Curious if anyone is finding success using certain prompts to get something done for in-flight projects, for me personally I found success in having Claude, Cursor etc create architecture, flow-charts, and logic markdown files for me to reference later on if I'm digging into a specific error, or when I need to update a delicate feature. It's not bullet proof, but I also tend to use "As a senior Developer, Perform a Root Cause Analysis on the following errors xxxxx, and symptoms I'm noticing xxxxx do not act on it, provide contributing factors, rank these factors by likelihood, and create a remediation plan". The more I push the AI system to understand a problem holistically (if I can at least) the bugs, and error conditions are sometimes easier for me to isolate and have AI apply fix without breaking some logic elsewhere. Again, none of this is guaranteed, just sharing my personal experience wrestling with in-flight builds that I'm expanding or adding on to and encountering bugs with. Curious, how do you all handle this? got any tips to share?

I’m going through the Complete SaaS Build series, and it’s incredibly valuable. One key takeaway is that the more structured our prompting and documentation process is, the better results we can get from Claude or any LLM. It also breaks the myth that anyone can build a production-grade app just by prompting. You still need a solid understanding of product development and must review each output with a product manager’s mindset, orchestrating it carefully through each development stage, just like we would without AI. Huge thanks to @Zubair Kakakhel for sharing such insightful and experienced content. Guys what's your takeaways ,would love to hear

The first (& I think the most crucial part) of the course has been uploaded now. The architecture & planning which covers - Foundation PRD - Screens - Database - Security 80% of the effort in AI coding is in the planning stages.. Direct link: https://www.skool.com/idea-to-app-3209/classroom/e615a87c?md=a1d211fa36054a728054afe698e5541f The remaining videos are coming. I'm traveling & its harder/slower to review etc. It took about 15 hours to record & a lot more hours & people to edit. Editing/reviewing etc is a slow process but a lot of people have been asking for this already. Looking forward to hearing feedback & see how everyone learns along the journey. Drop comments as you watch here!

I recently built the same AI-first Property Management MVP using both Lovable and Bolt , full workflows like: - Landlord adds property - Tenants apply - AI shortlists applicants using OpenAI - Maintenance tickets auto-replied by AI - Role-based flows (tenant/landlord/admin) Here’s what I learned 👇 Where Bolt Stood Out ✅ Fewer Prompts, Smarter Outputs ,It understood things like “show landlord their own properties + applicants” without extra breakdowns. ✅ Better Logic + State Flow Screen transitions, app state, conditional logic , Bolt just flowed. Lovable needed more wiring. ✅ AI Native Integrating (for screening or replies) felt seamless in Bolt. Less manual setup. Bottom Line If you're building logic-heavy, AI-powered internal tools, 🔹 Bolt = less prompting, more reasoning 🔹 Lovable = great design, but more manual for workflows What Are You Using? Tried Bolt, Lovable, or something else like BuildShip or Framer AI? What helped you more in prompt bases development of idea

While trying to build production-grade AI apps, I realized getting from 0 to 80% is easy with today’s tools. But the last 20% shipping, performance, reliability is where things get real. Biggest lesson? AI won’t magically solve unclear thinking or messy UX. Excited to sharpen those skills here and learn from how others cross that finish line.