AI & Automation

Vertical AI agents (specialty)

Build AI agents tuned to a specific vertical (real estate, legal, dental) that perform a single job end-to-end.

Catalog synthesis

The idea, in plain language

Build AI agents tuned to a specific vertical (real estate, legal, dental, divorce, restaurant phones, home services) that perform a single end-to-end job and are sold per seat, per outcome, or as a managed agent. Numbers across the videos include Slang AI's restaurant phone-answer agent, Same Day's home-services dispatcher, Ryan Carson's Untangle divorce agent tracking 4x revenue growth as a solo operator, Flo Crivello's Lindy AI (executive-assistant, proposal, recruiter and lead-gen agents), and Greg's three-phase leveraged-agency playbook ($1-5K/mo manual SOP → 80% margin with AI → enterprise/self-serve/API tiers toward $5M ARR). Customers are small businesses and professionals whose existing workflow is one specific job (intake, scheduling, document review, dispatch); startup cost is essentially the AI tooling plus a landing page, and the moat is the SOP encoding and the watchdogs/observability wrapped around the agent.

Where the sources agree

  • Pick one vertical where a workflow already has a paycheck attached — insurance forms, invoice processing, restaurant phones, divorce intake, home-services dispatch — and shadow 10-20 jobs before automating.
  • Ship a minimum useful agent (triage, draft-and-approve, coordinator, bounded action) and sell it like labor before productising the repeatable parts.
  • The agent loop, context files, memory, MCP tool connections and skills/SOPs are the technical primitives — Greg, Remy Gaskell and Flo Crivello each give slightly different versions of the same stack.
  • A solo operator can run a meaningful agent business — Untangle's 4x monthly growth as a one-person team, Orgo's cloud-agent model, and Greg's three-phase plan all assume a solo founder.

Where they differ

  • Greg Isenberg dominates with framework / playbook episodes (three-phase agency, agent SaaS, $1M+ solo agent business, most-valuable-skill 2026). MFM (Amjad Masad magic-school apps, Sarah Guo's 10 ideas, Jess's matrix) pitches verticals as brainstorm fodder.
  • Starter Story (ToneAdapt at $25K/month) anchors on a consumer-facing niche; Greg's agent cases (Slang AI, Same Day, Lindy, Untangle) are mostly B2B SMB or vertical professional services.
  • Pricing shapes differ: $50-100/month SaaS (Postiz-style AI features, Greg's first phase), outcome-priced AI receptionist (Slang AI), per-seat AI employee (Lindy), and solo-agent ops templates.
  • Technical stack differs: Greg leans on Lindy + OpenClaw + skills; MFM leans on Replit / magic-school / no-code AI; Flo Crivello pitches Lindy itself as the platform; String demos a NL-prompt agent builder with dynamic code generation.

What each source says

MFMHow To Build A $10M AI App In Literally 30 Seconds (this is insane)

Amjad Masad's Replit episode shows how magic-school-style AI apps can be built quickly and reach large audiences when they solve a vivid use case. The AI-agent angle is rapid prototyping, weekend-scale app creation, and using agents to iterate on software ideas.

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IsenbergBuilding AI Agents that actually work (Full Course)

Package a 'skills library' for client onboarding and reuse the same SOPs across several vertical products.

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IsenbergI built next gen AI Agents with MCP + Claude (STEAL my workflow)

Greg and Riley Brown demonstrate Claude enhanced with MCPs, Docker, Notion, Glyph, and specialized workflows. The episode supports packaging a configured agent workspace, custom instructions, and task-specific skills for clients that want an 'AI employee' without assembling the stack themselves.

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Isenberg13 Businesses for the Age of AI

Isenberg names vertical agents as one of 13 business categories built for the agentic AI era, sitting alongside proprietary data, domain harnesses, and robotics in a framework of owning scarce assets.

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IsenbergThe Most Overlooked $12.5K/mo AI Agent Business Anyone Can Start

Greg's three-phase plan starts with a manual service around a boring, high-value workflow at $1-5K/month and about 40% margins, then automates the SOP with agents to target 80% margins, then expands into enterprise, self-serve, or API tiers. His examples include insurance forms, invoice processing, review responses, and PDF-to-Salesforce.

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IsenbergThe $1M+ Solo AI Agent Business (Full Course)

Nick from Orgo frames the solo AI-agent business around cloud computers, customer workspaces, watchdogs, observability, and content-led customer acquisition. The episode supports selling managed cloud-agent seats for one vertical with a fixed setup and maintenance package.

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IsenbergMost Valuable Skill of 2026: Managing AI Agents

Ryan Carson's Untangle stack shows model routing, cheaper fine-tunes for bulk work, production watchdogs, daily self-improvement loops, and parallel cloud agents producing 22 to 40 PRs a day. The episode treats agent management itself as the valuable 2026 skill.

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Starter StoryThe First App I Ever Built Makes $25K/Month

Kyan's ToneAdapt story shows a tiny personal texting problem becoming a $25K/month app in five months. The repeatable lesson is to ship V1 fast, solve a narrow communication pain, post short-form content three times a day, and scale the formats that work.

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MFM10 AI Business Ideas From The Queen of AI ft. Sarah Guo

Productise a 'Generative Voice Receptionist' for community organisations and small law/medical practices: the same AI voice + booking pattern, repackaged per vertical and sold through an outreach system.

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IsenbergAI Agents are the new SaaS

Greg's agent-SaaS playbook says to pick a workflow with a paycheck attached, shadow the human for 10-20 jobs, ship a minimum useful agent, and sell the pilot like labor. Slang AI and Same Day illustrate phone-answering and dispatcher-style agents that become productized software.

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IsenbergMy AI agents scrape Google Maps to make $$ in BORING businesses

Build the Google Maps niche-finder agent on top of an existing scraper stack and resell leads to the contractors and home-services pros in a portfolio of demo-site towns.

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MFMAsking A Billionaire How To Make $1,000,000

Sam and Shaan's discussion with Jess frames vertical agents around finding a starving crowd, then building focused intake, scheduling, compliance, or operations agents for that group. The episode also includes DOGE as a service, Holy Health, Divorce.fund, digital-twin teams, and AI for medicine as adjacent idea prompts.

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KoernerAI Agencies Just Got Simple Enough for Anyone to Start

Position a small web-services business as a Lindy-style AI agent implementation shop for SMBs, using Claude Code agents and an AI voice receptionist as the starting stack.

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IsenbergHow To Make MILLIONS As A Faceless YouTuber | Dru Riley

Dru Riley's faceless YouTube playbook combines thumbnail and title testing, AI scripts and voiceovers, niche AI tools, productized creator services, and co-reg newsletter giveaways. The episode suggests using one focused channel or audience at a time, then turning repeated needs into paid tools.

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IsenbergMeet the Hidden Agent Builder Turning Simple Prompts into Profit

Ship a String-style HN/Reddit monitor agent for niche keywords and a blog-to-LinkedIn agent for a content pipeline.

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IsenbergThe Future of AI with Riley Brown

No take is available for this episode.

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Koerner5 Ways to Make Money From an AI the Government Fears

No take is available for this episode.

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MFMHow Nick Saban’s Side Hustle Might Make Him a Billionaire

No take is available for this episode.

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Isenberg5 $1M+ AI startup ideas from an indie hacker legend

No take is available for this episode.

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IsenbergMaster the Art of AI-first Products with Dave Rogenmoser's Winning Formula

No take is available for this episode.

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MFMIf I Could Start Over Again, This Is What I’d Do To Get Rich - Scott Galloway

No take is available for this episode.

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MFMIf you’re in your 40s, build a business on these trends.

No take is available for this episode.

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IsenbergThe framework for building AI startups from a product design genius

Mike Hudack presents an AI-startup framework of picking repetitive, feedback-rich, bounded tasks, studying Greenlight, Granola, Gradient Labs and Domu, with regret-minimisation pricing and build-in-public go-to-market advice.

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