Agent Routing on AIBussin — AI applications, systems and books

Capabilities and Routing

Sat, 08 Aug 2026 17:09:00 +0100

Every mechanism built so far has taken the action set as given. The action boundary validates a proposal against a fixed list of permitted action types. Candidate generation samples several proposals from the same list. The runtime-state chapter watches what happens after execution and decides whether to continue. All of them assume that somebody, somewhere, already decided which capabilities the policy could choose from.

So far we have treated that decision as an input. This chapter makes it explicit, because the capability surface changes the decision problem the policy has to solve and therefore belongs inside the agent architecture itself.

Advanced Agents From First Principles 05: Is One Model Doing Everything? Build a Mixture of Experts at the Agent Level

Sat, 08 Aug 2026 23:41:00 +0100

A common agent architecture starts simply:

request
 ↓
model
 ↓
action

That simplicity is valuable.

It should be your default.

But eventually you may notice something strange.

The same model is being asked to do everything:

classify the task,
search documentation,
reason about code,
write SQL,
review a patch,
summarize logs,
judge another model,
decide whether a deployment is safe,
and answer simple questions that did not require an expensive model in the first place.

At that point the problem may no longer be:

Agents From First Principles 06: AI Agent Chooses the Wrong Tool? Design Better Tool Interfaces, Schemas and Routing

Sat, 08 Aug 2026 17:09:00 +0100

An agent can have a perfectly capable model and still behave badly because its tools are badly designed.

This is one of the most common agent failures in production:

user goal
 ↓
agent
 ↓
wrong tool
 ↓
wrong action

The model may understand the task.

The agent may have enough context.

The problem is that the action space is ambiguous.

If two tools overlap, their descriptions are vague, their schemas are huge, or their results are difficult to interpret, the model has to guess.