SaaS is dead?

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

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

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

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP I sit down with James Dickerson, the Boring Marketer, who owns Diesel Dudes, a mobile diesel repair business in Charlotte, North Carolina, and spent years running agencies for local businesses. James shows how to sell AI-built funnels to Main Street trades businesses doing $2 million to $20 million a year, starting with a Boring Funnels search that found 100 Dallas plumbers worth pitching. He walks through the leaks he finds on their landing pages, the funnel offers he'd sell, and how he'd win clients with the Dream 100, lumpy mail, and local meetups. If you know how to use coding agents, this episode gives you a full playbook for a service business built around booked jobs. Build funnels that sell: https://startup-ideas-pod.link/boring_funnels Timestamps 00:00 – Intro 01:23 – Sponsor: Brex 02:08 – Why sell AI to Main Street 03:05 – James's Background 04:32 – Finding and Picking a Niche 07:26 – The $2M to $20M Opportunity 09:02 – Plumbing and HVAC Market Size 10:56 – Underserved Trades Niches 12:38 – Auditing Five Dallas Plumbers 13:50 – Personal Agents vs. Google 15:02 – Selling Booked Jobs and Phone Calls 17:41 – Funnel Offer Overview 19:43 – Funnel Example 23:19 – Matching Ads to Funnels 24:14 – Chet Holmes and the Dream 100 28:18 – Branding your Firm 30:04 – Meta Ads for your firm 31:37 – Stacking Old School and New School Marketing Strategy 34:31 – Find, Pitch, Deliver 36:02 – Showing Owners the ROI 37:37 – Pricing your Offer 41:45 – Reporting With AI 42:33 – Closing Thoughts Key Points Main Street trades businesses doing $2 million to $20 million a year have budgets and few useful pitches in their inbox. James sells booked jobs and phone calls, since owners care about revenue and ROI over AI. The biggest leaks sit on the landing page: missing ad promises, hidden Google ratings, and buried booking buttons. Funnels with tripwires, instant prices, quizzes, and owner videos turn paid traffic into booked jobs. The Dream 100, lumpy mail, and local meetups build trust with owners over months. One free build in exchange for a case study gets you to paid work. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND JAMES ON SOCIAL X/Twitter: https://x.com/boringmarketer LinkedIn: https://www.linkedin.com/in/jadickerson/

In this solo episode, I break down the war on AI agents, from Amazon blocking Meta's Muse to Delta treating outside booking agents as unauthorized automated activity to Yelp charging agents for access. I share how I think about an agent, as a customer with a credit card who reads your site instead of looking at it, and the ladder of trust that runs from research to prepare to pay. Then I walk through each big player's bet, my nine stages for how this war plays out, five moves any business can make this week, and the startup ideas I see between agents and the businesses they buy from. If you run a store or build products, this episode gives you a map for selling to customers who send an agent to shop for them. Timestamps 00:00 – Intro 02:09 –The Three Camps 05:08 – How I Define an Agent 06:52 – The Ladder of Trust 08:54 – Real Reasons to Block Agents 09:48 – What Agents Skip 12:57 – How Each Company is Playing it 17:06 – Lessons From Mint and Plaid 17:49 – The 9 stages of The War on Agents 21:56 – What to do this week 24:39 – Startup Idea 1: Agent Readiness 25:48 – Startup Idea 2: Plaid for One Vertical 26:22 – Startup Idea 3: Insurance for Agents 26:57 – Startup Idea 4: Analytics for Agent Traffic 27:26 – Startup Idea 4: Agent Specialist 28:05 – Closing Thoughts Key Points Agents read product details, prices, shipping, and return policies, so plain-text facts on the page decide whether they pick you. Agents climb a ladder of trust from research to prepare to pay, and the whole fight happens on the pay rung. Many blocks protect the ad and upsell revenue that agents skip on the way to the sale. The biggest stores block, the biggest audiences open the door, and payment and security companies want the toll booth. I expect a Plaid moment for agent identity and payments, followed later by ads that buy an agent's first recommendation. Vertical Plaids, agent insurance, and agent analytics are open lanes for startups right now. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP In this solo episode, I break down how to make money with Meta Muse by mining Facebook groups, Marketplace, and Instagram to match buyers with sellers. The idea came after my wife and I had a baby and the agency we hired for a night nurse admitted it found candidates in Facebook groups. I demo Muse finding night nurses at $30 an hour in Montreal, show how to give it a phone number through Bland AI, and share the Marketplace and Instagram tactics I'd use. I close with my four-level framework for growing a matching side business into a trusted list, a community, and a vertical software company. Timestamps 00:00 – Intro 01:19 – Sponsor: Brex 03:22 – Meta Muse 03:52 – Why this is a big opportunity 04:33 – Picking a Niche, City, and Rules 05:44 – Owning the asset and data 06:51 – Cleaning Data You Own 08:27 – Lessons From eBay 10:37 – A Phone Number With Bland AI 11:30 – Undervalued Facebook Groups 12:55 – Business Pages and IG Niche Pages 13:46 – Prompting Muse Into Facebook Groups 15:19 – Mining FB Marketplace and Instagram 17:20 – Four Levels of Personal Agent Arbitrage 20:38 – Results From Montreal Groups 21:40– Goods vs. Services 22:15 – Muse vs. Dots and Instinct 24:09 – Closing Thoughts Key Points Muse mines public Facebook groups, Marketplace, and Instagram to match buyers and sellers in any niche and city. A clean list of names, needs, prices, and trust signals is an asset I own and can sell later. Facebook groups, business pages, and IG niche pages look undervalued as Muse agents start crawling them. I tell Muse where to look, and Facebook groups gave me the highest quality data. My four levels: mine the data, own the list, own the room, then build technology. A lean cost structure lets me charge a success fee of a few hundred dollars and keep high margins. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Gemini 4 Argon is LIVE, Google's most advanced AI model, try it for yourself: https://startup-ideas-pod.link/gemini4-argon In this solo episode, I share what I learned after a week with Gemini 4 Argon, Google's new frontier model. I show three places it shines: marketing with AI, physical AI, and complex engineering, with a real build for each. You'll see Argon rebuild my holding company's website, write a post in my voice, design a Shopify product customizer that exports STL files, and build a free quoting app for commercial cleaning companies. I close with six techniques that raise Argon's output quality and the Google AI plan I'd pick for building. Timestamps 00:00 – Intro 01:35 – What Gemini 4 Argon Does Well 03:09 – Rebuilding the Late Checkout Website 07:49 – Justine Moore's Apple Computer Museum 09:20 – Using Argon for writing 13:03 – Physical AI and Vibe Manufacturing 17:41 – Made-to-Order Shopify Store 19:01 – Building Boring SaaS 21:59 – Commercial Cleaning Quote App 25:12 – 6 techniques to get the most out of Argon 28:39 – Closing Thoughts Key Points Argon produces premium creative work once I give it reference images and a clear direction. A skill built from my posts, newsletters, and videos lets Argon write in my voice. Argon builds Shopify product customizers that export print-ready STL files. Free, focused rebuilds of boring legacy SaaS put me in front of likely buyers. Argon gets the engineering right on prompt one, and design takes a few more rounds. /plan, /subagents, and /goal give me the biggest jumps in output quality. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I walk through eight GitHub repos and AI skills that I test at night and on weekends. The list covers launch videos, social research, local voice and dubbing, editable decks, agent teams, lead-magnet tools, idea stress-testing, and design guidance. For each one, I explain what it does, how I'd set it up, and one concrete way to use it to make money or run a business more easily. Most are free to download, and you pay for the model you run them with. Timestamps 00:00 – Intro 01:25 – Brag: Launch Videos From a Link 04:50 – Agent Reach for Customer Research 07:46 – Voice Studio: Local AI Voice and Dubbing 10:41 – PPT Master: Editable Decks From Notes 12:59 – OpenRig: Coding Agents as a Team 14:57 – Free Tools Skill by Corey Haynes 17:25 – Grill Me Skill by Matt Pocock 19:31 – Impeccable: Design Guidance for Agents 23:03 – My Top Picks: Brag and Agent Reach 24:07 – Closing Thoughts GitHub Repo Links: Brag (launch video skill): https://startup-ideas-pod.link/brag Agent Reach: https://startup-ideas-pod.link/agent-reach Voice Studio: https://startup-ideas-pod.link/voice-studio PPT Master: https://startup-ideas-pod.link/ppt-master OpenRig: https://startup-ideas-pod.link/openrig Free Tool: https://startup-ideas-pod.link/marketing-skills Grill Me Skill: https://startup-ideas-pod.link/grill-me Impeccable Skill: https://startup-ideas-pod.link/impeccable Key Points Most of these tools are free to download, and the main cost is the model you run them with. Work I do for someone up front, like a launch video or a design fix, starts a conversation in place of a cold email. Posts on Reddit, X, and YouTube show tasks people still do by hand, and a small tool can fix them. Translated onboarding videos make a recurring monthly service for other companies. Grill Me logs my assumptions so I check them with a real customer before I build. Ten clients at $1,000 a month is $10,000 a month, and that cash flow funds the move from services to technology. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I walk through the 13 businesses I think are left to build in the agentic era. I believe that in a world of agents and abundance, owning the right assets puts you in a better position. For each business, I explain what it is, why it holds up in a world of agents, and one or two examples, from Othership's sauna clubs to Osmo's window-cleaning robots. This episode gives you a map of where to build next, at any age. Timestamps 00:00 – Intro 01:15 – AI-Native Service Firms 02:57 – Offline Businesses 05:41 – Distribution and Organic Audiences 07:34 – Proprietary Data Sets 09:08 – Domain-Specific Harnesses 12:16 – Robotics and Physical AI 14:01 – Physical Products With a Fan Following 16:34 – Compute and Energy 17:31 – Health, Longevity, and Care 19:30 – Marketplaces and Social Networks 21:04 – Real Assets 21:46 – Vertical Agents 22:18 – Security 24:08 – Closing Thoughts Key Points In an AI-native service firm, agents do most of the delivery and a human reviews the exceptions. Ad clicks went from about five cents in 2009 to $1–5 today, so I start with organic audiences. Proprietary data and domain-specific harnesses are the two gold rushes I see right now. Offline businesses, niche hardware, and robotics sell rooms, objects, and labor that agents only support. Compute, energy, and security are the scarce inputs every agent depends on. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Google's most advanced audio models are LIVE, try them for yourself: Gemini 3.8 Live: https://startup-ideas-pod.link/gemini-3.8-live Gemini 3.5 Transcribe https://startup-ideas-pod.link/gemini-3.5-transcribe Gemini 3.5 Live Translate: https://startup-ideas-pod.link/gemini-3.5-live-translate In this episode, I talk with Vas from Varick about what it takes to put AI to work inside a real company. Vas makes the case that AI pays off through process reengineering, and he walks me through the exact method his forward deployed engineers (FDEs) use: interviews, process mining, step sorting, and agents built inside existing systems of record. We go through real engagements, including a $5B public software company and an accounts payable overhaul that cut the cost per invoice from $31 to $6. By the end, you get a clear picture of the FDE role, the business opportunity behind AI roll-ups, and a five-day plan to start on your own. Links Mentioned: FDE Presentation: https://startup-ideas-pod.link/FDE-slides Vas’s Article: https://startup-ideas-pod.link/vas-fde Timestamps 00:00 – Intro 01:31 – Sponsor: Google 03:58 – FDE Overview 05:02 – AI Roll-Ups and Process Reengineering 08:04 – The Personal Systems Analogy 09:55 – Understanding a company’s process (step-by-step) 14:11 – Case Study: $5B Software Company 18:11 – 4 Buckets for Every Step 19:04 – Build Inside Systems of Record 21:36 – Case Study: PE Portfolio 23:43 – Selling to C-Suite Executives 27:07 – Process of Mapping Five NetSuite Companies 28:39 – Example: Accounts Payable Process Map 32:54 – Case Study: 60-Person Accounting Firm 34:51 – When to Use Code, Agents, or Humans 36:00 – Choosing AI Models 38:16 – Sidekick vs Background Agents 40:29 – The 3 Skills of a Top FDE 42:25 – Why FDEs Earn So Much 45:26 – Five-Day Starter Plan 47:39 – On-Premise Hardware Demand 48:36 – OpenAI Private Intelligence 50:20 – The Full Playbook 52:01 – Closing Thoughts Key Points AI pays off when you re-engineer the process first, then build agents into it. Map the real process with interviews, system-of-record mining, and existing docs. Sort every step into four buckets: delete, plain code, agent, or human decision. Build agents inside the tools clients already use, like Salesforce, NetSuite, and Slack. Sell the outcome each buyer cares about, and prove it with before-and-after KPIs. Top FDEs combine domain knowledge, production engineering, AI judgment, and strong communication. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND VAS ON SOCIAL Varick Agents: https://www.varickagents.com/#hero-section X/Twitter: https://x.com/vasuman AI Forward Deployed Engineers: https://learn.varickagents.com/fde-in-30-days