The Startup Ideas Podcast

Stop building AI wrappers. Start building agent harnesses. Oct 28, 2026

Show notes

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.

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FIND JON ON SOCIAL

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

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

How to sell AI to Main Street (Full Playbook) Oct 26, 2026

Show notes

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

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

Timestamps

00:00 – Intro

01:23 – Sponsor: Brex

02:08 – Why sell AI to Main Street

03:05 – James's Background

04:32 – Finding and Picking a Niche

07:26 – The $2M to $20M Opportunity

09:02 – Plumbing and HVAC Market Size

10:56 – Underserved Trades Niches

12:38 – Auditing Five Dallas Plumbers

13:50 – Personal Agents vs. Google

15:02 – Selling Booked Jobs and Phone Calls

17:41 – Funnel Offer Overview

19:43 – Funnel Example

23:19 – Matching Ads to Funnels

24:14 – Chet Holmes and the Dream 100

28:18 – Branding your Firm

30:04 – Meta Ads for your firm

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

34:31 – Find, Pitch, Deliver

36:02 – Showing Owners the ROI

37:37 – Pricing your Offer

41:45 – Reporting With AI

42:33 – Closing Thoughts

Key Points

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

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

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

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

The 9 Stages of AI Agent Adoption, Explained Oct 21, 2026

Show notes

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

Timestamps

00:00 – Intro

02:09 –The Three Camps

05:08 – How I Define an Agent

06:52 – The Ladder of Trust

08:54 – Real Reasons to Block Agents

09:48 – What Agents Skip

12:57 – How Each Company is Playing it

17:06 – Lessons From Mint and Plaid

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

21:56 – What to do this week

24:39 – Startup Idea 1: Agent Readiness

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

26:22 – Startup Idea 3: Insurance for Agents

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

27:26 – Startup Idea 4: Agent Specialist

28:05 – Closing Thoughts

Key Points

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

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

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Making $$$ with Meta Muse AI Oct 19, 2026

Show notes

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

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Gemini 4 Argon: AI Marketing, 3D Printing and SaaS Oct 15, 2026

Show notes

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

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8 GitHub Repos To Go Viral and Make Money Oct 08, 2026

Show notes

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

Timestamps

00:00 – Intro

01:25 – Brag: Launch Videos From a Link

04:50 – Agent Reach for Customer Research

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

10:41 – PPT Master: Editable Decks From Notes

12:59 – OpenRig: Coding Agents as a Team

14:57 – Free Tools Skill by Corey Haynes

17:25 – Grill Me Skill by Matt Pocock

19:31 – Impeccable: Design Guidance for Agents

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

24:07 – Closing Thoughts

GitHub Repo Links:

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

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

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

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

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

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

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

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

Key Points

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

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

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How Will People Make Money in the AI Age? Oct 06, 2026

Show notes

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

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Become a $1M/yr FDE (Full Course) Oct 01, 2026

Show notes

Google's most advanced audio models are LIVE, try them for yourself:
Gemini 3.8 Live: https://startup-ideas-pod.link/gemini-3.8-live

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

Gemini 3.5 Live Translate: https://startup-ideas-pod.link/gemini-3.5-live-translate
In this episode, I talk with Vas from Varick about what it takes to put AI to work inside a real company. Vas makes the case that AI pays off through process reengineering, and he walks me through the exact method his forward deployed engineers (FDEs) use: interviews, process mining, step sorting, and agents built inside existing systems of record. We go through real engagements, including a $5B public software company and an accounts payable overhaul that cut the cost per invoice from $31 to $6. By the end, you get a clear picture of the FDE role, the business opportunity behind AI roll-ups, and a five-day plan to start on your own.

Links Mentioned:

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

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

Timestamps

00:00 – Intro

01:31 – Sponsor: Google

03:58 – FDE Overview

05:02 – AI Roll-Ups and Process Reengineering

08:04 – The Personal Systems Analogy

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

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

18:11 – 4 Buckets for Every Step

19:04 – Build Inside Systems of Record

21:36 – Case Study: PE Portfolio

23:43 – Selling to C-Suite Executives

27:07 – Process of Mapping Five NetSuite Companies

28:39 – Example: Accounts Payable Process Map

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

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

36:00 – Choosing AI Models

38:16 – Sidekick vs Background Agents

40:29 – The 3 Skills of a Top FDE

42:25 – Why FDEs Earn So Much

45:26 – Five-Day Starter Plan

47:39 – On-Premise Hardware Demand

48:36 – OpenAI Private Intelligence

50:20 – The Full Playbook

52:01 – Closing Thoughts

Key Points

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

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

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

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

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

OpenAI DevDay: Dots, Agents & $100B Opportunities Sep 29, 2026

Show notes

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

Timestamps

00:00 – Intro

01:48 – Dots, the Personal Agent Platform

03:29 – OpenAI Doubles Down on Plugins

05:02 – Decisions API

06:43 – Agents API With Computer Use

08:01 – Sign In With ChatGPT

12:36 – Where should you build?

13:46 – Idea: Real-World Work APIs

15:04 – Idea: Analytics for Agent Discovery

17:05 –Closing Thoughts

Key Points

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

The #1 tool to find startup ideas/trends - https://www.ideabrowser.com

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