How to pair program with an AI coding agent

Pairing with an AI agent is like pairing with a teammate who never admits when it is lost. It will guess instead of asking, and a wrong guess can cost minutes or hours if you catch it late. The difference between a five-minute detour and a full redo is how fast you surface the confusion and keep the loop tight.

Start with a single file and a one-sentence plan

Open the smallest slice of the task you can still call a slice. A single function or a small component is enough. Ask the agent to explain the change in one sentence and to name the file it will touch next. If it cannot, you have found the first sign of confusion.

Force the agent to commit to the next step

Require the agent to answer three things before it writes code: the file it will change, the function inside that file, and the exact behavior it will add or fix. Write those three items in the chat yourself and ask the agent to confirm. If it hedges or changes its mind later, stop it immediately.

Keep every message under two sentences

Agents optimize for speed, not clarity. If you let them write long, discursive messages, they hide gaps in their understanding behind walls of text. A two-sentence limit forces them to surface confusion early, because they cannot bury it in paragraphs.

• Stop after the first file change and read the diff yourself. Do not wait for a full diff at the end.
• If the agent’s change touches more files than you expected, ask it to explain why. The answer often reveals a misunderstanding of the task.

Ask for a plan when the task spans more than one file

If the task requires changes across multiple files or libraries, ask the agent for a one-sentence plan before it starts. A long plan is usually a sign the agent has not scoped the work, so insist on brevity. The plan should name the entry point, the files it will touch, and the order it will visit them.

Reject plans that hide gaps

Look for phrases like “among other things” or “plus some cleanup”. Those are the agent’s way of deferring decisions. Ask it to name the specific files and functions it will change first, and what it will do in each one. If it cannot, the plan is not ready.

• If the agent’s plan involves touching shared state or configuration, ask it to describe the invariants it assumes. Shared state is where agents most often guess wrong.
• Require the agent to update the plan after each file change. A plan that drifts is a plan that hides new confusion.

Stop wrong guesses within the first minute

Agents will not tell you they are confused, but they will often give you a wrong answer before they give you no answer. Watch for three signals: the agent starts editing a file it should not touch, it proposes a solution that does not match the stated goal, or it falls silent for more than 30 seconds while you wait for the next step.

Use silence as a signal

If the agent does not respond within 30 seconds to a two-sentence prompt, treat the silence as a confession of confusion. Ask it to restate the goal and the next step. If it cannot, you have caught the mistake before it wrote code.

Interrupt early, not late

Agents rarely self-correct once they have written code. If you let them proceed after a wrong guess, they will compound the error in the next file. Stop the agent, name the mistake, and ask it to restate the goal and the next step before it continues.

• If the agent’s change introduces a new dependency, ask it to justify why that dependency is necessary. Unnecessary dependencies are a common source of wrong guesses.
• Before you approve a change, run the tests yourself. Agents can miss edge cases in integration tests or environment-specific behavior.

Overlap warnings arrive when an agent claims work, which the five tools each contribute to in a different way. If you see an overlap warning, stop the agent immediately and clarify the boundaries of the work. Agents do not handle overlap gracefully once they have written code.

Tighten the loop after the first change

After the agent finishes a change, read the diff yourself instead of trusting its summary. Agents often miss edge cases or misdescribe the impact of a change. A human review catches what the agent never knew to look for, especially in integration points or shared state.

Insist on a summary you can verify

Ask the agent to write a two-sentence summary of the change: what it did and why it did it. Then read the diff and check that the summary matches. If it does not, the agent has hidden something in the implementation.

Revisit the plan after every change

Tasks drift as agents encounter unexpected files or constraints. After each change, ask the agent to restate the goal and the next step. If the plan has changed, update it in writing so both of you stay aligned. A drifting plan is a sign the agent is guessing its way forward.

• If the agent’s change touches configuration files, ask it to explain the rollback plan. Configuration changes are the hardest to undo once they are merged.
• Before you merge, run the full test suite locally. Agents can pass unit tests while breaking integration tests, especially in CI environments.

If you are pairing across repositories or machines, the Concord MCP server keeps the agent’s context visible to you both. It surfaces overlap warnings and task ownership in real time, so you can stop wrong guesses before they compound.

A wrong guess costs seconds when you surface the confusion early, and hours when you catch it late.