The Startup Ideas Podcast

I sit down with Cody Schneider, to break down how to become a top 0.1% marketer with GrokBot, Claude Code, and the tools around them. Cody shows the environment an agent needs to do marketing work: data in a warehouse, write access to ad platforms, and API tools for images, video, and leads. We build static ads live for Idea Browser, Late Checkout, Cursor, and more, then make a UGC avatar video ad with motion graphics for about $5. I add two pieces of my own: a swipe warehouse of creative references and a creative director agent that scores every ad. If you build products and hear crickets, this episode gives you workflows you can set up today.
Timestamps
00:00 – Intro
04:29 – Agents are now Marketers
09:56 – Data Pipelines & Warehouses
13:56 – Getting your agent access to data
16:15 – The tools for your agent
18:08 – Agents become .1% marketers
20:43 – Swipe Warehouse and Context
22:35 – Creating Static Ads
29:08 – Static Ads Results
30:03 – Creating UGC Avatar Ads
36:28 – Running the Workflow
37:58 – UGC Ad Results
39:51 – Human Creators Through Tribe and Sideshift
41:42 – Reviewing the Static Ads
43:29 – The role of Creative Director
50:49 – Closing Thoughts
Key Points
Agents do marketing's middle work once they have data, platform access, and tools.
A data pipeline into a warehouse gives agents full-funnel data and keeps them off rate-limited APIs.
Agents write to Facebook and Google Ads through their APIs and read data only from the warehouse.
One skill turns a brand URL into five researched, on-brand static ads.
A UGC avatar ad with motion graphics costs about $5, compared with $300 to $500 from humans.
Creative velocity wins, since Facebook's algorithm matches good creative to the right buyer.
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 CODY ON SOCIAL:
Cody’s startup: https://www.graphed.com/
X/Twitter: https://x.com/codyschneiderxx
Youtube: https://www.youtube.com/@codyschneiderx

In this solo episode, I lay out how I think about building an AI-proof business now that anyone can press a few buttons and spin up a company in seconds. Layoffs keep coming, people copy products pixel for pixel, and I still see more opportunity than ever. I walk through eight categories: atoms, permission, attention, timing, belonging, liquidity, unique data, and outcomes. I share examples like Hampton, final.com, and Cars & Bids, say how I'd rank the categories, and show how to mix them. If you're an employee looking at a startup or a founder worried about getting copied, this episode gives you a map for building something with value when AI makes software, content, and answers almost free.
Timestamps
00:00 – Intro
01:17 – Atoms: Physical Businesses
02:26 – Permission: Licenses, Regulation, and Partnerships
04:10 – Attention: Building a Media Machine
06:28 – Timing: Spotting Trends Early
08:24 – Belonging: Paid Communities and IRL Events
10:59 – Liquidity: Marketplaces
14:38 – Unique Data: Data Brokers and Curated Directories
18:31 – Outcomes: Customers Paying for Results
20:44 – Closing Thoughts
Key Points
Physical businesses hold up against overnight clones, and I expect their valuations to rise as tech money moves in.
Licenses, regulation, and preferred-vendor deals are permission that a copycat has a hard time getting on day one.
Media is underrated, and AI lets you run a content machine around a micro niche.
A first mover's product may be easy to copy, while the data, brand, and trust it collects stay AI-proof.
Marketplaces rank among the stickiest businesses of all time, and agents let a team of one to five run one.
I rank physical and licensed businesses near the top and outcomes at the bottom, and you can mix categories.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/
FIND ME ON SOCIAL
X/Twitter: https://twitter.com/gregisenberg
Instagram: https://instagram.com/gregisenberg/
LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Nick, co-founder of Orgo, to break down how to build a custom Grok Bot for a business and sell it for $25,000 up front with a $3,000-a-month retainer. Nick demos Bops, the agent platform he built in a 36-hour weekend, where each bot has its own phone number, email, and computer with four screens. He walks me through his research, design, and build process, the stack behind each bot, and the offer he takes to business owners. We also cover how to pick a niche by calling 50 people you know and how to turn one free case study into warm referrals. If you want to sell AI employees to businesses, this episode gives you the stack, the offer, and an open source repo you can fork today.
Links Mentioned
Nick’s Bops: https://startup-ideas-pod.link/bops
Timestamps
00:00 – Intro
03:09 – Bops, Custom Grok Bot Team
05:07 – Dumb SaaS vs. Custom Apps
07:02 – Selling AI Agent Teams
09:49 – Demoing Bop
13:57 – One Agent per Platform
15:07 – Step 1: Research
17:49 – Step 2: Design
22:12 – Step 3: Picking The Stack
26:43 – Step 4 and 5: Hosting and Shipping Fast
27:21 – The Offer and Business Model
38:02 – Why start this now
40:21 – Finding your first client
47:27 – Closing Thoughts
Key Points
Busy owners want their problems solved, so a GrokBot built for their industry wins over a platform they have to set up.
Nick builds in three steps: research the category, design in Paper, then pick a stack and read the docs.
Each bot gets its own email, phone number, computer, and connectors through Agent Mail, Agent Phone, Orgo, and Composio.
The SMB offer is $25,000 up front for a system the owner keeps, plus an optional $3,000-a-month retainer.
A free website redesign, a money-back guarantee, and free lead magnets make the offer easy to accept.
Call 50 people you know, do the first build free, and trade the case study for warm intros.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/
FIND ME ON SOCIAL
X/Twitter: https://twitter.com/gregisenberg
Instagram: https://instagram.com/gregisenberg/
LinkedIn: https://www.linkedin.com/in/gisenberg/
FIND NICK ON SOCIAL
Youtube: https://www.youtube.com/@nickvasiles
Instagram: https://www.instagram.com/nickvasilescu/
Personal Website: https://www.nickvasilescu.com/

In this solo episode, I explain why I say SaaS is dead and what I see taking its place. For 15 years, SaaS meant paying engineers to build a tool and charging per seat, and now models like Opus 5.5, GPT-6, and Argon make the tool easy to build. I walk through what I call smart SaaS: give the tool away for free, collect data and network effects, and make money by upselling AI agents and human services. I share a calorie tracking example, three ways to charge, and why enterprises still pay per seat. If you build software, this episode gives you a map for building something people want in a market where the tool is free.
Timestamps
00:00 – Intro
00:47 – SaaS 1.0
02:56 – SaaS 2.0: The New Business Model
05:12 – How to monetize SaaS 2.0
06:18 – Service is the new Software
07:22 – SaaS Is Dead, Long Live SaaS
08:58 – SMB vs Enterprise
10:31 – Closing Thoughts
Key Points
AI makes the tool easy to build, so the per-seat model of the last 15 years has run its course.
Smart SaaS gives the tool away and collects data and network effects as payment.
The money comes from upselling intelligence from AI agents and services from humans.
Agents can charge by token or by outcome, and human services by the week or month.
SaaS for SMBs, prosumers, and individuals trends toward free, while enterprises still pay something per seat.
The market for getting things done is bigger than the market for tools, so the total market for SaaS grows.
The #1 tool to find startup ideas/trends - https://www.ideabrowser.com
LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/
FIND ME ON SOCIAL
X/Twitter: https://twitter.com/gregisenberg
Instagram: https://instagram.com/gregisenberg/
LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Jon Noronha, co-founder and chief product officer of Gamma, to break down agent harnesses and the startup openings around them. Jon explains how Gamma rebuilt its product as a creative agent this year and walks me through the roughly 20 models and 200 calls behind one finished presentation. We talk about AI smell, why taste carries more weight than evals in creative work, how Gamma tests a new model within the hour, and the fast mode test that lost to good friction. Jon also shares the harnesses he wants to see, from a Slack agent that learns his voice to a couch shopping tool that checks the fit in your room. If you want to build a vertical agent, this episode gives you a clear model of what a harness is and where your edge can come from.
This episode was made possible thanks to Anthropic (the team behind Claude) for hosting us at Claude Founder house and sponsoring the episode.
Timestamps
00:00 – Intro
01:23 – What Is an Agent Harness
03:36 – Harnesses as the New Wrappers
04:25 – Inside One Gamma Prompt
08:23 – Where Vertical Harnesses Fit
11:08 – Finding Your Edge
11:56 – Opportunities for Harnesses
13:09 – Designing a Niche Harness
13:48 – AI Smell
15:49 – Evals and Taste
18:40 – Who Pays for AI
19:44 – The Gamma for X
20:19 – A Harness for Slack
22:01 – Building on Other People's Models
23:28 – Closed vs. Open Source Models
24:11 – A Broad but Shallow Stack
24:57 – Prompts vs. Fine-Tuning
25:30 – Testing New Models
26:25 – Running Experiments
29:10 – The Marketing Engineer
32:26 – Interesting Automations
33:33 – The Top 1% Marketing Engineer
35:00 – Everyone Is Now a VP of Agents
36:19 – Experiments as a Numbers Game
38:26 – Underhyped: AI Image Models
40:42 – Startup Opportunities
45:40 – What Jon Would Build Next
47:26 – Closing Thoughts
Key Points
An agent harness is the set of tools an agent uses to act, check its own work, and deliver a finished result.
One Gamma presentation uses about 20 models and 200 calls, including rounds of visual QA.
Strong harness ideas sit in subjective work, where people care about the output and want a human in the loop.
Your edge comes from a distinct vision, proprietary data, or a business that mixes AI with the physical world.
Gamma gets 98% of its value from prompts and treats fine-tuning as a cost and quality optimization.
Experiments reward volume, and Gamma's fast mode test showed that good friction raised paid conversion.
FIND ME ON SOCIAL
X/Twitter: https://twitter.com/gregisenberg
Instagram: https://instagram.com/gregisenberg/
LinkedIn: https://www.linkedin.com/in/gisenberg/
FIND JON ON SOCIAL
X/Twitter: https://x.com/thatsjonsense?lang=en
LinkedIn: https://www.linkedin.com/in/jonnoronha/