Where the bot should stop.

“Research this account” sounds like one task. In practice, it can mean finding sources, extracting facts, making a judgment, updating a record, and telling someone what to do.

Those steps deserve separate decisions. A bot that is useful at gathering information has not automatically earned the next action.

Start with the smallest useful task

A bot can follow fixed rules, use AI, or combine both. A notification triggered by a known property value may need no model at all. Reading several sources and preparing a summary is a different kind of work.

Keeping sources beside the claims helps the reviewer check the output. It also makes “I couldn’t establish this” a usable result, rather than a gap the bot feels obliged to fill.

Connected does not mean decided

APIs connect systems. MCP servers expose tools, resources, and prompts to AI applications; a server may call an API behind the scenes. These connections make capabilities available. They do not decide which actions belong in a particular workflow.

That choice needs to be explicit. Can the assistant read a record, propose a change, or write it? What happens when information is missing, a tool fails, or the result conflicts with an existing value?

Preparing a message and sending it are different actions. So are suggesting a change and applying it. Put the review point at the boundary that matters, and give the person enough context to make the decision.

A small bot with a defined stopping point is easier to understand, check, and improve.