AI Should Make Work Faster — So I Built a Demo to Show How

AI Should Make Work Faster — So I Built a Demo to Show How

AI is dominating headlines, yet many people still aren’t sure what it actually does or how it can make their work easier. So I built a simple demo application to show—very concretely—how AI can automate slow, manual workflows and enable teams to move faster with more consistency.

The Scenario

If you’re a Product Manager, you’re constantly transforming raw ideas into structured Product Requirements Documents (PRDs) that downstream teams can use to build, test, and ship new features.

The Problem

Creating PRDs is time‑consuming and often inconsistent.
Without strong governance, documentation quality varies across teams, leading to:

• unclear requirements
• confusion for delivery teams
• rework and delays
• inconsistent expectations across the organization

These issues ripple through design, development, QA, and deployment.

The Solution

The Product Document Generator automates PRD creation by taking four simple inputs:

• Idea description
• Target market
• Constraints
• Optional context

The AI then produces a clean, structured Product Document that includes:

• Product Overview
• Goals
• Success Metrics
• User Stories
• Risks
• MVP Scope

Work that typically takes hours can be completed in seconds—and with consistent formatting every time.

Why This Matters for Real Business Workflows

This is just one example. The same pattern can be applied to any workflow.

Imagine automating your entire project intake process:

• standardizing scope and requirements
• drafting WBS and timelines
• generating risk assessments based on historical project data
• consolidating RAID logs for reporting
• producing post‑mortem documents that feed lessons learned back into the model

Or imagine a law firm where AI:

• conducts the initial client discovery call
• identifies which partner is best suited to the case
• assists in preparing or reviewing legal documents
• provides instant answers about contract clauses

The possibilities extend to every industry where repeatable processes, documentation, or decision‑support are required.

Try the Demo

I created this demo to show organizations how AI can help increase capacity—especially those facing hiring freezes or resource constraints.

Click here to access the demo.

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Support

I built this quickly and handled QA myself, so if you spot a bug, feel free to email me at: support@tebaulttechnologygroup.com

Let’s Talk About What’s Possible

If you’d like to explore how AI can create operational capacity inside your organization, I offer a free consultation.
 

For the technical folks

Architecture

Operating Cost:

Estimated monthly cost: <$10 for hundreds of generations

Frontend:
- React 18.3 with TypeScript
- Material-UI 6.3 
- AWS Amplify UI React 
- Vite (Build tool)

Backend:
- AWS Amplify Gen2
- AWS Lambda (Bedrock integration)
- Amazon DynamoDB (Data storage)
- AWS Cognito (User auth)
- AWS AppSync (GraphQL API)

AI/ML:
- AWS Bedrock
- Anthropic Claude 3 Haiku (cost efficient ~$0.004 per generation)

GitHub:

https://github.com/TebaultTechnologyGroup/requirements-agent