Moat

A durable competitive advantage that protects a business from rivals.

Example

Proprietary data that competitors cannot easily obtain, or deep integration into customers' workflows.

Access to a capability everyone else can also use is not a moat.

Edge — The specific reason you can expect a better-than-average result in a particular market - something you know, see or can do that the average buyer of that asset cannot.
Technical Risk — The risk that a technology will not work as intended, cannot be produced at scale, or takes much longer to develop than planned.

The real competitor is often a spreadsheet or doing nothing — Competitive diligence maps every alternative a customer could choose, including internal tools and inaction, and uses win and loss data to see where the company actually wins. (10 min)
AI companies can have software growth with hardware-like costs; deep tech trades time for defensibility — AI businesses must be judged on the cost of running models and on what protects them from competitors using the same models. Deep tech companies face technical risk and long timelines before revenue, in exchange for harder-to-copy advantages. (12 min)
Ask why now, and what stops the next ten companies — Evaluating competition means understanding why this opportunity exists now, who else can serve the customer, and what would make this company hard to displace once it is working. (11 min)
An AI product's margin and moat depend on what it does not own — Companies built on AI models carry specific risks: dependence on model providers, inference costs that grow with usage, rights to training data and outputs that are hard to evaluate. Diligence tests each. (11 min)
A moat is what stops a competitor copying your success — Competitive advantages come from switching costs, network effects, proprietary data, brand, scale and distribution. Network effects are especially powerful, and especially often claimed without evidence. (11 min)