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Build an Internal Dashboard

The opposite of a marketing site: a dense, function-first admin tool for your team or your customers' ops. Material UI for speed, custom shadcn if you must brand it.

Repos
19
Layers
11
Build time
About 1 month
Outcome
See below
You will ship

A multi-page admin with auth, role-based access, data tables, charts, and CSV export.

01

Framework + UI

2 repos
02

Tables + Data

2 repos
03

Charts

3 repos
8 more layers · 12 more repos · members only
  • DB + Auth2 repos
  • Forms + Validation2 repos
  • Tables (advanced)1 repo
  • Layout + drag2 repos
  • Auth + RBAC1 repo
  • Export + reporting2 repos
  • Component documentation1 repo
  • Email (digest / alerts)1 repo
12 more curated repos · unlock full access · members only

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See pricing
How to build build an internal dashboard with AI

The 4-step AI workflow

The AI agents are good at code. They're bad at deciding what stack to use. This bundle does the second part. You bring the agent.

  1. 1
    Ideate with ChatGPT or Claude.ai (web)
    Paste your idea: “I'm building build an internal dashboard. Help me sharpen the product spec — features, edge cases, MVP scope.” Iterate for 10-15 minutes until you have a clear one-page brief.
  2. 2
    Pick your coding agent
    For this kind of bundle, we recommend Claude Code — Sonnet 4.6/4.7 handles full-stack multi-file reasoning best. See the install guide → Cursor and Codex are also great; pick the one you already pay for.
  3. 3
    Feed this bundle to the agent
    Open Claude Code / Cursor / Codex in an empty folder, then paste:
    I'm building build an internal dashboard. Use this bundle as the source of truth for the stack:
    https://stackpicks.dev/build/internal-dashboard
    
    Brief from my product spec:
    [paste your brief from step 1]
    
    Follow the bundle order strictly:
      1. Framework + UI
      2. Tables + Data
      3. Charts
      4. DB + Auth
      ...
    
    Stop and confirm with me after each layer.
  4. 4
    Wire one layer at a time, commit between each
    Don't let the agent install everything before the first git commit. One layer = one commit. Catches drift early, easy rollback.

Beyond the bundle

  1. 1Ship the boring version first. The bundle above is the maximalist list. For an MVP, start with 60% of these and add the rest when real users ask.
  2. 2Deploy early. Push to Railway / Vercel after layer 02 (auth) — not after layer 09. Production breaks differently than localhost.
  3. 3Read CLAUDE.md / .cursor/rules in this repo for the project conventions your AI agent should follow.
  4. 4Iterate on the take. If a repo here doesn't fit your specific use case, tell us — contact — and we'll add a better one within 60 minutes.
Build an Internal Dashboard — bundle of 19 repos — StackPicks