Harness, Loop, & Graph Part 2: A Simple Explanation of How AI Agents Are Built
We’re watching the largest, fastest-moving business and operating model disruption ever play out right now. The core of both disruptions is the transformation from delivering artifacts to delivering outcomes. Google, Microsoft, and Meta all discussed the transformation during their earnings calls.
The largest tech companies are shifting their business models to provide platforms that support an outcomes economy and outcomes-based operating models. Microsoft ramped up a massive organization of FDEs to help businesses make the transformation. AI, information, and agents are transformation drivers, but the technologies alone will not transform the business.
Businesses don’t have all the pieces to make the transformation in a single step. Harnesses, loops, and graphs are a bridge that helps the business and operating model take advantage of AI, information, and agents by generating value while building the pieces required to transform. The architecture and technical capabilities mature in parallel with the business and operating models’ transformations.
Mark Zuckerberg explained information flywheels as the moat Meta is building on. The flywheel you build by watching a community (either internal users or customers) use a product is the advantage. Every time someone uses the product, they generate contextual data that can be used to improve the product.
That is the purpose of loops and graphs. They are the mechanisms that build the information flywheels that enable the business to progress on its business, operating, and technology model transformations. These are the bridges from an artifacts-based business to an outcomes-based business.
Realize that once the business crosses the bridge, it is never going back. Businesses that don’t build and cross the bridge will not survive. This architecture is a technical and strategic necessity.