In the emerging era of AI agents and tool-using models, a new kind of product strategy is taking shape. Products are no longer just competing for user attention—they’re competing to be the default tool a model chooses to invoke.
I wrote a deep dive on how Model Context Protocols (MCPs) are reshaping product thinking. It covers:
- Why agents (not humans) are becoming primary users
- How discoverability, callability, and context readability become critical
- Why a product’s success may soon depend on whether it's “Agent-Native”
- What metrics PMs should track to win in this new invocation-first world
Would love feedback and discussion—especially from folks building in the AI infra or agent tooling space.
In the emerging era of AI agents and tool-using models, a new kind of product strategy is taking shape. Products are no longer just competing for user attention—they’re competing to be the default tool a model chooses to invoke.
I wrote a deep dive on how Model Context Protocols (MCPs) are reshaping product thinking. It covers:
- Why agents (not humans) are becoming primary users - How discoverability, callability, and context readability become critical - Why a product’s success may soon depend on whether it's “Agent-Native” - What metrics PMs should track to win in this new invocation-first world
Would love feedback and discussion—especially from folks building in the AI infra or agent tooling space.