Nathaniel Whittemore

One-line fix?

Dock update?

Too often, routine tasks get routed to the priciest path out of fear of losing performance.

This only burns budget for no additional gain.

You wouldn't have Messi play goalie.

Every model has different strengths, whether it's reasoning, speed, cost, or context.

Factory Router automatically picks the right model for every task.

And to show that this works, Factory says that Router delivered the same performance as Opus 4.7 at 20-25% lower cost.

Perplexity also announced a product this week in this domain.

They're calling it Hybrid Agentic Inference, and basically it's an inference routing system

that intelligently distributes AI tasks between resources from your local machine and cloud servers.

Perplexity demonstrated the system at the Computex conference on Monday using their Perplexity computer agent.

The demonstration used local models running on Intel Core Ultra 3 hardware, so basically a relatively high-end consumer device.

Now, the ability to run AI models on local hardware obviously isn't novel, but what Perplexity is saying is new is the system's ability to split up tasks.

Perplexity's orchestrator can break a task down into components and assign them to sub-agents using a variety of different AI models.

The system can then determine which sub-agents need to run on the more powerful cloud inference and which can be completed on local hardware.

The process is all fully automated and requires no decision-making from the user.

And Perplexity pointed out that hybrid inference is especially useful when it comes to private information.

They claim their orchestrator is able to identify sensitive data and ensure it doesn't leave your computer.

Basically, the orchestrator was presented as a way to balance intelligence, accuracy, privacy, and cost when running fully agentic workflows.