The Four Criteria Test
Not every professional workflow is a good target for an AI tool. Four criteria separate the ones worth building for from the ones that look attractive but aren't.
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The Layer Stack
Professional due diligence workflows are being assembled as stacked, complementary MCP servers — one layer for people, one for data, one for documents. Two of the three layers now exist. The third is the opportunity.
The Wrong Battleground
Choosing the right problem to solve matters less than choosing the right market to solve it in. Two workflows can have identical AI potential and completely different competitive landscapes.
The Boring B2B Pattern
The most profitable AI businesses in 2026 are not the most impressive ones. They're in workflows that are painful, high-stakes, and completely unglamorous — and that's exactly why they work.
The Engineer Gap
The MCP ecosystem in 2026 is overwhelmingly built by engineers, for engineers. The tools that don't exist yet are the ones built for professionals who aren't engineers — and that's the interesting space.
The Retention Asymmetry
Domain-specific AI tools retain customers at 3-5x the rate of horizontal tools. This isn't a coincidence — it's structural. When the tool understands your workflow, switching means more than changing software.
The Credit Wallet
Credit-based pricing is becoming the dominant model for AI-native SaaS. It's not just a billing mechanism — it's a way of making AI costs predictable for buyers while keeping pricing aligned with actual usage.
The Per-Resolution Shift
AI pricing is moving from seats to outcomes. The most successful AI products in 2026 are charging per resolved ticket, per completed draft, per analyzed document. This isn't a billing detail — it's a product philosophy.
What the Enterprise Buys
Enterprise buyers aren't paying for AI. They're paying for domain knowledge that makes AI usable in their workflow. The tools that command enterprise prices are the ones that know what the profession expects.
The Fifteen-Minute Lease
Lease abstraction used to take four to six hours per lease. AI has brought it to fifteen minutes. The question now isn't whether AI works — it's where the output goes.