This breakdown on AI agents and their specialized use cases hits the nail on the head. The shift from monolithic LLMs to domainmspecific models feels like the natural evolution of the AI landscape especially with the rise of edge deployment. The example of Casetext shows how narrowing the scope can actually drive better outcomes. Do you see interoperability between these specialized agents as a future standard or will most vertical Ai ecosystems remain siloed?
Great question! While specialized AI agents will likely thrive in their respective domains—particularly where data privacy and tight integration are crucial—I do see increasing momentum toward interoperability standards. Think of it like the evolution of web services: Initially, companies built isolated APIs, but over time, protocols like REST and GraphQL emerged to facilitate cross-service interactions.
Ultimately, the industry tends to move toward seamless integration because interoperability can unlock a multiplier effect. The challenge is balancing this collaboration with data privacy and ensuring each agent’s proprietary “secret sauce” remains protected.
This breakdown on AI agents and their specialized use cases hits the nail on the head. The shift from monolithic LLMs to domainmspecific models feels like the natural evolution of the AI landscape especially with the rise of edge deployment. The example of Casetext shows how narrowing the scope can actually drive better outcomes. Do you see interoperability between these specialized agents as a future standard or will most vertical Ai ecosystems remain siloed?
Great question! While specialized AI agents will likely thrive in their respective domains—particularly where data privacy and tight integration are crucial—I do see increasing momentum toward interoperability standards. Think of it like the evolution of web services: Initially, companies built isolated APIs, but over time, protocols like REST and GraphQL emerged to facilitate cross-service interactions.
Ultimately, the industry tends to move toward seamless integration because interoperability can unlock a multiplier effect. The challenge is balancing this collaboration with data privacy and ensuring each agent’s proprietary “secret sauce” remains protected.