13 Categories of Businesses to Build in the Agentic Era: Greg Isenberg's Strategic Guide

Serial entrepreneur and podcast host Greg Isenberg (@gregisenberg) has shared a strategic framework identifying the 13 categories of businesses durable enough to build and scale in the 'agentic era', a period where autonomous AI agents rapidly drive down the marginal cost of software and routine knowledge work.

Image source: @gregisenberg

As the cost of creating code approaches zero and AI agents handle programming, copywriting, and routine operational workflows, conventional wrapper tools and agencies selling billable hours face structural decline. Isenberg argues that sustainable competitive advantage is shifting decisively toward businesses that either own scarce, non-replicable assets that no agent can prompt into existence or deploy agent leverage to deliver high-margin, outcome-based services.

How the Agent Economy Disrupts Knowledge Work and Generic Software

The proliferation of autonomous AI agents creates extreme abundance in knowledge output and software production. As building generic software becomes trivial, founders face critical shifts across the market landscape:

• Erosion of Software Moats: When building features requires minimal effort, standard software tools struggle with product differentiation and inevitably slide into pricing commoditization.
• Decline of the Billable Hour: Professional service firms charging by the hour face disruption as agents execute the majority of operational tasks, forcing a migration toward outcome-based and per-job pricing models.
• Value Migration to Scarce Assets: Economic rents concentrate around owners of proprietary niche data, physical spaces, distribution channels, and critical infrastructure that cannot be scraped or simulated.

The 13 Durable Business Categories in the Agentic Era

Isenberg sorts viable business opportunities into two primary groups: businesses that use agents to deliver work at unprecedented speed and margin, and businesses that own physical or institutional assets that AI cannot replace.

1. AI-Native Service Firms

Service providers where autonomous agents execute over 90% of operational workflows, while human experts focus exclusively on edge cases, client strategy, and quality assurance. By billing per completed job rather than by the hour, these firms achieve high operating margins with lean client rosters. Practical examples include specialized bookkeeping, financial compliance, and brand identity asset production.

2. Offline Experience Businesses

Real-world, location-based ventures that deliver physical sensory experiences that digital software cannot replicate. Membership-driven concepts like the Toronto-founded sauna club Othership illustrate how communal wellness, physical immersion, and human gathering spaces maintain durable moats in an agent-saturated world.

3. Distribution Assets (Media, Community, Audience)

Proprietary distribution channels cultivated through the ACP (Audience to Community to Product) funnel. As building products becomes easier, attention and audience trust become the primary bottleneck. Founders with dedicated audiences and engaged communities enjoy structural conversion advantages.

4. Proprietary Niche Datasets

Specialized datasets within narrow industrial or professional domains that competitors cannot scrape from the public web. Businesses possessing validated operational data provide the indispensable context required for accurate agent execution.

5. Domain-Specific Agent Harnesses

Comprehensive operational harnesses that orchestrate complete end-to-end industry workflows, moving far beyond superficial API wrappers. These act as specialized micro-operating systems managing tools, rules, permissions, and exception paths for a specific vertical.

6. Robotics and Physical AI

Hardware and robotic systems designed to perform labor directly in the physical world. Initiatives like Osmo's high-rise window-cleaning robots demonstrate that automating physical labor subject to friction and real-world dynamics remains insulated from pure software agents.

7. Physical Products with a Fan Following

Tangible goods supported by brand loyalty and active customer subcultures. Tactile quality, aesthetic design, and cultural belonging create emotional value that virtual agents cannot substitute.

8. Compute and Energy Infrastructure

The physical infrastructure required to power non-stop real-time agent inference. As billions of agent runs execute simultaneously, specialized data centers, custom silicon, clean power, and grid capacity capture massive economic value.

9. Health, Longevity, and In-Person Care

Hands-on physical health, rehabilitative medicine, longevity protocols, and personal caregiving. Services directly tied to biological well-being and personal human presence remain strictly non-automatable.

10. Hybrid Marketplaces for Humans and Agents

Next-generation transaction networks where autonomous agents discover, negotiate, and purchase goods or services alongside human participants. These platforms support machine-to-machine API commerce governed by human policy boundaries.

11. Real Physical Assets

Land, commercial property, heavy industrial equipment, and vital logistics infrastructure. As digital generation accelerates, capital naturally gravitates toward finite physical assets that cannot be duplicated.

12. Vertical Operational Agents

Autonomous systems engineered to resolve a single, recurring workflow within an industry from end to end, such as inventory purchasing for independent restaurants. Rather than attempting to serve as generalized assistants, they eliminate targeted operational pain points.

13. Agentic Security and Defense

Specialized security solutions engineered to protect autonomous agent fleets, model orchestration layers, execution sandboxes, and sensitive organizational data against emerging attack vectors.

Strategic Takeaways for Builders and Founders

Isenberg's framework emphasizes that when software barriers fall, economic value flows outside the code itself:

1. Treat Software as an Enabler, Not the Destination: With code production commoditized, founders should prioritize unit economics, execution velocity, and outcome quality over generic tool features.
2. Cultivate Defensible Assets Early: Focus on building assets with high replication costs, including proprietary datasets, direct audience relationships, and deep operational integration into vertical workflows.
3. Bridge Digital Leverage with the Physical World: Pairing AI efficiency with physical experiences, hardware, or tangible assets produces durable long-term defensibility.

Original source

• Greg Isenberg (@gregisenberg) Post on X: https://x.com/gregisenberg/status/2107527601778835621
• The Startup Ideas Podcast: 13 Businesses for the Age of AI (YouTube)