Outbound Desk

# Build Outbound Desk

You are a senior full-stack engineer pairing with me on a side project. Build a working first version of the product described below. Read the whole brief before writing any code, then follow "How to work" at the end.

## The idea

**Outbound Desk.** Give an agent your customer profile and a list you already have permission to contact, then review each researched draft in an approval queue. Nothing goes out until you approve it.

**Why now:** Franco, an outbound sales agent that runs on a coding subscription, passed 900 GitHub stars within weeks of its Oct 15 launch. A Dev.to post on Oct 14 also made the case for spending limits on AI agents using paid data. An approval queue is the part small teams can trust.

**Who it is for:** Founders and small teams doing their own outbound

**What makes it fun:** An eager junior rep that cannot hit send without you.

## Scope

- **Build time:** One week. Size every decision to ship a working first version inside this window.
- **Technical ambition:** Level 3 of 5, "APIs or integrations". The product leans on third-party APIs. Wrap each integration in its own module, handle its failures and rate limits, and cache what is safe to cache.
- **First version only.** Ship the core features below end to end. Stretch goals are listed so you can design around them, not build them.

## Core features (each must work end to end in the first version)

1. Customer profile and offer
2. Lead list import
3. Approval queue for each draft
4. Daily sending limit and opt-out list

## AI features

- Researches each lead from public pages you allow
- Drafts a short email and shows its sources

How to build them:
- Put every model call behind one server-side module with a typed interface, so the provider can change without touching the UI.
- Read API keys from environment variables only, and document each one in `.env.example`.
- Write prompts as versioned constants with clear instructions and an example of the expected output; parse and validate responses before using them.
- Handle timeouts, rate limits, and malformed output with a graceful fallback the user can understand. Stream responses where a wait would exceed a couple of seconds.
- Never let a feature depend on the model being perfect. Show the result, let the user edit or retry.

## Stretch goals (later, not in the first version)

- Follow-up drafts
- Reply sorting
- Connect your own email account

Leave clean seams for these (a module boundary, a nullable column, a feature flag), but do not implement them unless I ask.

## Tech stack

Use exactly: Next.js, Supabase, Claude.

Stay on current stable versions, follow each tool's official conventions, and add a library only when the standard library or the chosen stack cannot do the job cleanly. If part of this stack is a poor fit for a specific requirement, say so and propose the smallest change.

## Owner's notes

Written by me, the project owner. Treat these as requirements and preferences that override the generated material above when they conflict.

The first version should be exactly this, and no bigger: Import ten leads and approve or reject a draft for each, with no sending yet.

## Build plan (with saved progress)

0 of 4 steps complete. Resume at step 1: Profile and list. Before you start it, check what is already implemented so you do not repeat finished work.

1. **Profile and list** [not started]
   Who you sell to and who is on the list.

2. **Research step** [not started]
   Read the sources you allow for each lead.

3. **Approval queue** [not started]
   Edit, approve, or reject every draft.

4. **Send with limits** [not started]
   A daily cap and an opt-out list.

## Definition of done for the first version

- [ ] Customer profile and offer works end to end, with real data, not a placeholder.
- [ ] Lead list import works end to end, with real data, not a placeholder.
- [ ] Approval queue for each draft works end to end, with real data, not a placeholder.
- [ ] Daily sending limit and opt-out list works end to end, with real data, not a placeholder.
- [ ] Every screen handles loading, empty, and error states.
- [ ] Typecheck, lint, and any tests pass, and the main user flow was exercised by hand.
- [ ] A README explains setup, environment variables, and how to run it locally.

## Quality bar

- Responsive from a phone to a desktop, keyboard-accessible, semantic HTML, visible focus states, labelled inputs, and sensible contrast.
- Loading, empty, and error states for every screen that reads or writes data. Errors say what happened and what to do next.
- Validate on the server, never trust the client, and keep secrets in environment variables with a committed `.env.example`.
- Type-safe end to end. No `any` without a comment explaining why.
- Small, readable modules named after what they do. No premature abstraction, no dead code, no TODOs left for later without a note.
- Sensible defaults over settings. If a choice is not in this brief, pick the simplest option that keeps the product coherent and say what you chose.

## How to work

1. **Read, then restate.** Summarize the product in three sentences and list your assumptions. Ask only the questions that block implementation. For everything else, decide and note the decision.
2. **Plan before code.** List the files and modules you will create, in build order, mapped to the core features. If a build plan is included above, use it instead: resume at the first step not marked done and check what already exists before touching it.
3. **Set up.** If a project already exists, inspect its code, instructions, and conventions first and build on them. Otherwise scaffold the stack above with linting, formatting, a typecheck script, `.env.example`, and a README stub.
4. **Model the data first.** Define the types, schema, and any migrations before the UI, so the shape of the product is settled early.
5. **Build in vertical slices.** Finish one core feature end to end (data, logic, UI) before starting the next. Keep the app runnable after every slice and commit each slice with a message that says what changed and why.
6. **Then the interface.** Apply the quality bar above to each screen as it lands, not as a final pass.
7. **Verify.** Run typecheck, lint, and tests. Exercise the main user flow by hand. Check each item in the definition of done and each acceptance criterion.
8. **Report.** Tell me what works, what you tested and how, what is not done, every setup step I must complete myself, and the three most useful next steps. Never claim a service, test, or flow was verified when it was not.

If you can edit and run the project, start implementing right after the short plan. If you cannot, give me concrete code and the exact commands to run for the next step.

Rules: keep the product name and the scope as written, do not invent features, prefer boring and proven choices, and stop to ask me when a decision would be expensive to reverse.