Building Better AI Specs: A Developer's Guide

Why Specs Matter More Than Ever

With AI coding agents becoming mainstream, the quality of your specifications directly impacts the quality of the code you get back. A vague spec leads to vague results.

The Anatomy of a Good AI Spec

1. Clear Context

Always start with the what and why:

## Context
We're building a user authentication system for our SaaS app.
The app uses Next.js 14 with App Router and Prisma for the database.
 
## Goal
Add a "forgot password" flow that sends a reset link via email.

2. Visual Evidence

Screenshots and screen recordings eliminate ambiguity. When you show an agent exactly what you're looking at, there's no room for misinterpretation.

3. Acceptance Criteria

Define what "done" looks like:

## Acceptance Criteria
- [ ] User can request password reset from login page
- [ ] Reset email arrives within 30 seconds
- [ ] Link expires after 1 hour
- [ ] User can set new password and login

4. Constraints and Non-Goals

Be explicit about what you're not building:

## Non-Goals
- Rate limiting (handled separately)
- OAuth integration
- Password strength meter

The Pinpoint Approach

Pinpoint automates this entire process. Record your screen, narrate what you want, and Pinpoint generates a structured spec with all the right pieces in place.

No more manual screenshot management. No more forgetting edge cases. Just record, review, export.

Next Steps

Ready to level up your specs? Join the waitlist for early access to Pinpoint.