Sparround

The live task: demonstrating agentic coding

Some interviews ask you to code live with an AI tool. The format is growing because, unlike a conversation, it shows real working habits.

What the interviewer watches:

1. How you frame the task — do you supply context, set boundaries, give a verification path.

2. How you assess the result — do you read it, or accept and move on.

3. What you do when it's wrong — have it fixed or fix it yourself, and which when.

4. When you decline to use the agent — some things are faster by hand, and knowing that is a signal.

5. Whether you can explain it — do you understand the code the agent wrote.

DoDon't
Think out loudType silently and wait for output
Add a verification path to the taskSay "fix this" and accept whatever comes back
Read the diff and comment on itMove on without reading
Move in small stepsAsk for everything in one prompt
Type the trivial thing yourselfSend everything to the agent, even one line
Note the agent's mistake calmlyApologise for the agent's output

The most common mistake: accepting the agent's output without reading it. The interviewer sees it immediately, and it outweighs the rest of your technical performance as a negative signal. Reading the diff and commenting in one sentence ("state hoisting isn't right here, I'll fix it") is the strongest positive signal.

The format can also appear without a tool: "how would you give this task to the agent?" Here the answer is a written prompt — and the prompt's quality is what's assessed.

Elements of a good prompt: - Location and context — which file, which pattern. - A concrete requirement — what should be done. - Constraints — what must not be touched. - Verification — the done criterion and the command.

Without those four the prompt stays at the level of "improve the code" and tells the interviewer nothing.

📚 Sources and documentation