Alle afleveringen
391 afleveringen, van nieuw naar oud
-
SaaS is dead?
29 oktober 2026 · 11 min
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/ Lees meer -
Stop building AI wrappers. Start building agent harnesses.
28 oktober 2026 · 49 min
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 Q… Lees meer -
How to sell AI to Main Street (Full Playbook)
26 oktober 2026 · 44 min
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 traffi… Lees meer -
The 9 Stages of AI Agent Adoption, Explained
21 oktober 2026 · 31 min
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 - htt… Lees meer -
Making $$$ with Meta Muse AI
19 oktober 2026 · 25 min
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 … Lees meer -
Gemini 4 Argon: AI Marketing, 3D Printing and SaaS
15 oktober 2026 · 31 min
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/gisenb… Lees meer -
8 GitHub Repos To Go Viral and Make Money
8 oktober 2026 · 24 min
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 f… Lees meer -
How Will People Make Money in the AI Age?
6 oktober 2026 · 25 min
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/ Lees meer -
Become a $1M/yr FDE (Full Course)
1 oktober 2026 · 54 min
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 buil… Lees meer -
OpenAI DevDay: Dots, Agents & $100B Opportunities
29 september 2026 · 19 min
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. Lees meer
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/
-
$5T opportunity: AI Roll Ups
28 september 2026 · 30 min
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. Lees meer
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…
-
Muse AI Connectors: The Next App Store Moment?
24 september 2026 · 26 min
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. Lees meer
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 Right Way To Write With AI
21 september 2026 · 1 uur 10 min
Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP Lees meer
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/tre…
-
Jev is HERE. How to use it
18 september 2026 · 28 min
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. Lees meer
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
In…
-
Instinct AI: The AI Assistant for normal people
15 september 2026 · 28 min
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. Lees meer
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: http…
-
Building a Software Factory that actually works (Full Course)
14 september 2026 · 31 min
Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP Lees meer
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
… -
You're using GPT-6 Astra WRONG
10 september 2026 · 23 min
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. Lees meer
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
-
Local AI Clearly Explained
8 september 2026 · 39 min
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. Lees meer
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 ve…
-
These 5 Github Repos are a goldmine
2 september 2026 · 25 min
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. Lees meer
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/
-
Making $$$ as a Marketing Engineer
31 augustus 2026 · 35 min
In this solo episode I explain a role that I call the marketing engineer. I believe this person becomes one of the most valuable hires in tech in the next 18 to 24 months. I define the job, I show the four eras of marketing that lead to it, and I give the tool stack that makes it work. I use a commercial HVAC software company as a worked example, and I list six systems that a marketing engineer builds. I close with four ways to earn money from this skill and a 30-day plan to learn it.
Timestamps:
00:00 – Intro
01:46 – The Evolution of Marketing
04:29 – What is a marketing engineer
07:19 – Build the Growth OS
10:18 – Marketing Engineer Tool stack
13:23 – Live Data Workflow
14:32 – Agent Job Description
16:56 – Example: vertical SaaS for HVAC contractors
18:27 – System 1: Customer Truth
20:20 – System 2 - 4: Founder content, Outbound signal and Creative Testing
23:31 – System 5: AI search visibility and the growth cockpit
24:19 – System 6: Eval Loop
25:06 – Ways to Monetize
29:41 – The 30-day plan
32:24 – Closing Thoughts
Key Points
I expect the marketing engineer to command salaries from 250K to more than 1 million dollars.
I build the growth repo first, because it holds the marketing memory of the whole company.
I write a job spec for each agent, in the same way that I write a job description for a person.
I measure qualified replies and pipeline, because business results show the true signal.
I treat taste and judgment as the moat, because agents become a commodity.
I recommend one working system over five half-built ones.
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/ Lees meer -
WebMCP clearly explained (and how to make $$)
26 augustus 2026 · 29 min
Vinny is back on the pod, and he explains WebMCP. WebMCP puts MCP tools inside the browser UI, so any agent that you bring can read a page and act on it. Vinny demos an espresso gear store where his agent compares two machines, checks the counter width, matches accessories, adds an item to the cart, and applies a coupon. Together we map the agent-native options, from headless APIs to in-app agents, and we place WebMCP in the middle of that map. I close the episode with two cash-flowing business ideas that a semi-technical founder can start today. Lees meer
Timestamps
00:00 – Intro
02:28 – WebMCP Clearly Explained
07:22 – Demo: Conditional Tools And Browser Session Login
09:11 – The Agent-Native Paradigm
12:12 – How Agents Interact with Apps
16:05 – Demo: Accessories, Cart, And Coupons
18:42 – Where WebMCP fits
21:03 – Startup Idea 1: WebMCP Conversion Agency
24:27 – Startup Idea 2: Agent Mystery Shopper
26:11 – Closing Thoughts
Key Points
WebMCP makes a website agent-readable and agent-actionable through a short, clear list of tools.
The browser session carries the login, so tools stay conditional and the setup stays simple.
The live store demo compares machines, matches accessories, adds to the cart, and applies a coupon.
WebMCP sits between headless APIs and in-app agents, and it keeps the visual UI that most people prefer.
Vince says WebMCP launched in February as a joint Microsoft and Google experiment in Chrome.
The first markets: complex commerce, SaaS admin consoles, read-only flows in regulated industries, and internal 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: http…
-
Screensharing top takes in AI/startups
25 augustus 2026 · 41 min
On this week’s SIP Live we dive deep on the X timeline to give each post a sip or a skip, and we answer questions from the chat. This episode covers AI-native operations, a baby food app that earns a million dollars a month, iMessage agents, human customer support as a brand advantage, small teams, reading habits, and sales advice for builders. Listeners get concrete first steps, business ideas they can copy today, and two clear opinions on each take. Lees meer
Timestamps
00:00 – Intro
00:59 – Where an AI-Native Company Starts
04:48 – The $1M-a-Month Baby Food App
10:31 – An App Store for iMessage Agents
16:32 – Customer Support Is Eating Engineering
23:38 – RIP to the 2-Pizza Team
26:36 – Paul Graham on Reading as an Advantage
33:31 – The Worst Moves for 2026
37:01 – From Designer to Salesperson
Key Points
Make the company legible first: keep meeting notes and SOPs in files that an LLM can read.
Let the team explore AI tools freely, then ask one department, such as admin, to lead.
A million-dollar-a-month app leaves room for niche copies that earn 10K to 30K a month.
Build loops that turn daily support transcripts into prototypes and measurable goals.
Human support works as a marketing advantage, and premium buyers pay for it.
Sales stays part of the owner's job, so learn the frameworks and start cold calling.
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:…
-
Grok Bot: make a 1 person company with agents
21 augustus 2026 · 44 min
I sit down with Billy Howell for an inside look at a real business that runs on Grok Bot agent teams. Billy tests hundreds of tools for The Rundown, and he uses Grok Bot to run his local newsletter, The Arlington Bagel, which goes to 6,000 readers every Thursday. He walks me through his chief of staff bot, his research and sales agents, and the routines that move work forward while he sleeps. We cover the token math, the four-week plan he follows, and the business models that fit this tool best: newsletters, directories, and Shopify stores. You leave with a setup you can copy for one project this month. Lees meer
Timestamps
00:00 – Intro
02:22 – Grok Bot Overview
03:12 – What makes GrokBot special
06:09 – Pick one project
08:09 – Creating your initial agent team
11:19 – First week sprint with Grok Bot
13:06 – Automated Routines within Grok Bot
15:51 – Agent Org Structure
17:35 – Best Practices for building Agents
19:45 – Newsletter playbook
21:12 – Plugins
22:24 – Newsletter playbook pt 2
25:43 – Sales agent
29:06 – Iterating and Improving Agents
33:34 – Grok Bot business ideas
36:45 – Site stack builder
38:36 – Directories and landing pages
41:42 – One project for a month
42:50 – Closing Thoughts
Key Points
Keep one project per Grok Bot account, so context stays clean and tokens stay available.
Start with a chief of staff bot, and let it audit your business and name the first three agents.
Follow the four weeks: build the team, execute, hire and fire, then automate.
Ask each agent for a five-line brief: what shipped, what is stuck, what needs you.
Move repeatable steps into scripts or make com, and keep agent tokens for high value work.
Newsletters and directories give the easiest entry, and the two models feed each other.
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, app…
-
You need to be skillsmaxxing (10x your Claude/Codex)
19 augustus 2026 · 32 min
Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP Lees meer
I talk with Remy, known online as AI with Remy, about agent skills and how to share them across a whole team. Remy explains that a skill is an SOP for AI: a markdown file that teaches Claude your exact way to do a task. He then shows his system. He keeps his team skills in one GitHub repository, and he installs that repository as a plugin in Claude Code and Codex. The result is one source of truth, automatic updates for everyone, version control, and company ownership of the work. Listen to this episode if you run daily tasks with agents and you want your whole team to get the same quality of output.
Remy’s prompt + skill setup: https://startup-ideas-pod.link/Remy-skills
Timestamps
00:00 – Intro
02:33 – Skills as SOPs for AI
04:27 – How the agent uses skills
05:13 – AI is single player
06:21 – Example Skills: Notion, Brand Voice, Email
08:07 – How to share skills
11:40 – What is a Plugin?
14:58 – Anatomy of a Plugin
15:30 – Version Control and Rollback
16:58 – A Second Repo for Personal Skills
18:29 – The Day Claude Deleted 150 Skills
20:02 – Skills as Company Assets
21:00 – A Web App on Top of the Repo
24:46 – How Many Skills to Build
27:00 – The Self-Improvement Loop
28:15 – Skill Maxxing
30:40 – Closing Thoughts
Key Points
A skill is a markdown SOP that teaches an agent your exact way to do a task.
Most skills sit on one laptop, so a great process stays with one person.
A GitHub repo plus a plugin gives the team one source of truth for every skill.
Auto-update sends each skill edit to every teammate in Claude Code and Codex.
A company-owned repo keeps the skills when a teammate moves on.
Remy builds thin agents and thick skills, so any harness can run the same process.
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://latechec…
-
How to use Claude Code better than 99% of People
17 augustus 2026 · 48 min
Get Claude Code: https://startup-ideas-pod.link/claude-greg Lees meer
In this solo episode I lay out the exact system I use to turn Claude Code into what I call an AI employee. My premise is simple: give Claude the same things you would give a person joining your company (a workspace, memory, a brief, a clear ticket, eyes, review, a schedule, and permissions). I build the whole setup live around a real idea I found on ideabrowser.com , a missed-lead responder for med spas, and I share the specific prompts I use at each step. By the end, the product, the customer feedback, the docs, the demos, the reviews, and the recurring work all live inside one operating loop. I close with a seven-day plan you can run at your own pace. And thank you to Claude and Anthropic for supporting the podcast.
Setup Claude Code to be your 24/7 employee: https://startup-ideas-pod.link/Claude-code
Timestamps
00:00 – Intro: The AI Employee Map
05:47 – Step 1: Creating The Workspace In Claude Desktop
14:53 – Step 2: The Brief And Plan Mode
18:08 – Step 3: The Ticket And Defining Done
22:15 – Step 4: The Eyes And Desktop Preview
26:13 – Step 5: Review In Layers And The Diff View
29:34 – Step 6: The Schedule And Routines
34:32 – Step 7: Parallel Agents And Worktree Isolation
39:14 – Step 8: Permissions: Safe, Ask First, Human-Owned
41:15 – Step 9: Skills, Connectors, And Hooks
44:28 – The Seven-Day Plan
47:42 – Closing Thoughts
Key Points
I treat Claude Code like a new hire: workspace, memory, brief, ticket, eyes, review, schedule, permissions.
The repo brain teaches Claude how I work and what good looks like.
Plan mode comes first: Claude reads the context, proposes an approach, and waits for my approval.
One ticket at a time means one task, one finish line, and one reviewable change.
The eyes matter: Claude opens the app in desktop preview, clicks the flow, checks the console, and reports what a buyer experiences.
Routines and permissions turn a chat tool into a 24/7 operator with…
-
How to Build an AI-Native Company in 2026
12 augustus 2026 · 48 min
I sit down with Allie K. Miller to talk about the shift from managing AI agents to enabling them. Allie runs a workforce of 34 AI agents led by an AI chief of staff named Simon, plus six directors named after Friends characters. She shares her three-word prompt, her daily AI diary, her AI watchdogs, and her rule to build the factory before the product. We then debate the future of software: why enterprises still want a vendor to call, and why consumer software now rewards taste and distribution. Listeners leave with one mindset shift and a first step they can finish in under three hours. Lees meer
Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP
Timestamps
00:00 – Intro
02:29 – Become a Great Agent Manager
04:49 – The Three-Word Prompt
08:12 – The Pyramid of Proactivity
12:23 – Making the Company Queryable
19:14 – How to Design an AI Workforce
22:25 – AI as a Watchdog
24:56 – Startup Opportunities
26:29 – Build the Factory, Then the Product
30:09 – The SaaS Question
34:53 – Consumer Software as Art
37:12 – High-Value Bottlenecks
44:56 – Closing Thoughts
Key Points
Allie sits three rungs above her 34 agents. She sets the infrastructure and waits for escalations.
Her strongest prompt runs three words on top of full business context: do smart things.
She holds the risk tier steady and expands only the breadth and scope of agent work.
A dictated daily diary captures the context that lives outside meetings, email, and Slack.
AI watchdogs remain wide open: duplicate work, calendar conflicts, and meeting disagreements.
The bigger play is a software factory. Build the primitives once, then ship each product faster.
I see opportunity on both sides of software: enterprises want a vendor to call, and consumers reward taste.
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 wi…
-
Making $$$ selling to AI Agents
10 augustus 2026 · 34 min
In this solo episode I break down Cloudflare's AI agent announcement in plain English and explain why I see it as the new business model for the internet. I walk through AI crawl control, pay per crawl, the monetization gateway, and the x402 payment rail, and I show how a single request turns into a transaction. From there I give three startup ideas built directly on top of this shift: a niche data refinery, agent readiness for businesses, and expert archives turned into agent tools. For each idea I lay out the wedge, the first customer, the first version, and how I would sell it. My core claim: the internet is moving from pages humans visit to resources agents use, and the builders who move now own the doors. Lees meer
Timestamps
00:00 – Intro
01:01 – The Old Paradigm of the Internet
02:57 – The New Paradigm of the Internet
03:41 – What Cloudflare is actually doing
06:33 – An AI Index for all our customers
07:34 – The Agent Internet Stack
09:09 – Why Now Is the Best Time to Build
10:29 – Startup Idea 1: The Niche Data Refinery
17:10 – Startup Idea 2: Agent Readiness for Businesses
23:43 – Startup Idea 3: Expert Archives as Agent Tools
30:36 – The Filter for Finding Ideas
32:33 – Closing Thoughts
Key Points
The human web monetized attention; the agent web monetizes useful resources, priced per request.
Cloudflare's pay per crawl, monetization gateway, and x402 turn the HTTP 402 status code into a live checkout at the edge.
Idea 1: refine one niche's messy data into clean fuel for agents, starting with 100 businesses in one city.
Idea 2: sell agent readiness by showing a founder exactly what AI says about their company today.
Idea 3: package an expert's archive into one job-specific agent tool the audience already wants.
Every one of these works as a manual services business today and productizes as agent payments mature.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growing startups build their fu…
-
These AI Marketing Agents Get You Customers
5 augustus 2026 · 44 min
I bring Cody Schneider back on the show to build two marketing agents end to end, live. The first one monitors LinkedIn posts from creators in your category, scrapes everyone who engages, waterfalls those profiles into emails and phone numbers, and then runs cold email and LinkedIn DMs with an agent managing the replies. The second one turns internal conversations, sales calls, and podcast transcripts into a daily organic LinkedIn content engine across an entire team. Cody names every tool in the stack, shares the real infrastructure costs, and shows the actual terminal commands he runs in Claude Code. By the end you have two systems you can go set up today for your startup. Lees meer
Timestamps
00:00 – Intro
02:27 – Agent Number One: Cold Outbound Agent
04:26 – Finding Creators in Your Category on LinkedIn
09:09 – Apify Explained and the API Maestro Actors
10:59 – Extracting Engagers Live in Claude Code
12:59 – Agent Versus Automation
15:45 – Waterfall Enrichment: GitLeads, Apollo, Origami
17:13 – Compliance, Data Brokers, and What Stays Legal
21:40 – Waterfall Enrichment: Million Verifier and LeadMagic
25:38 – The Cold Outbound Infrastructure
28:33 – Software Factories and Marketing as Code
31:41 – Agent Number Two: The Organic LinkedIn Engine
39:34 – Earned Media Math at $22 CPM
42:31 – Closing Thoughts
Key Points
LinkedIn engagement is a hand raise, so it beats firmographics as a targeting signal.
Ten to twenty source accounts give you roughly 80% surface area coverage of an industry.
Waterfall enrichment moves cheapest to most expensive: GitLeads, then Apollo, then Origami or Prospeo.
Roughly $200 a month covers sending software plus inboxes for about 10,000 cold emails.
An agent here is plain code on a cron job with an LLM attached where judgment is needed.
Organic content works best when it starts from real human source material like calls, Slack, and transcripts.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps …
-
Graph Engineering Clearly Explained
3 augustus 2026 · 26 min
I go solo on this one to break down graph engineering, the term I keep seeing go viral on X. I define it in plain English: prompt engineering is how you ask AI a better question, context engineering is how you give AI better information, and graph engineering is how you design the work around the AI so it lives as a managed workflow instead of one giant chat. I walk through the vocabulary (jobs, arrows, state), separate knowledge graphs from agent graphs, and run a full worked example on whether to launch an AI bookkeeping product for Shopify merchants. Then I show three levels of implementation, from manual lanes on a whiteboard up to LangGraph and n8n, plus ready-made graphs for support, content, and code. You leave with a repeatable way to turn one AI workflow you already run into a map of steps, checks, handoffs, loops, and human approvals. Lees meer
Timestamps
00:00 – Intro
01:24 – Prompt Engineering, Context Engineering, Graph Engineering
02:50 – Chat vs Graph
03:35 – Defining Terms and Workflows
06:44 – Knowledge Graphs vs Agent Graphs
08:47 – When to use Graph Engineering
10:01 – Example: AI Bookkeeping For Shopify Merchants
13:22 – The Diamond Pattern Graph Visualized
15:10 – Three Levels of Implementation
17:14 – Customer Support Graph
18:45 – Content Creation Graph
19:30 – Coding Graph
20:42 – The Trap Of Oversized Graphs
22:22 – Building Your First Graph
24:53 – Closing Thoughts
Key Points
Graph engineering means designing the work around the AI: jobs connected by arrows, with shared state moving between them.
Knowledge graphs help AI understand how information connects; agent graphs help AI understand how work should move.
Reserve a graph for work with multiple steps, multiple sources, parallel paths, checks, risks, or approvals.
Separate the writer from the checker, since a single model grading its own answer inflates confidence.
Draw and run the graph manually first; add LangGraph, n8n, or Make com once the structure proves itself.
Aim f…
-
Jack Dorsey's Buzz: The New Hermes Agent?
29 juli 2026 · 39 min
I sit down with Vinny for a live tour of Buzz, an open source, agent-native chat app from Block built on an open protocol. Vinny makes the case that openness is the real story here: agents arrive as first-class teammates, the harness underneath each agent swaps freely between Claude Code, Codex, Goose, and open code, and your entire chat context travels with you through every swap. He demos real output, including a CRM app built with the Wasp full stack framework and deployed to Railway, plus a tweet leaderboard that pipes daily stats back into a channel through a public API. I press him for the honest state of the software and for the setup advice he actually uses day to day. By the end I share where I land on Buzz versus Slack, and why I think anyone building right now gains from putting their hands on tools like this. Lees meer
Timestamps
00:00 – Intro
02:57 – Agents as First-Class Team Members
03:49 – Swappable Harnesses Under Any Agent
06:55 – Audio Huddles With Agents
08:34 – Git, Feature Branches, and Parallel Worktrees
11:20 – Building a CRM App with Buzz and Agents
13:43 – Why This Matters
18:13 – Best way to engage with your Agents
23:53 – Shared Compute and Local Models
25:42 – Model Choice, Data Ownership, and Lock-In
27:36 – Context as the Foundation
29:39 – Setting Up Agents
31:21 – Skills and Speed
33:03 – Who Should Try Buzz Today
34:36 – My Take: Live in the Future
38:10– Closing Thoughts
Key Points
Buzz treats agents as members of your team, so one shared chat becomes the context layer for humans and agents together.
The harness under any agent swaps freely, and every chat, project, and decision comes along for the ride.
Globally installed agent skills stay available inside Buzz, so an existing Claude Code setup carries straight over.
Agents branch, work in parallel worktrees, push to Git hosting on your own relay, and ship live apps end to end.
Shared compute lets a small team run one local model on one machine and use it from many c…
-
How I use Claude Code + MCPs to run my marketing
27 juli 2026 · 38 min
Cody Schneider is back on the podcast, and I ask him to lay out what a real marketing agent looks like once you get past the hype. He draws a hard line: an agent owns unified business data, runs on a cadence, and improves from the results it reads back. We use one concrete business as the sandbox — an AI-first product built on top of WordPress — and Cody walks the entire stack behind a Facebook ads agent that researches pain points, generates static and video creative, publishes through the Facebook Marketing API, kills the losers, and promotes the winners. You leave with a business idea, the exact infrastructure list, and the tools we use to run it today. Lees meer
Timestamps:
00:00 – Intro
01:54 – Defining a Marketing Agent
04:00 – Startup Idea: AI for WordPress
07:27 – AI-First Plugin Ideas: Yoast, WPForms, WooCommerce, Akismet
09:55 – The current state of Meta Ads
12:48 – Bundling the Stack and Choosing Channels
15:23 – Two creative pipelines: static and video
17:25 – The Data pipeline and warehouse
24:11 – Ad strategy
25:51 – Solving for Entropy
28:01 – Let the market pick the winner
34:26 – Closing Thoughts
Key Points
WordPress powers 43% of all indexed websites, which leaves a wide open lane for AI-first products built on that stack.
A marketing agent earns the name when it owns live data, runs on a cadence, and learns from its own results.
The infrastructure comes down to three pieces: a pipeline (Airbyte), a warehouse (ClickHouse), and cloud hosting (Heroku, Railway, or similar).
Facebook's Andromeda algorithm reads your creative and your landing page, so the ad copy now carries the targeting.
Fresh inputs — competitor ad libraries, YouTube transcripts, podcast transcripts — keep agent creative varied over time.
Paid ads let you test a thousand angles and read the market's verdict inside 48 hours.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growing startups build their future - from War…
-
Most Valuable Skill of 2026: Managing AI Agents
24 juli 2026 · 45 min
I welcome Ryan Carson back to the show to turn anyone into a world-class agent operator. Ryan spent 25 years founding companies, scaled Treehouse to around 110 employees and a million learners, and now runs Untangle, an AI divorce agent for family law firms, as a team of one while his revenue tracks toward 4x this month. He walks me through his full stack: running cloud agents in parallel, building automations that watch production and improve themselves, and shipping 22 to 40 PRs a day, often from his phone. We also get into keeping token costs sane through model routing and building a durable reputation by sharing your work on X. By the end, listeners hold a clear playbook to run agents, automate the busywork, and ship faster. Lees meer
Timestamps
00:00 – Intro
01:43 – The New Agent Paradigm
04:24 – Inside Ryan’s eight-screen desk setup
07:23 – Why Devin and cloud agents
10:00 – Everyone Is Now a Manager of Agents
13:15 – Local vs Virtual Development
14:50 – Agent Management System
24:22 – 3 Automations to build
32:54 – Self-improvement loop with Grace
34:38 – Token costs and model routing
40:33 – Building reputation on X
44:03 – Closing thoughts
Key Points
Ryan frames every knowledge worker as a manager of agents, and mastering that role is the new edge.
Cloud VMs let Ryan run five to ten agents at once and ship 22 to 40 PRs a day.
Roughly half of Ryan's work happens on his phone, which keeps his agents moving in real time.
Automations like a production watchdog and a daily self-improvement loop hand Ryan a running summary of what matters.
Model routing keeps costs in check: budget around $5k a month per employee and lean on cheaper fine-tuned models.
Sharing your work publicly on X compounds into relationships and opportunities over time.
Numbered Section Summaries
Meet Ryan and Untangle Ryan Carson returns to walk me through his stack. He spent 25 years founding companies, scaled Treehouse to about 110 employees and a million learners, and now runs…
-
FDE: The $1M/Year AI Job Explained
20 juli 2026 · 52 min
I sit down with Vas from Varick Agents to map out exactly how to break into AI forward deployed engineering — and how to grow into a sharper FDE — in thirty days. We start from a single premise: every company can now buy the same frontier intelligence, so the real advantage moves to deployment. Vas traces the role back to Palantir, explains the judgment that decides where AI belongs, and lays out the audit → evals → deployment loop that turns raw models into measurable business value. He then hands over a full 30-day plan to build, harden, measure, and defend a production-grade agent, so you can do the job before you hold the title. The whole conversation stays tactical and grounded, with clear examples I can apply today. Lees meer
The FDE Blueprint: https://startup-ideas-pod.link/fde-starter
Timestamps
00:00 – Intro
02:03 – What is an FDE
04:09 – How Palantir Popularized FDEs
06:16 – Deciding Where Intelligence Belongs
11:26 – What FDEs Earn
14:59 – Two Kinds of Judgment: Communication and Engineering
17:38 – How the Work Really Gets Done
20:40 – Audit, Evaluation, Deployment
22:56 – Which LLM to Choose
27:36 – Audit: Finding the Workflow Worth Rebuilding
31:47 – Evals: Turn non-determinism into evidence
32:57 – Deployment: Build on Existing Systems
38:59 – The 30-Day Plan Begins
49:13 – Final Thoughts
Key Points
Intelligence is now commoditized, so the real edge lives in deployment — the job of the AI forward deployed engineer.
Vas traces the FDE role to Palantir, where engineers embed on-site, learn workflows, and customize the ontology per client.
The strongest FDEs blend deep technical skill with consulting-grade communication — the rare "art plus science" combination worth up to a million dollars a year.
The FDE loop runs audit → evals → deployment, and each improved workflow makes the next one clearer.
Vas condenses a year of learning into a 30-day plan: build an agent, harden it, make it measurable, then defend it like an FDE
The #1 tool to fin…
-
The $1,000/hour Solo AI business (Full Course)
15 juli 2026 · 1 uur 1 min
In this episode I sit down with Corey Ganim to unpack what he calls the simplest way to earn money with AI in 2026: a $999 AI Tools Assessment for small business owners. Corey lays out his entire four-phase system, from a probing discovery call through an AI-assisted analysis in Claude, a stupid-simple client report, and a review call that turns roughly half of clients into implementation buyers. We walk through his full upsell menu, seven client-acquisition methods that run on zero capital and zero audience, and his AI Concierge retainer that earns him about $1,000 an hour. Anyone listening leaves with a copy-and-paste playbook they can adapt to their own city or industry. Lees meer
Checkout Corey’s AI Audit Template: https://startup-ideas-pod.link/ai_audit
Timestamps
00:00 – Intro and the episode promise
03:48 – The full playbook preview
06:39 – Phase 1: the discovery call
08:27 – Phase 2: AI Analysis
12:11 – Phase 3: The Report
22:24 – Tool and Model Selection
23:39 – Phase 4: The Review Call
26:15 – The Upsell Services
35:52 – Finding Customers
49:16 – The AI Concierge retainer
58:46 – Final Thoughts
Key Points
The core offer is a $999, 45-minute AI Tools Assessment that prescribes 3–7 off-the-shelf tools, backed by a full-refund guarantee tied to finding at least five reclaimed hours per week.
Fulfillment runs in four phases: discovery call, AI analysis in Claude, a templatized report, and a review call that converts about half of clients into implementation work.
The report stays deliberately simple, with an executive summary, an effort-versus-impact matrix, quick wins, a four-day quick-start plan, and a clear ROI slide.
The upsell menu spans process redesign, automation builds, knowledge systems, custom workflows, and full implementation, with lifetime value reaching $3K–$10K or more.
Seven client-acquisition methods run on zero capital and zero audience, from local meetups and door knocking to agency partnerships and office hours.
The AI Concierge…
-
Making $$$ with Loop Engineering
13 juli 2026 · 40 min
I sit down with Elie Steinbock to unpack loop engineering and how to run a business on loops. We start with the roots of the idea in the lean startup and Toyota's manufacturing, then move into practical, copy-ready workflows for SEO, Facebook ads, and product feedback. Elie walks through a live Google Search Console example on Draft Fantasy and shows how to set up an SEO loop that runs once a month for years. The core promise for listeners: hand repeatable business work to an AI agent that measures an objective metric and improves over time. By the end, you know how loops work and how to launch your first one today.
Timestamps
00:00 – Intro and episode promise
02:54 – What is Loop Engineering
06:51 – Loops with AI agents: build and verify
11:17 – Example of Loop: SEO as an objective-metric loop
15:29 – Setting up the SEO loop and tools
25:27 – Cost and token economics
29:05 – The Paid ads loop
33:10 – The product feedback loop
36:25 – A minimal viable loop for every channel
39:21 – Closing Thoughts
Key Points
Loop engineering means giving an agent a task, an objective metric, and a stop condition so it improves on a schedule.
The lean startup and Toyota's build-measure-learn cycle map directly onto AI agents.
An SEO loop connects to Google Search Console and Data for SEO, then pushes rankings up month over month.
These loops run cheaply — often a few dollars per monthly run — which beats the cost of an agency.
The same pattern extends to Facebook ads, and a product feedback loop stands as the ultimate version.
Start small with a minimal viable loop tied to a clear metric like impressions or ten likes.
Numbered Section Summaries
The Promise of Running a Business on Loops I open by asking Elie what listeners will walk away with, and he frames the whole episode: use loops to automate SEO, ads, and more. We agree the aim is clear, copyable workflows people can launch today.
Where Loop Engineering Comes From Elie traces the recent buzz to Boris from Claude Code and Pete… Lees meer -
Grok 4.5 is a bigger deal than Fable
11 juli 2026 · 56 min
In this episode I bring Nick Vasilescu, co-founder of Orgo, back on the show to unpack the buzz around Grok 4.5. Nick makes the case for treating Grok 4.5 as a genuine AI co-founder inside harnesses like Hermes and OpenClaw, and he proves it live: spinning up cloud computers, wiring in tools, and building a full startup from idea to landing page to outreach. We race Grok 4.5 against GPT 5.6 Sol, tour Nick's agent stack, and talk through the cost paradox of a model this fast and cheap. Listeners walk away with a concrete playbook for standing up their own always-on agent today.
Get Nick’s Agent Template Stack: https://startup-ideas-pod.link/nicks-stack
Timestamps
00:00 – Intro
01:40 – Why Grok 4.5 release matters
03:39 – Automation versus a co-founder
05:16 – Setting up Hermes and Grok 4.5 on Orgo
09:01 – Why Orgo to manage Agents
11:23 – Grok 4.5 Cost discussion
14:02 – Grok 4.5 Fast Execution and Unlock
16:20 – The Agent tool belt
19:13 – X MCP for trends
20:37 – vidIQ for outliers and thumbnails
22:11 – Finding new startup ideas
26:15 – Grok 4.5 versus GPT 5.6 Sol
30:56 – Ranking and Reviewing the startup ideas
34:06 – The AI agency opportunity
38:46 – Thumbnails over Telegram
40:10 – Reviewing AI Agency Landing Page
41:58 – Vertical MCPs and agent startups
43:36 – Skill graph and the offer
45:25 – Reviewing the Thumbnail Generated
46:42 – Email Outreach Campaign
48:07 – Reviewing Market Insight 1-Pager
50:45 – From a Camry to a Ferrari
52:12 – Reviewing Cold Email Outreach Sequence
53:22 – Closing thoughts
Key Points
Grok 4.5 delivers Opus 4.8-level intelligence at a fraction of the cost and roughly 10-15x the speed of Fable.
I learn to treat the model as a co-founder by handing it email, a phone number, a debit card, memory, and every connector that matters.
Nick runs agents on Orgo cloud computers so they stay online, textable, and ready around the clock.
Live, Grok 4.5 builds a landing page in about 40 seconds and wins on design and copy for me over GPT 5.6 S… Lees meer -
We Tested OpenAI's GPT 5.6 for a Month
9 juli 2026 · 49 min
In this episode I sit down with Dan Shipper to see how he runs his work and personal life on OpenAI's Codex Desktop with the 5.6 model. He walks through his card-based email setup, daily feeds for his company and Slack, and the in-app browser that lets his agent collaborate with him inside tools like Proof. We build a small SaaS app live, called Turnaround, and use it to explore why maintenance is the real product in the AI era and where Codex-native software heads next. Along the way Dan shares his pirates-versus-architects framing, his approach to fine-tuning a copy-editing model, and the patterns — pulses, Mailroom, and router threads — that hold his system together. The throughline: pick one simple win, let context do the heavy lifting, and manage the system instead of running every task by hand.
Learn how to get customers with AI Agents: https://startup-ideas-pod.link/GTM-agents-IB
Timestamps
00:00 – Intro
01:16 – Codex and GPT-5.6 Overview
03:40 – Training your own model: the step after skills
04:49 – Automating Email, Slack, Meeting Notes with GPT-5.6
08:53 – Why GPT-5.6 sharpens the results
10:26 – The light bulb moment with Codex
15:05 – Building Turnaround live: a maintenance badge
18:00 – GPT-5.6 vs. Fable: A tier and S-plus tier
19:34 – LFG and goal: looping toward a finished build
24:28 – Huge Opportunity: Codex-native apps
29:33 – The design checkpoint and the "warm paper" quirk
31:32 – Local models
34:04 – From 70% to 100%: pirates and architects
37:22 – Mailroom: giving Codex its own email address
40:58 – Getting started: download, grant access, explore
43:07 – Record and Replay: turning tasks into skills
44:37 – Closing Thoughts: Start small and build over time
Key Points
Codex Desktop plus the 5.6 model runs as a full operating system for knowledge work — email, research, and building software from one surface.
Context is the multiplier: an agent wired into your computer and the web turns every inbox and feed into cards with a clear next action.
M… Lees meer -
AI Agents are the new SaaS
1 juli 2026 · 26 min
In this solo episode I lay out why I believe building agents is the new SaaS: software is shifting from helping you do the work to doing the work with you. I walk through a full playbook — find a niche, pick a workflow with a paycheck attached, shadow the human, spec the agent, build the minimum useful version, sell a pilot like labor, then productize the repeatable parts. I share live market examples like Slang AI for restaurants and Same Day for home services, plus pricing models and a distribution strategy built on workflow teardowns. I close with a 30-day, zero-to-100 plan for launching an agent-first business. This one is for anyone eager to build with AI or simply become more productive. Lees meer
Timestamps
00:00 – Intro
01:38 – Building Agents is the new SaaS
04:11 – Pick a valuable workflow
06:12 – Shadow the Human First
09:34 – Build the Minimum Useful Agent
12:50 – The wrapper makes it SaaS
15:50 – Sell the Pilot Like Labor (and Pricing)
18:37 – Own the workflow
21:45 – The Zero-to-100 Plan in 30 Days
24:14 – Closing Thoughts
Key Points
Agent SaaS sells work as a service; the product is the job itself, priced like labor.
Start with a workflow that already carries a paycheck: high frequency, clear finish line, existing software, learnable edge cases, and felt pain.
Shadow a human across 10–20 real jobs before you write a single prompt — the detail is the product.
Ship the minimum useful agent — draft-and-approve, triage, coordinator, or bounded action — and earn autonomy over time.
The wrapper (logs, approvals, evals, analytics) creates trust and turns automation into real SaaS.
Win distribution with workflow teardowns: show the old way, show the agent way, sell the painkiller.
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.…
-
“Learn AI” Is Bad Advice. Learn These Instead
25 juni 2026 · 30 min
In this solo episode, I lay out the six skills I believe stay valuable as AI grows more capable. I chose these six because each one is open to anyone, each one starts this weekend, and each one rises in value as AI improves. I walk through agents and local models, distribution, robotics, curation, the builder distributor, and IRL community building, with one concrete first rep for every skill. My goal is to hand you one simple, clear map of where the world is heading and exactly how to begin. Lees meer
Timestamps
00:00 – Intro
00:57 – Skill 1: Running AI Agents and Local Models
04:51 – Skill 2: Marketers Who Build Distribution
09:03 – Skill 3: Robotics Engineers Who Build and Source Hardware
14:29 – Skill 4: Curators Who Yap and Make Short-Form Video
19:05 – Skill 5: The Builder Distributor
23:11 – Skill 6: IRL Community Builders
27:34 – Build Your Skill Stack
Key Points
I chose these six skills because each one rises in value as AI improves.
Skill 1 is the grown-up version of prompt engineering: I design an AI worker with context, tools, memory, permissions, and a goal.
Distribution beats posting, so I learn where attention already lives and turn it into trust before I sell.
Hardware is the new frontier: cheap arms, open-source robot learning, and supplier sourcing put robotics within my reach.
As the builder distributor, I ship the product and win the attention in one loop, which makes the one-person company real.
Real rooms grow scarce and valuable, so I build belonging, trust, and context as my edge.
Numbered Section Summaries
The Premise: What Stays Valuable as AI Improves I open by picturing a near future where AI builds and writes almost anything, then ask which skills hold their value. I narrow it to six skills that anyone can start this weekend, each one climbing in value as AI gets better.
Skill 1 — Agents and Local Models I describe the move from typing prompts to designing a small AI employee with context, tools, permissions, memory, a goal, an…
-
GLM 5.2 Clearly Explained (and how to set it up)
23 juni 2026 · 23 min
In this episode I sit down with Amir to get tactical about running local AI models as part of a daily workflow. We center on GLM 5.2 from ZAI, how it stacks up against frontier models like Opus 4.8, and how a fusion approach lets you sequence a heavy thinking model with a lighter execution model for the best output at the lowest cost. Amir walks through setup in Cursor and Codex via OpenRouter, shares real token-cost math, and demos GLM 5.2 refining a live app. By the end you will know how to start today, where local models shine, and how model chaining keeps spend in check. Lees meer
Timestamps
00:00 – Intro
02:09 – GLM 5.2 and Z AI
04:01 – Specs: 1M context and Terminal Bench 2.1
05:22 – Making sense of benchmark scores
06:42 – Setup in Cursor or Codex with OpenRouter
10:18 – Local model upside: buy a machine, run tasks
11:42 – Token cost: 44 cents versus $2.38
13:36 – Future-proofing with an upfront hardware bet & The Uber subsidy analogy
16:49 – Model chaining and the vision workaround
19:23 – Token maxing vs routing tasks to the right model
20:54 – Answering the "cost is irrelevant" crowd
21:59 – Closing thoughts
Key Points
GLM 5.2 ships with a 1M-token context window and scores 81 on Terminal Bench 2.1, landing about four points behind Opus 4.8.
A fusion approach (a term OpenRouter coined) sequences models: plan with Opus, execute with GLM 5.2, review with Composer 2.5 or Codex 5.5.
Running GLM 5.2 in the cloud through OpenRouter costs roughly 44 cents for a task that runs about $2.38 on Opus 4.8 — close to a 5X saving.
You can start today with credit-based access: load $20 in OpenRouter and route tasks to the right model.
For images, Amir uses Opus 4.8 to read screenshots and describe them, then hands the layout to GLM 5.2 to act on.
Teams are shifting from token-maxing to output-maxing, making model governance and chaining the smart play
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growin…
-
Making $$$ with IOS apps
15 juni 2026 · 48 min
In this episode I sit down with George Lampropoulos, a 19-year-old founder who turns AI-built mobile apps into real revenue. George walks through his framework for reaching $10K a month—roughly $333 a day—starting with a simple, sellable idea you actually care about and ending with a distribution plan anyone can run. He shares the numbers behind WrestleAI (100K-plus downloads and close to $200K in revenue) and explains why a sharp "gotcha feature" and a clean Instagram funnel do most of the heavy lifting. We also dig into closing influencers, hiring a VA, running paid ads, and reading the metrics that decide whether you grow. If you want a practical, founder-tested playbook for building apps with AI, this one delivers. Lees meer
George’s $10K/mo app playbook: https://startup-ideas-pod.link/George-app-playbook
Timestamps
00:00 – Intro
01:54 – George's track record with WrestleAI
02:36 – How AI unlocks fresh app ideas
06:29 – Reverse-engineering a viral idea from your feed
16:16 – Designing the UI/UX of the app
17:49 – The gotcha feature that sells the app
21:25 – Onboarding that converts
23:04 – Actionable Plan to $10k/mo
28:55 – Outreach as a numbers game
33:35 – Paid ads clearly explained
36:20 – Reading metrics: conversion, ARPU, retention
38:30 – TLDR: a great product earns inbound creators
39:51 – Answering the vibe-coding skeptics
39:51 – Scaling with vibe-coded app
43:35 – Why now is the app-building boom
46:05 – Closing Thoughts
Key Points
I learn why a simple, sellable idea you're passionate about beats pure distribution every time
George breaks down the "gotcha feature"—one feature so clear that five seconds explains the whole app
We cover a clean Instagram page that doubles as a sales funnel and as social proof for recruiting creators
George shares his influencer playbook: lead with relationships, close on a call, and aim for a $2 CPM
I get his paid-ads starter method—5 to 15 creatives, $100 a day, then keep the winners.
George explains the…
-
Claude Fable 5 is BANNED. What to do?
13 juni 2026 · 25 min
In this solo episode, I walk through the implications of the ban of Claude Fable 5 — the most powerful model on the planet and the one I planned to build with — after the US government sent Anthropic a letter. I make the case for local AI by walking through the benefits: intelligence that lives on your own hardware, stays private, runs free after the hardware cost, and keeps working through bans, outages, and price hikes. I lay out the exact order I'd learn it in — runtimes, model-to-hardware matching, quantization, and agents — and I name the specific tools and models I reach for. Then I hand you five startup ideas that exist precisely because intelligence now sits on your desk. The payoff for you is a clear plan to own a resilient layer of your stack starting this week.
Timestamps
00:00 – Intro
01:20 – The Fable 5 Ban
02:31 – Renting Access vs. Owning Intelligence
03:41 – How a Local Model Works
07:19 – The Local Model Stack
08:45 – Match Model to Machine
10:45 – Pick Your Model (Qwen 3, DeepSeek, Gemma, Llama)
13:09 – Quantization Explained
14:36 –The Local Agent Loop
17:45 – Model Routing (The Real Skill)
18:44 – Five Startup Ideas for the Local-AI Era
22:17 – Closing Thoughts
Key Points
One government letter took Fable 5 offline overnight, which is why I now own a private layer of my stack.
Local models already handle roughly 80% of everyday ChatGPT or Claude tasks, fully offline and free after hardware.
I'd learn it in order: runtime first (LM Studio or Ollama), then match model size to your RAM.
A 12-billion-parameter model on 16 GB of RAM is the sweet spot where most people should live.
Quantization (look for Q4) roughly halves the memory a model needs while keeping quality high.
Pointing an agent like Hermes at a local model turns your desk into a private, always-on mini data center.
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 D… Lees meer -
You are using Claude Fable 5 wrong
11 juni 2026 · 33 min
Get my Fable 5 prompt pack: https://startup-ideas-pod.link/fable5-prompt-pack Lees meer
In this episode I break down how to get the most out of Fable 5, the most powerful model I've ever used. I move past the benchmarks and go straight into tactical use cases, copy-and-paste prompts, and startup ideas you can build today. I walk through tournaments for copy and landing pages, an interview-before-build workflow that hunts for product-market fit, and ways to point Fable at contracts, churn data, and years of your own notes. I close with three of my favorite startup ideas — a synthetic focus group firm, 48-hour custom software, and a contract refund firm — plus the exact prompts behind each. My goal here stays simple: leave you ready to build and earn with Fable 5 while it remains included in your plan.
Timestamps
00:00 – Intro
02:22 – Anthropic Employee Edits a Launch Video With Fable
05:50 – Building an AI Content Engine
07:30 – Best way to configure Fable 5
08:42 – Prompt 1: Copywriting Tournament for Landing Pages
13:18 – Prompt 2: The Interview-Before-Build Prompt
18:34 – Prompt 3: Hire Fable to Kill Your Company
20:18 – Prompt 4: Your One-Page Operating Manual
21:20 – Prompt 5: Find the Gaps Worth Filling
22:06 – Prompt 6: Negotiation Simulator
23:11 – Prompt 7: The 80-Page Second Opinion on Contracts
24:56 – Prompt 8: Make Fable Build Its Own Tools
25:47 – Startup Ideas
31:23 – Closing Thoughts
Key Points
I show why low effort is the alpha, since Fable Low beats Opus High on routine work.
I run tournaments — landing pages and ad copy scored by AI judge panels — to ship far stronger output.
I use an interview-before-build prompt so Fable pushes back and writes specs with real product-market-fit odds.
I point Fable at big datasets — contracts, churn data, support tickets, years of notes — to surface money and patterns.
I share startup ideas Fable 5 makes viable today, including a synthetic focus group firm and a contract refund firm.
The #1 tool to f…
-
What are Agentic Loops?
10 juni 2026 · 23 min
S/o Coderabbit for sponsoring today’s vid: https://startup-ideas-pod.link/code-rabbit
On this episode I sit down with Professor Ras Mic to break down agentic loops. We define what a loop is, explain why well-known builders like Boris and Peter swear by them, and stay honest about who they truly serve. Mic argues that human-in-the-loop remains the strongest setup today, and he walks through the one loop he runs every day for code review using Cursor, GitHub, and Greptile. By the end you will know when a loop earns its place and when your own hand belongs on the wheel.
Timestamps
00:00 – Intro
01:23 – What is a Loop
07:59 – /goal Explained
11:32 – The Slop Machine
12:42 – Code Review as a use case for Agentic Loop
18:19 – Honest Take for Builders
20:42 – The Future of Loops
21:50 – Closing Thoughts
Key Points
A loop fires once from a human, then the agent generates, reviews its own result, and feeds it back to keep building.
Human-in-the-loop keeps you directing, governing, and approving each step while the agent builds.
Wide-open loops make heavy assumptions and burn serious tokens; Michael cites Peter's tweet about $1.3 million worth of tokens in one month.
Reserve slash goal and similar loops for the $200/month plan, since the $20 and $100 tiers burn through fast.
Loops shine in confined, fixed-feedback work: code review, SEO pages, and other binary tasks.
Mic’s daily win is a closed code-review loop with Cursor, GitHub, and Greptile that chases a 5/5 score.
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: htt… Lees meer -
Become AI Native in less than 60 mins
8 juni 2026 · 57 min
Become an AI Native Organization: https://startup-ideas-pod.link/ai-native-org Lees meer
In this episode I sit down with Theo to unpack what becoming AI native truly means. We define an AI native org as people managing agents, agents reading and writing to the company, and the company growing smarter over time. Theo opens his actual workflows, walking through a working prototype, an auto-generated client proposal microsite, and a live usability test that synthesizes feedback into a V2 in one session. We close with service-business startup ideas built on this same system, plus a free consultation offer for larger companies. For founders and operators, the value lands as a concrete playbook for turning speed into customer signal and a durable moat.
Timestamps:
00:00 – Intro
04:09 – The Demis Hassabis origin story
06:53 – Defining AI Native Organization
08:19 – Mapping the system: people, agents, context
09:18 – Why people lead: strategy, taste, trust
13:23 – Agents: models using tools in a loop
16:12 – Evals and defining "good"
17:34 – Skill chains explained
20:06 – Proposal skill-chain demo setup
25:48 – Proposal microsite walkthrough
30:46 – Building the Daily Blitz feature demo
32:50 – Context as the foundational layer
41:07 – Daily Blitz ships and the labs page
43:47 – Bootstrapping context with a small team
46:21 – Usability test and live feedback
51:18 – Startup ideas: productize the system
54:28 – Closing Thoughts
Key Points
An AI native org runs on three layers: people for judgment, agents for execution, and context as the shared brain.
Everyone becomes a manager, so I set each agent up with a clear goal, the right skills, tools, and context.
Skill chains fire playbooks back to back, lifting quality and keeping outputs grounded in real data.
A living context layer gives agents 2020 vision, letting a personalized proposal ship in minutes.
Live prototypes plus built-in usability tests turn raw ideas into customer signal the same day.
The fastest…
-
Hermes Agent App Clearly Explained (and how to use it)
6 juni 2026 · 44 min
In this episode, I sit down with Alex Finn for a full, screen-shared walkthrough of Hermes Desktop, the new desktop home for the Hermes AI agent. I open with a clear challenge: by the end, sell me on installing Hermes Desktop, show me real ways to make money and stay productive, and explain his move from OpenClaw. Alex tours every major surface — sessions, profiles, artifacts, skills, cron jobs, and sub-agents — and shares money-saving tactics at each step. We close on the idea that matters most to me: aiming these agents at other people's challenges as the clearest path to real value. Lees meer
Timestamps
00:00 – Intro
04:04 – Sessions and Context Management
06:10 – Profiles Explained
08:49 – Model-Based vs Role-Based Profiles
12:58 – Artifacts as a Second Brain
14:32 – Why Alex Switched From OpenClaw
17:32 – Skills, Tools, and Tool Sets
19:19 – Messaging and Cron Setup
21:44 – Reverse Prompting and the Brain Dump
28:09 – Sub-Agents vs Profiles
32:12 – Putting It Together: Solving Challenges
32:38 – The Daily Business Opportunity Scan
37:05 – Local Models: Mac Studio vs DGX Spark
39:03 – Reframing Cost as Investment
41:59 – The Real Way to Make Money With Hermes
42:51 – Closing Thoughts
Key Points
Hermes Desktop pulls sessions, profiles, artifacts, skills, and cron jobs into one polished, Apple-style interface.
Smart session and context management keeps each message slim and keeps monthly costs low.
Profiles map to different models — Opus 4.8 for strategy, ChatGPT 5.5 for coding, a local Qwen model for free research — so each task runs on its best fit.
Reverse prompting plus a personal brain dump produces far stronger prompts, cron jobs, and outputs.
Sub-agents handle one skill across many parallel tasks; profiles handle work where each step needs a distinct skill set.
The biggest opportunity: aim your agent at Reddit and X to surface real problems you are positioned to solve.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
L…
-
Codex Sites Clearly Explained (and how to use it)
4 juni 2026 · 25 min
In this solo episode I walk through Codex Sites end to end, building a real internal tool live so you can copy the exact workflow. I open by comparing Codex Sites with one-prompt tools like Replit and Lovable, then construct a Startup Ideas OS board in six prompts. Along the way I cover memory and persistent storage, safe actions, Codex skills, save-gates, and proving the loop so the app updates autonomously. The core promise: by the end you know how to ship a Codex Site that an agent keeps operating for you. This one suits builders who already live in Codex and want self-updating products. Lees meer
Timestamps
00:00 – Intro and Episode Agenda
01:17 – Codex Sites vs Replit and Lovable
04:33 – The Build Plan: Startup Ideas OS
05:08 – Prompt 1: Build the Shell with Sites
07:02 – Plugins Worth Using and Game Studio
08:54 – First Board Review
09:21 – Prompt 2: Add Memory and Show the Data Model
10:56 – Prompt 3: Create Safe Actions
13:25 – Prompt 4: Create the Startup Ideas Admin Skill
14:51 – Prompt 5: Save-Gate and Checkpoints
16:29 – Prompt 6: Prove the Loop from a New Chat
18:10 – Publish, Auth, and Live Updates
20:28 – TLDR: Memory, Safe Actions, Skills
22:40 – The Real Unlock and Closing Thoughts
Key Points
Codex Sites rewards builders who already live in Codex by updating apps autonomously after launch.
Replit, Lovable, and Bolt stay the simpler one-prompt choice; Codex Sites trades that for autonomy and self-updating products.
Out of the box you prompt in auth, databases, payments, email, analytics, and a secrets vault yourself.
I build a Startup Ideas OS board in six prompts: shell, memory, safe actions, a skill, a save-gate, and a proof loop.
Safe actions let an agent call approved buttons and named mutations, so edits flow from any chat.
The real payoff is autonomous products that Codex keeps operating and improving on a live URL.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growing star…
-
The Next $100B Market: Selling To AI Agents
2 juni 2026 · 14 min
In this solo episode, I break down the shift from a human-first internet to an agent-first one, where AI agents become the customers that discover, evaluate, pay, and recommend. I map the agent buying journey and the new infrastructure agents need: identity, tools, an inbox, memory, a wallet, and receipts. I ground it with concrete examples like AgentMail and Stripe's agent wallet, then show how to make your website agent-readable through structured docs, schemas, MCP tools, and executable actions. I close with rapid-fire startup ideas and my big prediction for the next ten years: build startups for agents. Lees meer
Timestamps:
00:00 – Intro
00:49 – The tweet: build startups for agents
01:47 – Old web vs. agent web
02:24 – The agent buying journey
04:38 – What agents need: identity, tools, inbox, memory, wallet, receipts
05:30 – Examples: AgentMail, Stripe agent wallet, support, procurement, MCP, travel agent
08:24 – Building an agent-readable website
09:31 – What does this change for Startups
11:55 – Rapid-fire startup ideas for agents
13:07 – Closing Thoughts
Key Points
I explain that AI agents are becoming the primary customers online, with agent traffic set to outnumber human traffic.
I lay out the agent buying journey: finding, evaluating, transacting, using tools, and recommending to other agents.
I list what agents need beyond what humans need: identity, tools, an inbox, memory, a wallet, and receipts.
I walk through real examples like AgentMail, Stripe's agent wallet, support, procurement, MCP servers, and a travel agent.
I show how to make a site agent-readable with structured docs, schemas, MCP tools, SDKs, OAuth, checkout, sandboxes, and receipts.
I share rapid-fire startup ideas for the agentic era and frame my big prediction: build startups for agents.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn '…
-
Google's Biggest AI Announcements (I Was There)
22 mei 2026 · 26 min
Live from Google I/O, I sit down with Logan Kilpatrick from the Google DeepMind team to unpack everything Google just announced and what it means for founders, developers, and anyone trying to build with AI right now. Lees meer
We dig into Gemini 3.5 Flash, the new Gemini Omni world model, the expanded Antigravity ecosystem, managed agents in the Gemini API, and the native Android app builder inside AI Studio. Logan breaks down how distillation is pushing Pro-level intelligence into Flash, where the biggest opportunities are for solo founders, and why the agentic era has finally moved from impressive demos to genuinely useful products.
Thanks to Google for flying me out to Google I/O and making this conversation possible.
Timestamps
00:00 – Intro
00:53 – Gemini 3.5 Flash: The New Workhorse Model
01:49 – How Flash 3.5 Stacks Up Against Sonnet
02:38 – Gemini Omni: A World Model for Any Input and Output
06:18 – Building a Content and Creator Layer on Omni
08:21 – What to look forward to
10:53 – Google Spark and Managed Agents
14:00 – The Agentic Era and Requests for Startups
17:17 – The Antigravity Ecosystem Overhaul
18:51 – AI Studio vs. Antigravity: Vibe Coding vs. Agentic Engineering
21:31 – Native Android Apps Built Inside AI Studio
23:44 – Closing Thoughts
Key Points
Gemini 3.5 Flash ships as a Sonnet-level workhorse model tuned for long-running agentic tasks, coding, and tool use, available on day one to 900M+ Gemini app users.
Gemini Omni is a single model that takes any input and produces any output across video, image, audio, and music, fusing Veo, Nano Banana, Lyria, and TTS into one system.
Managed agents in the Gemini API let builders ship agentic products with a single API call, using skills and markdown instead of writing orchestration code.
The Antigravity suite now spans an IDE, agent manager, CLI, SDK, and API surface, all sharing the same agent harness that powers Gemini Spark.
AI Studio targets vibe coding and now builds native Android ap…
-
9 Huge Startup Opportunities in the AI Boom
18 mei 2026 · 1 uur 8 min
I sit down with my friend Jonathan Courtney, a.k.a. Jicecream, to dig into the 9 biggest startup opportunities I see right now across B2C, AI, mobile, and IRL. We each pick ideas, trade reactions, and pressure-test them live. The conversation ranges from agent-first "action apps" to elder tech, third spaces, hobby retreats, pet health, AI-native media, and the case for selling AI "junior employees" to small businesses. Listeners walk away with a concrete map of where to build in 2026, plus the framing I use to decide which niche is worth marrying. Lees meer
Timestamps:
00:00 – Intro
01:14 – Idea 1: Unscripted Creator Shows (Twitch model for tech)
07:50 – Idea 2: Action Apps: AI Agent Native Apps
16:39 – Idea 3: Loneliness and IRL Communities
26:47 – Idea 4: Elder Tech: Building for 65+
33:21 – Idea 5: Adult Hobbies
38:17 – Idea 6: AI Employee and AI Agents
45:33 – Idea 7: Personalized Nutrition/Health
53:08 – Idea 8: Pet Health and AI for Animals
57:34 – Idea 9: AI-Native Media Companies Done Right
01:03:18 – Stacking Ideas: Live + Retreats + Entrepreneurs
01:07:22 – Final Thoughts
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/