Internal tool PRD template

Overview

Internal tools live or die by their access model. Who can view what, who can edit what, and who should never see that column at all — these decisions need to be locked in before you write a single line, not after you've built three screens and realised HR and Finance are sharing a dashboard. A good internal tool spec starts with roles, not features.

Draftlytic asks you the questions that surface those decisions — primary users vs admins vs read-only viewers, the core workflow being replaced, integrations with existing systems — then turns your answers into a structured, editable spec you can drop straight into Cursor, Lovable, or any AI coding tool. Not a Google Doc. A real brief with a data model, navigation map, and a non-goals list that tells the AI exactly what not to build.

Role-based access and admin workflows baked in from the start

Internal tools almost always have at least two user types: the people who use the tool day-to-day and the admin or ops person who configures it, manages records, or has override access. Draftlytic captures both in your spec — personas, auth methods, and per-feature tier/role assignments so it's clear which screens and actions belong to which user type. If you're building a customer support queue, an inventory tracker, or an internal approvals flow, the spec will reflect who triggers each action and who can override it — not just a flat list of features.

A typed data model and the workflow it replaces

The single most useful thing an internal tool spec can do is name the entities. For a leave-management tool that's employees, requests, approvers, and policy rules. For an ops dashboard it might be orders, statuses, and assignees. Draftlytic generates a typed data model (entities, fields, types) alongside the feature list, so your AI coding tool knows what tables to scaffold. It also captures the non-goals — the explicit do-NOT-build list — which is critical for internal tools where scope creep from stakeholders is the default failure mode.

Export a spec your AI coding tool can actually use

Once your internal tool spec is built you can export it as Markdown, PDF, or ZIP — or push it straight to a connected GitHub repo. There's also a separate implementation-plan export that sequences the build into phases, so you're not handing a 40-feature spec to an AI and hoping it starts in the right place. AI Scan flags gaps before you export: missing auth details, vague acceptance criteria, features without a clear user role. Free to start, no credit card needed.

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