TLDR

This Notion document supports my Medium article on testing AI tools across the Product Development Lifecycle.

It contains the exact prompts used to build a fictional motorcycle maintenance tracker using AI tools.

I ran a complete PDLC from discovery to handoff using only AI-driven workflows.

The entire experiment took 58 minutes end to end.

This experiment demonstrates:

• Where AI accelerates the product development lifecycle
• What each tool does well and where it falls short
• Where human judgment still matters

Use this library to replicate the experiment, adapt the prompts, or test new tools.

👉 The full context and insights are explained in the linked Medium article.

👉 Here is a summary of the PDLC stages, relevant AI tools, and time taken.

💬 Prompt used

All exact prompts used are documented here for replication or further exploration.

1. Discovery

→ SWOT analysis

Act as a [product strategist] and perform [detailed SWOT analysis] for [an app that tracks a motorcycle’s maintenance schedule based on brand, model, and service intervals specific to India. Use my motorcycle, Hunter 350cc 2025 (purchased on 4 June 2025) as reference.]