this war plays out, five moves any business can make this week, and the startup ideas I see between agents and the businesses they buy from. If you run a store or build products, this episode gives you a map for selling to customers who send an agent to shop for them.

Timestamps

00:00 – Intro

02:09 –The Three Camps

05:08 – How I Define an Agent

06:52 – The Ladder of Trust

08:54 – Real Reasons to Block Agents

09:48 – What Agents Skip

12:57 – How Each Company is Playing it

17:06 – Lessons From Mint and Plaid

17:49 – The 9 stages of The War on Agents

21:56 – What to do this week

24:39 – Startup Idea 1: Agent Readiness

25:48 – Startup Idea 2: Plaid for One Vertical

26:22 – Startup Idea 3: Insurance for Agents

26:57 – Startup Idea 4: Analytics for Agent Traffic

27:26 – Startup Idea 4: Agent Specialist

28:05 – Closing Thoughts

Key Points

• Agents read product details, prices, shipping, and return policies, so plain-text facts on the page decide whether they pick you.
• Agents climb a ladder of trust from research to prepare to pay, and the whole fight happens on the pay rung.
• Many blocks protect the ad and upsell revenue that agents skip on the way to the sale.
• The biggest stores block, the biggest audiences open the door, and payment and security companies want the toll booth.
• I expect a Plaid moment for agent identity and payments, followed later by ads that buy an agent's first recommendation.
• Vertical Plaids, agent insurance, and agent analytics are open lanes for startups right now.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP

In this solo episode, I break down how to make money with Meta Muse by mining Facebook groups, Marketplace, and Instagram to match buyers with sellers. The idea came after my wife and I had a baby and the agency we hired for a night nurse admitted it found candidates in Facebook groups. I demo Muse finding night nurses at $30 an hour in Montreal, show how to give it a phone number through Bland AI, and share the Marketplace and Instagram tactics I'd use. I close with my four-level framework for growing a matching side business into a trusted list, a community, and a vertical software company.

Timestamps

00:00 – Intro

01:19 – Sponsor: Brex

03:22 – Meta Muse

03:52 – Why this is a big opportunity

04:33 – Picking a Niche, City, and Rules

05:44 – Owning the asset and data

06:51 – Cleaning Data You Own

08:27 – Lessons From eBay

10:37 – A Phone Number With Bland AI

11:30 – Undervalued Facebook Groups

12:55 – Business Pages and IG Niche Pages

13:46 – Prompting Muse Into Facebook Groups

15:19 – Mining FB Marketplace and Instagram

17:20 – Four Levels of Personal Agent Arbitrage

20:38 – Results From Montreal Groups

21:40– Goods vs. Services

22:15 – Muse vs. Dots and Instinct

24:09 – Closing Thoughts

Key Points

• Muse mines public Facebook groups, Marketplace, and Instagram to match buyers and sellers in any niche and city.
• A clean list of names, needs, prices, and trust signals is an asset I own and can sell later.
• Facebook groups, business pages, and IG niche pages look undervalued as Muse agents start crawling them.
• I tell Muse where to look, and Facebook groups gave me the highest quality data.
• My four levels: mine the data, own the list, own the room, then build technology.
• A lean cost structure lets me charge a success fee of a few hundred dollars and keep high margins.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

Gemini 4 Argon is LIVE, Google's most advanced AI model, try it for yourself: https://startup-ideas-pod.link/gemini4-argon

In this solo episode, I share what I learned after a week with Gemini 4 Argon, Google's new frontier model. I show three places it shines: marketing with AI, physical AI, and complex engineering, with a real build for each. You'll see Argon rebuild my holding company's website, write a post in my voice, design a Shopify product customizer that exports STL files, and build a free quoting app for commercial cleaning companies. I close with six techniques that raise Argon's output quality and the Google AI plan I'd pick for building.

Timestamps

00:00 – Intro

01:35 – What Gemini 4 Argon Does Well

03:09 – Rebuilding the Late Checkout Website

07:49 – Justine Moore's Apple Computer Museum

09:20 – Using Argon for writing

13:03 – Physical AI and Vibe Manufacturing

17:41 – Made-to-Order Shopify Store

19:01 – Building Boring SaaS

21:59 – Commercial Cleaning Quote App

25:12 – 6 techniques to get the most out of Argon

28:39 – Closing Thoughts

Key Points

• Argon produces premium creative work once I give it reference images and a clear direction.
• A skill built from my posts, newsletters, and videos lets Argon write in my voice.
• Argon builds Shopify product customizers that export print-ready STL files.
• Free, focused rebuilds of boring legacy SaaS put me in front of likely buyers.
• Argon gets the engineering right on prompt one, and design takes a few more rounds.
• /plan, /subagents, and /goal give me the biggest jumps in output 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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I walk through eight GitHub repos and AI skills that I test at night and on weekends. The list covers launch videos, social research, local voice and dubbing, editable decks, agent teams, lead-magnet tools, idea stress-testing, and design guidance. For each one, I explain what it does, how I'd set it up, and one concrete way to use it to make money or run a business more easily. Most are free to download, and you pay for the model you run them with.

Timestamps

00:00 – Intro

01:25 – Brag: Launch Videos From a Link

04:50 – Agent Reach for Customer Research

07:46 – Voice Studio: Local AI Voice and Dubbing

10:41 – PPT Master: Editable Decks From Notes

12:59 – OpenRig: Coding Agents as a Team

14:57 – Free Tools Skill by Corey Haynes

17:25 – Grill Me Skill by Matt Pocock

19:31 – Impeccable: Design Guidance for Agents

23:03 – My Top Picks: Brag and Agent Reach

24:07 – Closing Thoughts

GitHub Repo Links:

Brag (launch video skill): https://startup-ideas-pod.link/brag

Agent Reach: https://startup-ideas-pod.link/agent-reach

Voice Studio: https://startup-ideas-pod.link/voice-studio

PPT Master: https://startup-ideas-pod.link/ppt-master

OpenRig: https://startup-ideas-pod.link/openrig

Free Tool: https://startup-ideas-pod.link/marketing-skills

Grill Me Skill: https://startup-ideas-pod.link/grill-me

Impeccable Skill: https://startup-ideas-pod.link/impeccable

Key Points

• Most of these tools are free to download, and the main cost is the model you run them with.
• Work I do for someone up front, like a launch video or a design fix, starts a conversation in place of a cold email.
• Posts on Reddit, X, and YouTube show tasks people still do by hand, and a small tool can fix them.
• Translated onboarding videos make a recurring monthly service for other companies.
• Grill Me logs my assumptions so I check them with a real customer before I build.
• Ten clients at $1,000 a month is $10,000 a month, and that cash flow funds the move from services to technology.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I walk through the 13 businesses I think are left to build in the agentic era. I believe that in a world of agents and abundance, owning the right assets puts you in a better position. For each business, I explain what it is, why it holds up in a world of agents, and one or two examples, from Othership's sauna clubs to Osmo's window-cleaning robots. This episode gives you a map of where to build next, at any age.

Timestamps

00:00 – Intro

01:15 – AI-Native Service Firms

02:57 – Offline Businesses

05:41 – Distribution and Organic Audiences

07:34 – Proprietary Data Sets

09:08 – Domain-Specific Harnesses

12:16 – Robotics and Physical AI

14:01 – Physical Products With a Fan Following

16:34 – Compute and Energy

17:31 – Health, Longevity, and Care

19:30 – Marketplaces and Social Networks

21:04 – Real Assets

21:46 – Vertical Agents

22:18 – Security

24:08 – Closing Thoughts

Key Points

• In an AI-native service firm, agents do most of the delivery and a human reviews the exceptions.
• Ad clicks went from about five cents in 2009 to $1–5 today, so I start with organic audiences.
• Proprietary data and domain-specific harnesses are the two gold rushes I see right now.
• Offline businesses, niche hardware, and robotics sell rooms, objects, and labor that agents only support.
• Compute, energy, and security are the scarce inputs every agent depends on.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

Google's most advanced audio models are LIVE, try them for yourself:

Gemini 3.8 Live: https://startup-ideas-pod.link/gemini-3.8-live

Gemini 3.5 Transcribe https://startup-ideas-pod.link/gemini-3.5-transcribe

Gemini 3.5 Live Translate: https://startup-ideas-pod.link/gemini-3.5-live-translate

In this episode, I talk with Vas from Varick about what it takes to put AI to work inside a real company. Vas makes the case that AI pays off through process reengineering, and he walks me through the exact method his forward deployed engineers (FDEs) use: interviews, process mining, step sorting, and agents built inside existing systems of record. We go through real engagements, including a $5B public software company and an accounts payable overhaul that cut the cost per invoice from $31 to $6. By the end, you get a clear picture of the FDE role, the business opportunity behind AI roll-ups, and a five-day plan to start on your own.

Links Mentioned:

FDE Presentation: https://startup-ideas-pod.link/FDE-slides

Vas’s Article: https://startup-ideas-pod.link/vas-fde

Timestamps

00:00 – Intro

01:31 – Sponsor: Google

03:58 – FDE Overview

05:02 – AI Roll-Ups and Process Reengineering

08:04 – The Personal Systems Analogy

09:55 – Understanding a company’s process (step-by-step)

14:11 – Case Study: $5B Software Company

18:11 – 4 Buckets for Every Step

19:04 – Build Inside Systems of Record

21:36 – Case Study: PE Portfolio

23:43 – Selling to C-Suite Executives

27:07 – Process of Mapping Five NetSuite Companies

28:39 – Example: Accounts Payable Process Map

32:54 – Case Study: 60-Person Accounting Firm

34:51 – When to Use Code, Agents, or Humans

36:00 – Choosing AI Models

38:16 – Sidekick vs Background Agents

40:29 – The 3 Skills of a Top FDE

42:25 – Why FDEs Earn So Much

45:26 – Five-Day Starter Plan

47:39 – On-Premise Hardware Demand

48:36 – OpenAI Private Intelligence

50:20 – The Full Playbook

52:01 – Closing Thoughts

Key Points

• AI pays off when you re-engineer the process first, then build agents into it.
• Map the real process with interviews, system-of-record mining, and existing docs.
• Sort every step into four buckets: delete, plain code, agent, or human decision.
• Build agents inside the tools clients already use, like Salesforce, NetSuite, and Slack.
• Sell the outcome each buyer cares about, and prove it with before-and-after KPIs.
• Top FDEs combine domain knowledge, production engineering, AI judgment, and strong communication.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

FIND VAS ON SOCIAL

Varick Agents: https://www.varickagents.com/#hero-section

X/Twitter: https://x.com/vasuman

AI Forward Deployed Engineers: https://learn.varickagents.com/fde-in-30-days

I watched almost 60 minutes of Sam Altman on stage at OpenAI Dev Day 2026. Out of 20-plus launches, I pick the three or four that I think can make people billions of dollars in aggregate. I break down Dots, OpenAI's personal agent platform, plus the Decisions API, the Agents API with computer use, and Sign in with ChatGPT. I also share my four-step framework for building in this world and two business ideas I hope someone takes. If you want to build a business and make money around AI, this episode is for you.

Timestamps

00:00 – Intro

01:48 – Dots, the Personal Agent Platform

03:29 – OpenAI Doubles Down on Plugins

05:02 – Decisions API

06:43 – Agents API With Computer Use

08:01 – Sign In With ChatGPT

12:36 – Where should you build?

13:46 – Idea: Real-World Work APIs

15:04 – Idea: Analytics for Agent Discovery

17:05 –Closing Thoughts

Key Points

• Dots gives plugin builders a front door to 1.2 billion weekly active users.
• OpenAI is doubling down on plugins to make ChatGPT the app ecosystem for AI.
• Sign in with ChatGPT lets users bring their current plan, so a free core app with paid upsells now works.
• Workflows too niche for OpenAI to build become viable businesses.
• The strongest businesses in this world own the trigger, the action, and the feedback.
• Two open opportunities: real-world work APIs and an analytics layer for agent discovery

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I break down the $5 trillion wave of small businesses set to change hands as their owners retire, and why AI agents make this wave a real opening for solo founders. I walk through how Thrive Holdings and General Catalyst buy accounting firms, property managers, and support centers, then run AI agents inside them to lift margins. Then I show how I'd run a one-person holding company: the folder structure, the agent files, the human approval rule, and my average week. I close with the strongest arguments against AI roll-ups, including the one I take most seriously.

Timestamps

00:00 – Intro

01:52 – Why the $5 Trillion Shift Is Happening Now

04:52 – Examples: Thrive Holdings& General Catalyst

08:38 – The Fund Playbook

10:07 – The Small-Deal Gap

10:51 – The One-Person Holdco

14:23 – The Folder Structure

16:47 – The Agent Pipeline

18:38 – Inside a Reviewer Agent File

19:41 – My Week Running the Holdco

21:49 – How to Land the First Business

22:24 – Arguments Against AI Roll-Ups

27:43 – Closing Thoughts

Key Points

• About a million small businesses, part of a $5 trillion shift, are set to sell by 2035 as owners retire (McKinsey).
• AI agents now handle the work these firms run on: data entry, document chasing, status updates, and first drafts.
• The big funds chase bigger deals, which leaves the small firms open for solo founders and small teams.
• A one-person holdco runs on shared agents and rules, plus a GM with real upside at each business.
• A person approves all agent work before it reaches a client.
• The corrections log, turned into rules every week, becomes the most valuable asset in the holdco.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I break down the huge business opportunity because Meta has opened Muse, its personal AI agent, to developers. You can now submit a connector, which lets Muse use your service when someone asks it for help, and I think this could be the app store moment for AI. I explain how a connector works, share four startup ideas you can build on one, and cover how to get customers beyond Meta's directory. I also show how I'd build a first version with a coding agent like Claude Code or Codex, and what I'd test before submitting it to Meta for review.

Timestamps

00:00 – Intro

01:35 – The App Store Parallel

04:55 – How a Muse Connector Works

07:29 – Startup Idea 1: Lead Gen for Business Suppliers

09:28 – Startup Idea 2: Home Repair Dispatch

11:07 – Startup Idea 3: Paddle Match and Court Finder

12:47 – Startup Idea 4: Family Dinner Planning

14:10 – How to pick an idea?

14:56 – How People Find Your Connector

15:32 – Growth Idea 1: Partner With Creators

16:17 – Growth Idea 2: Product-Led Sharing

17:46 – Growth Idea 3: Connected Marketplaces and Directory Placement

19:34 – Building the First Version

21:38 – Custom Connectors and Meta Approval

23:56 – Where to Start This Week

25:31 – Closing thoughts

Muse Connector Prompt: https://startup-ideas-pod.link/muse-connector-prompt

Key Points

• Meta has opened Muse to developers, and a connector lets Muse use your service when someone asks it for help.
• I look closely at the step in a request where someone needs a business that can deliver and money changes hands.
• With a small budget, I'd start with lead generation, because I can show a customer a sample before writing much software.
• I plan distribution around channels I can reach, such as creators, product-led sharing, and connected marketplaces.
• A coding agent can build the first version, and I still inspect the results and test the awkward requests myself.
• To start this week, I'd talk to one type of customer about the last time they dealt with the task.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP

In this episode I speak with Nicholas Cole about the real value of everything you write on the internet. Cole has 15 years of experience as a nonfiction writer and ghostwriter, and he runs the SaaS platform Typeshare. He gives me a simple model with three tiers of content: commodity, personality, and original. He also explains the digital brain, which he calls your personal language model, and he shows how AI repeats your approved language at scale. By the end, you know how to judge the short, medium, and long-term value of a piece before you write it.

Start Writing Online In 30 Days: https://startup-ideas-pod.link/ship30

Timestamps

00:00:00 – Intro

00:03:36 – POV is the Moat

00:05:40 – Language As Open Source

00:11:24 – Value Is Relative To The Reader

00:14:26 – Approved Language

00:17:43 – The Value of AI in Writing

00:22:09 – Commodity Ideas

00:24:23 – How To Set Up The System

00:27:58 – Ownership IS Association

00:33:56 – Build your Personal Data Set

00:39:53 – Branded Content vs Founder-Led Content

00:45:17 – What is Original Content?

00:46:35 – Writing Versus Short-Form Video

00:48:58 – Three Types of Hooks

00:49:50 – Timely Content vs Timeless Content

00:53:27 – Voice is 3 dialed settings

00:56:32 – Finding your Voice

01:00:49 – The Company Brain As The Moat

01:07:30 – Closing Thoughts

Key Points

• A point of view creates the moat, because copycats must wait for your next idea.
• Content sits in three tiers: commodity, personality, and original. Each tier adds different leverage.
• Ownership equals association. Volume builds it, and personality details make it strong.
• Your life story is the unmade data set, so AI learns it only from your own writing.
• Every piece sits on a spectrum from timely to timeless, so match your expectations to the type.
• Humans do the thinking and the writing. Robots do the repeating and the remixing.

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

FIND COLE ON SOCIAL

X: https://x.com/Nicolascole77

Youtube: https://www.youtube.com/@nicolascole77

Ship 30 for 30: https://startup-ideas-pod.link/ship30

In this episode, I talk with Ryan Vogel about Jev, a new type of AI built for classification. Ryan shows how Jev takes an input plus an output schema and returns a probability for each choice in about 200 milliseconds. He demos Jev sorting 1,700 emails for 18 cents total, then covers lead scoring, support routing, video clipping, and browser control. I push him on the startup angle: find a business with an expensive queue of incoming information and put Jev at the front of it. You leave with a clear mental model, real use cases, and a simple way to try it today.

Links Mentioned:

Jev/Typeface AI: https://typesafe.ai

AI Gateway: https://vercel.com/ai-gateway

Timestamps

00:00 – Intro

02:27 – What Jev Is and Why It Matters

04:32 – Email Triage Demo

07:19 – Jev as an AI Decision Maker

15:46 – How to Use Jev in a Business

20:48 – Startup Idea: Local Services Matching and Instant Quotes

22:51 – Use Case 1: Bitcoin Signal Test and Limits

24:03 – Use Case 2: Auto-Clipping Long Videos

25:27 – Use Case 3: Browser Control: Flight Pick in 7.1 Seconds

26:18 – How to Get Access

27:25 – Closing Thoughts

Key Points

• Jev is a classifier: an input and an output schema go in, and a probability for each choice comes out.
• Ryan's demo scores 1,700 emails for 18 cents total.
• Each Jev query takes about 200 milliseconds, whatever the input and output structure.
• Use Jev at any point where a business makes fast, repeatable decisions on incoming data.
• Keep Jev in an advisory role, and save frontier models for high-intelligence tasks like trading.
• Instant access runs through the Vercel Gateway, and a waitlist covers direct access.

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/

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: https://x.com/ryanvogel

Youtube: https://www.youtube.com/@vogeldev/videos

I sit down with Remy to go through Instinct, the new invite-only personal agent that runs inside iMessage. Remy shares his raw chat history on screen: a haircut booking in Copenhagen, a restaurant reservation, a Bali visa on arrival, and an Emirates Skywards sign-up. We cover the parts that impress us, the points where the agent hits a wall, and the privacy questions that stay open. By the end of this episode you understand what Instinct does today, and you get fresh ideas for personal agents in general.

Timestamps

00:00 – Intro

02:08 – Instinct Pros

11:18 – Instinct Cons

13:16 – Simple Onboarding

15:19 – Tools and Connectors

17:43 – Example 1: Booking a Haircut in Copenhagen

20:24 – Example 2: Restaurant Booking and Calendar Entry

23:03 – Example 3: Bali Visa on Arrival and Emirates Skywards

26:00 – Closing Thoughts

Key Points

• Instinct hides the agent complexity behind a phone number and iMessage, so a first-time user starts in seconds.
• Remy gets it to book a haircut, hold a restaurant table, file a Bali visa on arrival, and open an Emirates Skywards account.
• A spend-limited virtual card keeps the blast radius small when the agent pays for things.
• The agent stalls when a task needs a phone app or an Indonesian checkout page.
• Users report that Instinct keeps copies of email after they disconnect Google, so treat privacy as an open risk.
• The trusted person network lets one Instinct talk to another, which builds network effects into the agentic era.

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/

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

X: https://x.com/remy_gaskell

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

AI with Remy: https://www.aiwithremy.com/

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP

I welcome Ras Mic back to the pod to explain the phrase "software factory." Mic shares his screen and walks through the exact system that he runs today. His factory has four steps: isolate, build, prove, and ship. He keeps the whole system in five or six markdown files, so it works with any model and any harness. By the end of this episode, you can boot up your own factory, run many agents in parallel, and trust the code that comes back.

Create your own Software Factory: https://startup-ideas-pod.link/ras-software-factory

Timestamps

00:00 – Intro

02:17 – Software Factory Definition

03:44 – Why the Software Factory Matters

05:23 – Step 1: Isolate With Git Work Trees

11:34 – Step 2: Build With the Code Structure Skill

14:48 – Step 3: Prove With Evidence-Driven Testing

22:25 – Step 4: Ship With Grep Loop and Greptile

26:52 – The Physical Factory Analogy

29:21 – A Software Factory Is Markdown Files

30:02 – Closing Thoughts

Key Points

• A software factory is a workflow of skills and domain knowledge, so it runs with any model and any harness.
• Isolate: every feature starts in a fresh git work tree branched from origin main, so each agent keeps its own station.
• Build: a code structure skill makes the agent write service layer code that a human developer can read.
• Prove: the agent records a before state and an after state as video, screenshots, or numbers.
• Ship: Greptile scores the PR, and the agent loops back to build until it earns five out of five.
• Mic runs up to 15 features in parallel and reviews the visual proof instead of the raw code.

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/

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 talk with Ras Mic about GPT-6 Astra. We skip the game demos and the 3D toys, and we focus on use cases to earn money or improve products. I share 9 Astra prompts that I posted publicly, and Greg Brockman reposted. Ras then shows his hardware project: he moved from a speaker idea to a parts list, a Blender layout, and merged code in about 30 minutes. The takeaway is simple: use this model for the ideas that felt too large for you last year.

Timestamps

00:00 – Intro

01:53 – Astra Overview

04:14 – 9 Astra Prompts

11:48 – Jarvis Speaker Idea

16:21 – Think Bigger with Astra

18:29 – Vibe Coding to Vibe Manufacturing

21:16 – Closing Thoughts

Key Points

• Astra costs more per task, and it uses fewer steps, so the value per dollar stays high.
• A performance audit moved one of Ras’s apps from 800 ms to 20–30 ms.
• A security audit on his live payments app found real risks in production.
• Ras went from a speaker idea to a $561 parts order and a merged pull request in about 30 minutes.
• Ras’s point: intelligence keeps climbing, and bravery stays flat. Ask for bigger things.
• The shift that vibe coding brought to software now reaches physical products.

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/

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 run this episode solo. I explain local AI in plain terms: the model runs on hardware I control, and a cloud model runs somewhere else. I map the four pieces of the local AI landscape — the model, the warehouse, the software, and the workflow — and I define the words that beginners meet first: parameters, tokens, context window, quantization, and GGUF. I walk through the Google open model stack (Gemma 4, Google AI Edge, LiteRT-LM, AI Edge Gallery), compare the other open model families, and show three ways to run a model today. I close with a first workflow you can copy and three startup ideas that use local AI as the wedge.

And a special thank you to Google for supporting the podcast.

Timestamps

00:00 – Intro

01:35 – The Open Model the Landscape

03:09 – Vocab Decoder

06:48 – Google Gemma Clearly Explained

10:29 – Other Open Model Families

14:20 – Path 1: Run Gemma in LM Studio

18:17 – Path 2: Ollama

20:15 – Path 3: Google AI Edge

21:07 – Hardware Cheat Sheet

21:52 – First Workflow to Build

22:47 – Workflows Before Fine-Tuning

25:06 – Local vs Cloud vs Hybrid Eval

26:33 – Framework for Local AI Startup Ideas

27:22 – Startup Idea 1: Home Health QA Reviewer

29:24 – Startup Idea 2: Offline Field Report Copilot

32:10 – Startup Idea 3: Pre-Send Reviewer for Professional Services

34:47 – Build Your Local AI Lab

37:55 – Closing Thoughts

Key Points

• Ask whether the model is good enough for the job, and the business opportunities become clear.
• Local AI has four pieces: the model, the warehouse (Hugging Face), the software (LM Studio or Ollama), and the workflow you build around them.
• Gemma 4 E4B is my practical starting point; E2B fits phones and older machines.
• Hybrid architecture wins: local does the private first pass, cloud does the heavy reasoning, and a human approves anything important.
• Start with one repeated workflow — one folder, one model, one output — and run it 10 times.
• I see a 24-month window to build local-AI-native software for verticals that still run early-2000s tools.

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/

On this solo episode, I review five free, open source GitHub repos that help you build products, make money, or save time: Peter Yang's No AI Slop Skill, the CRM by TryComp AI, Video Use by browser use, SkillSpector by NVIDIA, and Phone Harness. For each repo I explain what it does, why it matters, how to install it, and the first small workflow to try. I close with a simple three-step method: install the repo, make one small workflow work, then decide to productize it or keep it as your own leverage.

Timestamps

00:00 – Intro

01:44 – Repo 1: No AI Slop

05:20 – Repo 2: Agentic-first CRM

10:52 – Repo 3: Video Use

15:15 – Repo 4: SkillSpector

18:49 – Repo 5: Phone Harness

22:25 – Closing Thoughts

Links to repos:

petergyang/no-ai-slop — https://github.com/petergyang/no-ai-slop

trycompai/crm — https://github.com/trycompai/crm

browser-use/video-use — https://github.com/browser-use/video-use

NVIDIA SkillSpector — https://github.com/NVIDIA/SkillSpector

phone-harness — https://github.com/ShawnPana/phone-harness

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/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/