Greg Isenberg's 36 Startup Opportunities: What Is Actually Worth Building? | manman
Essay ・ No. 05
Greg Isenberg's 36 Startup Opportunities: What Is Actually Worth Building?
A practical breakdown of Greg Isenberg's 36 startup opportunities, with a focus on AI agents, vertical SaaS, outcome-based pricing, and startup ideas for small teams.
Greg Isenberg recently shared a list called “The 36 BIGGEST startup opportunities right now.”
The list is useful because it captures where internet businesses may be moving next: AI agents, vertical workflows, offline experiences, niche communities, and products that help people get real work done.
But it should not be treated as a step-by-step startup playbook.
Greg Isenberg is the CEO of Late Checkout, a company focused on building community-based internet businesses.
He also hosts The Startup Ideas Podcast, where he talks about startup ideas, internet business models, AI opportunities, and founder lessons.
His list is not an academic report or a market research white paper.
It is a set of observations from someone who spends a lot of time thinking about internet trends, consumer behavior, and startup opportunities.
The 36 Startup Opportunities
Here are the 36 opportunities from the list, rewritten in a practical way.
1. Solving loneliness
Third spaces, community apps, and real-world social products.
2. Managed AI employees for businesses
Not just AI tools, but AI workers that complete business tasks.
3. Elder tech
Products that help baby boomers live healthier and happier lives.
4. Action apps
Mobile apps that do things for users instead of just keeping them scrolling.
5. Trade worker marketplaces
Platforms for electricians, plumbers, HVAC technicians, and other skilled trades.
6. Small social
Products built around group chats, small circles, and private communities.
7. Shopping agents
AI agents that recommend products, compare options, and complete purchases.
8. Live and unscripted creator content
Live shows, spontaneous formats, and creator-led entertainment.
9. Conversational AI tutors
AI tutors that adapt to the student through ongoing conversation.
10. Outcome-based SaaS pricing
Software that charges based on results, not only seats or subscriptions.
11. AI service advisors for car dealerships
AI agents that answer common customer questions around repairs, appointments, warranty, and service status.
12. Training non-technical people to operate AI agents
A new skill category: managing and directing AI workers.
13. Offline experience kits
Anti-screen entertainment, games, challenges, and activities delivered to the home.
14. New forms of spiritual gathering
Products and communities built around belonging, meaning, and shared rituals.
15. Longevity biomarkers
Tools that help people track and manage long-term health indicators.
16. Action apps, again
The repeated idea: apps that take action, not just display information.
17. Human verification
Digital identity tools that prove someone is a real human.
18. Agent permissions, security, and audit logs
Infrastructure for AI agents that access real business systems.
19. AI-native media companies
Media brands that build distribution first, then sell products later.
20. Family operations automation
Tools for managing forms, calendars, school tasks, healthcare, and household logistics.
21. Bookkeeping agents
AI agents that handle bookkeeping and charge per transaction.
22. Brand-owned resale marketplaces
Secondhand marketplaces controlled by the original brands.
23. Adult hobby learning
Learning pottery, woodworking, painting, and other skills for joy, not career optimization.
24. At-home skincare diagnostics
Tools that scan skin, recommend routines, and track results over time.
25. Precision agriculture for small farms
Simple tools for family farms and smaller agricultural operators.
26. Subscription pest prevention
Preventive pest control services, similar to the shift seen in lawn care.
27. On-device AI for regulated industries
AI that keeps sensitive data local for healthcare, legal, and finance use cases.
28. AI game characters with memory
NPCs that remember players and build long-term relationships.
29. Agent-assisted matchmaking
AI agents that help filter, communicate, and match people in dating.
30. Adaptive fitness coaching
Fitness plans that update daily based on performance, goals, and recovery.
31. Autonomous travel planning and rebooking
AI that creates itineraries and also handles delays, cancellations, and changes.
32. Personalized nutrition
Diet recommendations based on blood tests, gut data, and other personal health inputs.
33. Pet health monitoring
Tech-enabled monitoring for pets in a large but still under-digitized market.
34. AI-native security and compliance for defense
AI tools for safety, compliance, and defense-related workflows.
35. Physical AI
Adding cheaper AI “brains” to existing hardware and robots.
36. Analog-feeling products
Products that feel physical, slow, handmade, or nostalgic in an AI-heavy world.
Is the List Actually Useful?
Yes, but not as a direct to-do list.
Its value is not in saying which idea will definitely work.
Its value is in showing several larger shifts.
AI Is Moving From Chat to Execution
Many ideas on the list point to the same trend.
Users do not want more dashboards.
They want software that completes work.
That connects ideas like:
Managed AI employees
Action apps
Agent permissions
Bookkeeping agents
Autonomous travel planning
The common pattern is simple: people want tools that do the job, not tools that create more work.
People Are Pushing Back Against Too Much Digital Life
Several opportunities are not really about AI.
They are about people wanting less screen time, less feed-based entertainment, and more real-world connection.
That includes:
Loneliness
Third spaces
Small social
Offline experience kits
Adult hobbies
Analog products
These are not just product categories.
They are cultural signals.
People are tired of endless feeds, synthetic content, and shallow interaction.
SaaS Pricing Is Changing
Outcome-based pricing may be one of the most important ideas in the list.
Traditional SaaS usually charges by seat, month, or usage.
AI SaaS may increasingly charge based on completed work.
For example:
Per invoice processed
Per support ticket resolved
Per qualified lead generated
Per transaction categorized
Per appointment booked
This matters because customers do not really want software.
They want outcomes.
Vertical Markets May Be Easier to Monetize
Some of the best opportunities are not the flashiest ones.
Car dealerships, bookkeeping, pest control, agriculture, family operations, pets, and skilled trades may be more practical than broad consumer AI apps.
Why?
Because these markets often have clear workflows, repeated pain points, and existing budgets.
For small teams, that matters more than sounding futuristic.
The Best Opportunities for Small Teams
For indie hackers, SaaS builders, and AI builders, the most useful ideas are the ones that can start narrow.
Here are the strongest categories.
1. Managed AI Employees for Businesses
This is one of the strongest opportunities.
But the right approach is not to build a “general AI employee.”
That is too broad.
A better approach is to build a specific AI worker for a specific job.
Examples:
AI customer support employee
AI appointment assistant
AI sales follow-up rep
AI bookkeeping assistant
AI real estate assistant
AI dealership service advisor
The narrower the worker, the easier it is to explain, sell, and improve.
2. Agent Permissions, Security, and Audit Logs
This is infrastructure for the agent economy.
As soon as AI agents can touch real systems, companies need control.
That means:
Permissions
Logs
Approval flows
Rollback
Security reviews
Role management
This is not a consumer product.
But it could become important B2B infrastructure.
3. Bookkeeping Agents
This is practical and easy to understand.
Many small businesses, contractors, and service providers do not want to manage accounting software manually.
They want:
Automatic transaction categorization
Receipt organization
Reconciliation
Monthly reports
Human review when something looks wrong
A per-transaction pricing model could make this especially clear.
4. AI Service Advisors for Dealerships
This idea looks small, but that is the point.
Many industries have the same repetitive questions every day:
Is my car ready?
How much will service cost?
Can I book an appointment?
Is this covered by warranty?
What documents should I bring?
Are you open today?
A vertical support agent is often easier to sell than a generic chatbot.
5. Family Operations Automation
A family is basically a small company.
Many households manage:
Forms
Bills
Calendars
Insurance documents
School notices
Medical appointments
Shared responsibilities
The opportunity is real, but the product must be simple.
This should not become another complex dashboard.
6. On-Device AI for Regulated Industries
Healthcare, legal, and finance teams are careful with sensitive data.
For many use cases, AI becomes more useful if data can stay local.
This category has a higher technical bar, but also strong long-term potential.
7. Human Verification
As AI content grows, proving that someone is human may become more important.
Platforms may need to distinguish between:
Real people
Bots
AI agents
Bulk accounts
Synthetic content accounts
This is a large opportunity, but also a difficult one.
It touches identity, privacy, trust, and platform adoption.
Opportunities to Treat Carefully
Some ideas on the list are real but harder to turn into a business.
Loneliness, Spirituality, and Nostalgia
These are meaningful human needs.
But they are not always easy startup entry points.
They often require strong branding, community building, content, and offline operations.
Dating, Consumer Social, and AI Game Characters
These have huge upside, but cold start is hard.
The main challenge is not usually technology.
It is distribution, retention, and network effects.
Small teams need a very specific wedge to compete here.
Skincare, Nutrition, Fitness, and Biomarkers
These markets have strong demand.
But they also involve health claims, data quality, and regulatory risk.
Products around blood work, gut health, diagnostics, or medical-adjacent advice should be handled carefully.
Travel and Ecommerce Agents
These are attractive categories, but large platforms are likely to compete here.
A small team should avoid building a generic travel or shopping agent.
A better strategy is to go vertical.
Examples:
Travel planning for photographers
Shopping agents for students moving abroad
Gear buying agents for niche outdoor communities
Travel planning for remote teams
Specific use cases are more defensible than generic agents.
What Should Builders Take Away?
The best opportunities are not always the biggest-sounding ones.
For small teams, the better question is:
Which customer has a painful, repeated, expensive problem that AI can solve much faster or cheaper?
The strongest startup opportunities usually have these traits:
Frequent pain
Willingness to pay
Measurable outcomes
Clear workflow
Vertical focus
Lower cost through AI
A niche small enough to start with
From that lens, the strongest opportunities in the list are:
Vertical AI employees
Agent permission and audit infrastructure
Outcome-based SaaS
Bookkeeping and finance automation agents
Family and small business operations automation
The right way to use this list is not to ask:
Which opportunity is the biggest?
The better question is:
Which opportunity has a small, painful, specific customer segment that already pays for a solution?
Real startup opportunities often look like this:
A specific group of people repeats the same annoying task every day.
They already spend money to solve it.
AI can make it ten times cheaper, faster, or easier.