I just completed something that would have taken me 2-3 weeks of manual work — in less than a day.

Working with a transportation sector non-profit to develop a mobile booking platform, I leveraged AI tools to accelerate our proof-of-concept in ways that fundamentally changed my approach to early-stage product development.

Using AI-powered design tools, I generated functional Figma prototypes that traditionally would have required days of wireframing and iteration. The AI understood user flows for booking systems and generated mobile-first designs that we could immediately test with stakeholders.

Here's where it got interesting. I needed to compare cloud platforms for authentication, authorization, and data management. Manually, this means:

• Reading documentation across AWS, Firebase, and Supabase
• Comparing pricing tiers at different user scales (1K, 10K, 50K, 100K users)
• Understanding service integration complexity
• Evaluating migration paths and vendor lock-in risks

Traditional research time: 6-8 hours minimum, likely spread over several days.

With Claude: 45 minutes of focused conversation yielding a comprehensive analysis with cost breakdowns, implementation timelines, and scaling considerations.

The recommendation for Supabase caught me off-guard. I'd defaulted to AWS thinking "enterprise scale," but the analysis revealed Supabase's unified platform (auth + PostgreSQL + storage) dramatically reduced complexity for our small team, with a clear path to scale and zero cost during POC phase versus AWS's 12-month free tier limit.

We're now building a functional prototype—going from early concept to implementation-ready architecture in record time. AI didn't replace strategic thinking; it eliminated the grunt work that delays it.