# Route a coding agent's questions by the kind of decision, and log every answer

> A team building a business system with coding agents has the agent stop and ask, with options, when a task runs past its spec. Questions about product direction, rule exceptions or loosening a check go to a person; routine design calls are answered from written rules and earlier rulings. In one week, 762 questions, 59 answered by the owner.

- URL: https://paperchasewebb.ai/bots/marketplace/items/route-a-coding-agent-s-questions-by-the-kind-of-decision-and-log-every-answer/
- Type: Agent use case pack
- Category: Vibe coding
- By: PaperChaseWebb
- Works with: Plain .md
- Price: Free USD
- Difficulty: Intermediate
- Setup time: 30 min
- Time to result: One working session
- Format: Markdown (.md) file, route-a-coding-agent-s-questions-by-the-kind-of-decision-and-log-every-answer.md
- Version: 1.0, updated 2026-10-29
- License: Personal and commercial use. Credit the original source when you share the workflow.

## What you end up with

The figures are the team's own.

## What you get

- A plain-language summary of the workflow
- A fill-in prompt template
- What to watch out for
- A link to the original source

## Who it is for

Builders who already use AI agents and want a proven workflow they can copy into their own project.

## Tools needed

- Coding agents: stop and ask with options when the spec runs out
- Rules and earlier rulings: answer routine design questions
- The owner: answers direction, exceptions and anything that loosens a check
- You need: An AI coding agent or chat model
- You need: A small real task to try it on

Cost to run: Free with the agent plan you already use.

## How it works

1. **Tell the agent to stop and ask with two or three options when the task.** Tell the agent to stop and ask with two or three options when the task goes past the spec. Expected: Done before you move to the next step.
2. **Sort questions into: product direction, rule exception, loosening a ch.** Sort questions into: product direction, rule exception, loosening a check, routine design. Expected: Done before you move to the next step.
3. **Send the first three to a person; answer routine ones from your rules .** Send the first three to a person; answer routine ones from your rules and past rulings. Expected: Done before you move to the next step.
4. **Record every answer with who gave it and point later questions to it.** Record every answer with who gave it and point later questions to it. Expected: Done before you move to the next step.
5. **Treat 'unsure which kind' as a person question.** Treat 'unsure which kind' as a person question. Expected: Done before you move to the next step.

## Sample prompt: Workflow template (Coding agents, Rules and earlier rulings)

```
Apply this workflow to [your project]:
1. Tell the agent to stop and ask with two or three options when the task goes past the spec.
2. Sort questions into: product direction, rule exception, loosening a check, routine design.
3. Send the first three to a person; answer routine ones from your rules and past rulings.
4. Record every answer with who gave it and point later questions to it.
5. Treat 'unsure which kind' as a person question.
Stop and ask me before anything irreversible: deploys, payments, sends or deletes.
```

Adapted by PaperChaseWebb. Not the original author's prompt.

## Free preview of route-a-coding-agent-s-questions-by-the-kind-of-decision-and-log-every-answer.md

````markdown
# Route a coding agent's questions by the kind of decision, and log every answer

PaperChase agent use case (free feed entry), version 1.0. Source: [u/DynoKore](https://www.reddit.com/r/AI_Agents/comments/1xiiris/we_route_our_coding_agents_questions_by_type_of/), 2026-10-28.

## What they did

Every answer is recorded with who gave it, so later questions can cite earlier decisions instead of being asked again. In the week to 26 October 2026 the agents raised 762 design questions; of the 737 answered, the owner answered 59. The rule they stress: 'not sure which route' counts as a reason to ask a person, otherwise the agent ends up judging the risk itself.

## Worth knowing

The figures are the team's own. The idea scales down: even a solo builder can keep a decision log the agent reads before asking. A related thread asks which early question saved the most rework; one example was whether a support bot needs account data or just docs.
````

## Worth knowing

- The figures are the team's own. The idea scales down: even a solo builder can keep a decision log the agent reads before asking. A related thread asks which early question saved the most rework; one example was whether a support bot needs account data or just docs.
- Figures are as reported by the original author and were not re-measured by us.

## Questions

**Where does this come from?** A public post credited to u/DynoKore. Source: https://www.reddit.com/r/AI_Agents/comments/1xiiris/we_route_our_coding_agents_questions_by_type_of/

**Is it free?** Yes. Feed entries are free to read and download.

## How to get it

Free sample. Download it directly at https://paperchasewebb.ai/bots/marketplace/items/route-a-coding-agent-s-questions-by-the-kind-of-decision-and-log-every-answer/, no signup.

Seller: PaperChaseWebb Inc., mgmt@paperchasewebb.com