What is agent context? Definition for AI coding workflows

Agent context is the body of input an AI coding agent uses to ground its next action — the files, instructions, screenshots, and conversation history it can read at the moment of the request.

The agent has nothing else to go on. It cannot ask a teammate, scroll through Slack, or remember what the team discussed yesterday. Whatever the context contains, the agent treats as the world; whatever is missing, the agent fills with plausible defaults that may or may not match the team's intent.

Building good context

The principle is the same as writing a good handoff to a human contractor: state the goal, show the relevant code or screens, name the constraints, and leave out the noise. The difference is that the agent will not push back if the context is unclear — it will produce an answer that matches what it can see, even when what it can see is incomplete.

Visual context turns out to be a force multiplier. A cropped screenshot of the broken state is worth more than a paragraph trying to describe it, and the agent can read both. A markdown document with the image inline, the source URL, and a sentence about expected behavior gives the agent everything a teammate would need.